Abdelmonom Hajjej
email: abdelmonom.hajjej@supcom.tn

Marwane Ayaida
email: marwane.ayaida@uphf.fr

Sameh Najeh
email: sameh.najeh@supcom.tn

Nadhir Messai
email: nadhir.messai@supcom.tn

Leila Najjar
email: leila.najjar@supcom.tn

Robust backbone network based on hybrid selection of relays for multi-hop data dissemination in VANETs

Keywords: Vehicular networks, VANETs, Data dissemination, Backbone, Relay nodes, Multi-hop

Broadcasting

Introduction

The ever-growing number of vehicles combined with the unprecedented technological progress pose a serious interest from researchers and recent automotive markets in the emerging Vehicular Ad-hoc NETworks (VANETs). VANETs open up the possibility of the connected car concept through enabling a Vehicle-to-Everything (V2X) communication paradigm, which can boost the development of numerous Intelligent Transportation Systems (ITS)-based applications ranging from entertainment to safety-related, including navigation and infotainment services [START_REF] Lee | Vanet applications: Past, present, and future[END_REF]2]. Realizing cooperative communications between vehicles without the need of the coordinator entities, e.g., Road Side Unit (RSU), is among the primary motivations of VANETs since they help to reduce the economical cost of the connected cars implementation, as well as avoiding some intrinsic problems brought by the use of a centralized network manager, such as the channel competition and packets congestion problems. To achieve this goal, each vehicle in VANETs is assumed to be equipped with a Dedicated Short-Range Communication (DSRC) [START_REF] Kenney | Dedicated short-range communications (dsrc) standards in the united states[END_REF] device, making it able to directly exchange information with its nearby neighbors, e.g., the exchange of Basic Safety Message (BSM) [START_REF] Ayoob | Efficiency broadcast base safety message bsm through vanet based on transmit packet coding (tpc)[END_REF] or Cooperative Awareness Message (CAM) [START_REF] Etsi | Intelligent transport systems (its); vehicular communications; basic set of applications; part 2: Specification of cooperative awareness basic service[END_REF].

In VANETs, some information are recognized as data for the public interest, where their realtime delivery could significantly enhance the traveling experience [START_REF] Wu | A low latency path diversity mechanism for sender-oriented broadcast protocols in vanets[END_REF][START_REF] Arif | A survey on security attacks in vanets: Communication, applications and challenges[END_REF], and especially boost the road safety applications by extending the knowledge bases of vehicles with numerous up-to-date information about various road conditions. The main challenge in this field arises from the fact that the sent data should be disseminated in a wide Area-of-Interest (AoI), while the sending vehicles are equipped with the limited DSRC devices. In order to handle this challenge, one promising technique is to allow messages to be spread over multiple depots in an ad hoc manner through a Vehicle-to-Vehicle (V2V) communication. However, Considering some intrinsic Inter-Vehicular Communication (IVC) [START_REF] Kenney | Dedicated short-range communications (dsrc) standards in the united states[END_REF] characteristics, it is obvious that the multi-hop retransmission paradigm is not mature enough to provide reliable dissemination process in VANETs. Indeed, due to the shared data load, vehicular traffic density, the lack of a coordinator entity to manage the channel allocation and contention, and the limited radio medium dedicated for VANETs [START_REF] Lee | Vanet applications: Past, present, and future[END_REF], serious broadcast storm and packet collisions threat the availability and timeliness of the network. Reducing the communication burden by enabling only a subset of vehicles to relay the sent messages (referred 2 This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d to as relay nodes) has long been debated to be efficient solution for reducing data redundancy and wireless channel damage [START_REF] Wisitpongphan | Broadcast storm mitigation techniques in vehicular ad hoc networks[END_REF][START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF][START_REF] Tizvar | A density-aware probabilistic interest forwarding method for contentcentric vehicular networks[END_REF][START_REF] Villas | Drive: An efficient and robust data dissemination protocol for highway and urban vehicular ad hoc networks[END_REF][START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF]. Nevertheless, it still hard to design a robust relay selection technique that can handle the characteristics of VANETs in a fully distributed manner [2]. For instance, the high-speed of vehicles induces a fast-changing network topology and frequent disconnection of the wireless communication links, resulting in a poor network reachability. This will lead to a serious packet loss problem and becomes more severe when increasing the network complexity. For example, the physical obstacles in the complex urban scenarios can easily intersect the transmitted signal and block the end-to-end communications [START_REF] Ghorai | A robust forwarding node selection mechanism for efficient communication in urban vanets[END_REF].

Designing a robust relay selection algorithm is a unique problem for disseminating messages in VANETs, a poor selection of relays can easily lead to a poor reachability and message coverage capability, high latency, and even to the reproduction of the broadcast storm [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF]. In general, existing relevant works address the issues of data dissemination in VANETs in two different ways [START_REF] Dighriri | Big data environment for smart healthcare applications over 5g mobile network[END_REF]. Some exploit the one-hop neighbors information gathered by means of the beacon messages to explicitly select the relay nodes at the sender side, referred to as sender-oriented relay selection mechanism; and others aim to improve the network reachability and avoid the beacon exchanging cost by adopting an implicit selection of relays, referred to as receiver-oriented relay selection mechanism. Each mechanism has its unique benefits and shortcomings, thus its own problems that are driving the research aspects. For example, sender-oriented schemes can achieve a rapid propagation of messages, but they are very sensitive to the mobility of vehicles. On the other hand, receiver-oriented schemes exhibit high tolerance with the high speed of vehicles, but with an extra transmission delay. Besides, regardless of whether the relay selection is sender-oriented or receiver-oriented, it should be noted that the geometric distribution of relays almost determines the message coverage efficiency. The selected relays should be adequately distributed inside the targeted dissemination area to ensure an optimal coverage of the entire AoI. Nevertheless, we observed that this requirement have not been effectively addressed in most of the existing dissemination protocols, incurring the chaotic distribution of relays and resulting in a poor information coverage.

Instead of the flat network structure, creating a network hierarchy in VANETs can bring significant advantage for the data delivery by managing the message retransmissions process in a structured manner. Meanwhile, there are other challenges over a dynamic VANET topology, especially, the maintenance and creation of stable network structure with less overheads [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF].

In light of the above description, this paper is proposed with the aim to construct a Robust 3 This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d BACKbone NETwork based on Hybrid Selection of Relays for multi-hop data dissemination in VANET, namely as BACKNET-HSR. Robustness is achieved by simultaneously addressing the most intrinsic data dissemination challenges stemming from the unique characteristics of VANETs, such as the unexpected packets loss, frequent failures of the communication links, expanded latency and the distributed nature of VANETs. First, one new relays distribution model is envisaged to avoid the chaotic distribution and ensure the information coverage capability. Then, we comprehensively adjust the relays selection and inhibition rules to realize the envisioned relays distribution in a distributed manner. Moreover, we tend to ensure reachability and reduce the latency by realizing a tight coupling of both existing sender-oriented and receiver-oriented relay selection mechanisms in one hybrid scheme. In more detail, the main contributions presented by this paper are summarized as follows:

• This paper gives out a deep overview of sender-oriented and receiver-oriented relay selection mechanisms, as well as a qualitative comparison among them.

• This paper identifies the causes behind the chaotic distribution of relays in previous dissemination works. To solve this problem, we envisaged one new relay distribution model based on the road map topology. In order to achieve the envisioned relay distribution model in a distributed VANET structure, we design one new message propagation pattern as the guidance of the relays selection and inhibition rules. As soon as the dissemination process is triggered, a synergy between the potential relay candidates is realized to build an on-the-fly backbone structure parallel to the road lines.

• This paper aims to enhance the relay selection robustness by exploiting the best features of the aforementioned relay selection mechanisms. An explicit selection of relays is performed at the senders side to provide a continuous retransmission at the application layer while comprehensively taking into account the mobility of vehicles, the communication links conditions and the static physical obstacles in the urban scenarios. As important disconnection of the communication links could be occurred unexpectedly, we use a contention-based relay selection technique to monitor the propagation of the sent message and compensate for the lost packets by implicitly selecting alternative relays upon capturing one failed communication between the explicitly selected relays. Different timer settings are defined to ensure the ordered combination of both adopted relays selection mechanisms.

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d

• Experiment simulations are carried-out under varying vehicular traffic densities and different scenarios to assess our proposed scheme with some other existing protocols, revealing that our proposed scheme efficiently improves the message coverage capability and noticeably reduces the transmission delay.

The remainder of this paper is organized as follows: Section 2 discusses the existing work on data dissemination in VANETs. Section 3 gives a detailed description of the problems encountered in this field. Section 4 gives the main components of the proposed scheme. Section 5 presents the proposed scheme in detail. The simulation results are analyzed in section 6. Finally, the last section provides a brief overview of our future work and concludes this work.

Related work

Multi-hop data dissemination is among the main research topics of VANETs in previous literatures [2]. Flooding has long been exhibited as the simplest way of disseminating data over the mobile ad hoc networks, each vehicle roaming inside the AoI broadcasts every incoming message once. Although the blind flooding has high performance efficiency under the sparse network scenarios, it disrupts the network availability by generating the broadcast storm problem when increasing the network density. Hence, it easily lead to a serious network congestion and packet collisions [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF][START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF]. In order to mitigate these problems, previous relevant works tend to adopt such a broadcast suppression technique [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF] to avoid the unnecessary retransmissions. Only a subset of potential vehicles will be allowed to relay the disseminated data, while the others will be inhibited.

At this point, it should be noted that a poor selection of the relay nodes will undoubtedly undermine the dissemination efficiency in many regards, such as latency, overheads, and particularly the message coverage capability [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF]. As described earlier, based on either the relay selection process is performed by the sender or the receiver nodes, existing broadcast suppression techniques can be classified into two main classes: sender-oriented and receiver-oriented relay selection mechanisms.

Next, we will detail these two major techniques, and then we give a qualitative comparison study between them listed in Table 1.

Sender-oriented relay selection mechanism

This class can be referred to as beacon-assisted relay selection mechanism. It exploits the onehop neighbors information gathered by means of the exchanged beacon messages to explicitly select 5

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d Each node that hear retransmission of an already scheduled message must immediately cancel its transmission.

Advantages Enables a continuous retransmission paradigm at the application layer, which can promote the development of the delay-sensitive applications.

Provides a good scalability when designing the relay selection rules [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF].

Exhibits good tolerance with the frequent disconnection of the communications links between mobile vehicles.

No prior information are required to perform the dissemination process (beaconless solution).

Drawbacks

Exhibits high sensitivity to the frequent disconnection of the communication links in VANETs.

Requires up-to-date information about the onehop network condition (beacon-assisted solution).

Adopts an intermittent retransmission

paradigm that noticeably increase the latency.

Not recommended for the delay-sensitive applications.

Frequent addressed issues

Handling the broadcast storm problem.

Maintaining stable communication links by considering several conditions, such as link connectivity [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF], link life time [START_REF] Ullah | Eemds: An effective emergency message dissemination scheme for urban vanets[END_REF], successful transmission probability [START_REF] Zhang | A street-centric opportunistic routing protocol based on link correlation for urban vanets[END_REF], and the use of an obstacle avoidance forwarding strategy [START_REF] Ghorai | A robust forwarding node selection mechanism for efficient communication in urban vanets[END_REF].

Enhancing the information coverage capability by adopting several techniques, such as the construction of an hierarchical network topology [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF][START_REF] Wang | V2v-covad: A vehicle-to-vehicle cooperative video alert dissemination mechanism for internet of vehicles in a highway environment[END_REF],

and the assignment of the highest rebroadcast priority to the relay candidates that have dense local networks [START_REF] Oliveira | Reliable data dissemination protocol for vanet traffic safety applications[END_REF].

Handling the unexpected link disconnection problem by selecting auxiliary relay(s) [START_REF] Wu | A low latency path diversity mechanism for sender-oriented broadcast protocols in vanets[END_REF][START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF][START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF].

Handling the broadcast storm problem.

Handling the expanded latency through the use of a probabilistic-based solution [START_REF] Zeng | A new probabilistic multi-hop broadcast protocol for vehicular networks[END_REF][START_REF] Reina | A survey on probabilistic broadcast schemes for wireless ad hoc networks[END_REF][START_REF] Tizvar | A density-aware probabilistic interest forwarding method for contentcentric vehicular networks[END_REF][START_REF] Srivastava | Fuzzy-based beaconless probabilistic broadcasting for information dissemination in urban vanet[END_REF], or the reduction of the contention timer [START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF][START_REF] Turcanu | A multi-hop broadcast wave approach for floating car data collection in vehicular networks[END_REF][START_REF] Bujari | Fast multi-hop broadcast of alert messages in vanets: An analytical model[END_REF][START_REF] Chuang | Deep: Density-aware emergency message extension protocol for vanets[END_REF].

Avoiding packet collisions by preventing the simultaneous retransmissions problem for both probabilistic-based solutions [START_REF] Tonguz | Dv-cast: A distributed vehicular broadcast protocol for vehicular ad hoc networks[END_REF][START_REF] Tizvar | A density-aware probabilistic interest forwarding method for contentcentric vehicular networks[END_REF][START_REF] Srivastava | Fuzzy-based beaconless probabilistic broadcasting for information dissemination in urban vanet[END_REF], and timer-based solutions [START_REF] Yoo | Roff: Robust and fast forwarding in vehicular ad-hoc networks[END_REF][START_REF] Amador | Evaluation and improvement of etsi its contention-based forwarding (cbf) of warning messages in highway scenarios[END_REF][START_REF] Bellache | Dcc-enabled contention based forwarding scheme for vanets[END_REF].

Enhancing the information coverage capability by designing a relays distribution model for the timer-based solutions, as in [START_REF] Villas | Drive: An efficient and robust data dissemination protocol for highway and urban vehicular ad hoc networks[END_REF], or assigning priority to the relay candidates with high local densities for the probabilistic solutions, as in [START_REF] Tizvar | A density-aware probabilistic interest forwarding method for contentcentric vehicular networks[END_REF].

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d the next-hop relays at the sender side. The current relay node should elect among its vicinity one or more neighbors to become the next dissemination entities, incorporates their identifiers inside the message and broadcast it. When receiving the sent message, each receiver first needs to judge whether or not it has been explicitly selected to become a relay node by checking the content message relay list. If yes, it will forward the message; else, it will be inhibited. As this type of mechanism provides the possibility of a continuous retransmissions at the application layer, sender-oriented solutions achieve promising performance in network latency, which can promote the development of the delay-sensitive applications [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF]. However, they exhibit high sensitivity to the frequent disconnection of the communication links in VANETs. In fact, considering the high mobility of vehicles, the presence of physical obstacles, the channel fading operation, the hidden nodes problem, etc. there is no guarantee that the explicitly selected relays (i.e., the only ones enabled to broadcast) will correctly receive the sent message. Hence, a serious packet loss is possible in this case.

In general, most of the existing dissemination solutions in VANETs exploit the furthest distance approach to reduce both data redundancy and end-to-end delay. The neighbor farther away from the sender is recognized as the ideal next-hop relay. Besides, sender-oriented solutions emphasized on the availability of the explicitly selected relays to avoid packets loss. To this end, several techniques have been proposed to enhance reachability between the neighboring relays [START_REF] Ghorai | A robust forwarding node selection mechanism for efficient communication in urban vanets[END_REF][START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF][START_REF] Zhang | A street-centric opportunistic routing protocol based on link correlation for urban vanets[END_REF][START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF][START_REF] Ullah | Eemds: An effective emergency message dissemination scheme for urban vanets[END_REF].

A link stability measurement based on the regularity of the incoming beacons has been proposed in [START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF]. It assigns priority to the neighbors with stable forwarding links to become the next-hop relays. The combination of multiple link quality parameters to mitigate the unexpected link failure problem has been widely studied in this regard [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF][START_REF] Ullah | Eemds: An effective emergency message dissemination scheme for urban vanets[END_REF]. The link state can be determined based on several conditions, such as link connectivity [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF], link life time [START_REF] Ullah | Eemds: An effective emergency message dissemination scheme for urban vanets[END_REF] and successful transmission probability [START_REF] Zhang | A street-centric opportunistic routing protocol based on link correlation for urban vanets[END_REF]. By increasing the dissemination constraints, other solutions tend to achieve robust relay selection process under complex VANET scenarios. Some are proposed with the aim to prevent intersecting the physical obstacles when establishing communications between neighboring relays, reducing the channel fading effect by enabling an obstacle avoidance forwarding strategy [START_REF] Ghorai | A robust forwarding node selection mechanism for efficient communication in urban vanets[END_REF]; and others consider the security constraints when selecting the relay nodes [START_REF] Poursajadi | Adaptive optimal relay selection in cooperative vehicular communications under security constraints[END_REF].

The improvement of information coverage is also within interests of existing literature. The goal is to enhance the message coverage capability by maximizing the number of vehicles receiving the message. To this end, the work in [START_REF] Oliveira | Reliable data dissemination protocol for vanet traffic safety applications[END_REF] takes into account the local density of each vehicle 7

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d during the relays selection process, the neighbor with high local density and falls farther away from the sender is more likely to become the next-hop relay. Other works achieve better coverage performance by allowing a multiple selection of the next-hop relays [START_REF] Wu | A low latency path diversity mechanism for sender-oriented broadcast protocols in vanets[END_REF][START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF][START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF]. A path diversity broadcast solution is proposed in [START_REF] Wu | A low latency path diversity mechanism for sender-oriented broadcast protocols in vanets[END_REF]. Instead of selecting only one relay, an auxiliary relay is selected to reinforce the message delivery capability. In order to reduce redundancy, the auxiliary relay will only broadcast the sent message without performing the relay selection process. A Bidirectional Stable Communication (BDSC) scheme [START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF] is proposed to improve both reachability and coverage. The main idea behind BDSC is to let every vehicle select 12 potential neighbors as relay candidates, ordered in a relay priority list based on the Link Quality (LQ) influence factor.

simultaneous retransmission is effectively addressed by using a contention-based retransmission paradigm. Data redundancy is also addressed by forcing the explicitly selected relays to cancel their scheduled transmissions upon hearing a twice copies of the same message. Two variants of the BDSC scheme have been proposed in [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF]. The main idea behind these variants is to combine multiple selection metrics when constructing the relay priority list, such as the furthest distance approach and the bi-directional link stability influence factor. Thus, achieving better performance than the original BDSC scheme under different traffic load conditions, particularly in terms of the end-to-end delay and the generated overheads. Hierarchical networks are also exhibited as promised techniques for improving the message coverage capability by overcoming the limitations of the flat network structure in VANETs. Within the context of data dissemination, we recognize the clustering approaches as representative solutions for attempting such a network hierarchy, like in [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF][START_REF] Wang | V2v-covad: A vehicle-to-vehicle cooperative video alert dissemination mechanism for internet of vehicles in a highway environment[END_REF]. Vehicles are organized into multiple connected clusters, and each cluster is managed by a controller entity named cluster-head. During the dissemination process, messages will be routed toward the cluster-heads, then forwarded towards the cluster-members in an hierarchical manner.

The main drawback of these solutions is that the formed hierarchy should be stable to ensure the structured propagation of the sent messages, which is hard to be realized in a time-varying VANET topology. Thus, any topology change should be reported to all relevant nodes, incurring an important communication overhead.

Receiver-oriented relay selection mechanism

While sender-oriented solutions faced the most intrinsic VANET challenge (i.e., the severe packet loss stemming from the frequent disconnection of the communication links), other research studies 8

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d

were proposed with the aim to fully overcome this issue by using a receiver-oriented relay selection mechanism. The main idea behind the latter mechanism is to make each receiver vehicle able to make its own broadcast decision in a distributed manner without the need of any prior knowledge about the surrounding network conditions, e.g., the neighbor location, the already established link connections, etc. For this reason, receiver-oriented solutions are known as beaconless approaches,

where their main advantage is usually referred to dispensing the beacon exchanging load [START_REF] Amador | Evaluation and improvement of etsi its contention-based forwarding (cbf) of warning messages in highway scenarios[END_REF][START_REF] Turcanu | A multi-hop broadcast wave approach for floating car data collection in vehicular networks[END_REF].

Although this benefit is true in the dissemination context, it should be noted that beacon messages have been standardized by the European Telecommunications Standards Institute (ETSI) as a cornerstone of the cooperative awareness service [START_REF] Etsi | Intelligent transport systems (its); vehicular communications; basic set of applications; part 2: Specification of cooperative awareness basic service[END_REF], particularly for the safety-related services. In reality, The main purpose of the receiver-oriented mechanism is to fit the fast-changing VANET topology by avoiding the link conditions dependency when designing the relays selection rules.

Upon receiving the sent message, the vehicle decides whether or not it becomes a relay node based on some predefined rules which can be probabilistic-based or timer-based. Probabilistic solutions [START_REF] Zeng | A new probabilistic multi-hop broadcast protocol for vehicular networks[END_REF][START_REF] Reina | A survey on probabilistic broadcast schemes for wireless ad hoc networks[END_REF][START_REF] Tizvar | A density-aware probabilistic interest forwarding method for contentcentric vehicular networks[END_REF] allow vehicles to forward the received message with a calculated probability that is usually associated with the distance and redundancy parameters. Like the sender-oriented solutions, probabilistic techniques can provide a continuous retransmission at the application layer, resulting in low dissemination latency. However, they lead to severe packet collisions and channel damage due to the simultaneous rebroadcasts from nearby nodes (multiple neighbors can have high broadcast probability of the same message, especially in dense VANET scenarios). Timer-based approaches [START_REF] Villas | Drive: An efficient and robust data dissemination protocol for highway and urban vehicular ad hoc networks[END_REF][START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF][START_REF] Turcanu | A multi-hop broadcast wave approach for floating car data collection in vehicular networks[END_REF][START_REF] Amador | Evaluation and improvement of etsi its contention-based forwarding (cbf) of warning messages in highway scenarios[END_REF] have been exhibited as promising alternative of the probabilistic approaches, since they effectively address the issue of the simultaneous rebroadcasts through the use of contention.

For every incoming message, the vehicle holds it and schedules a transmission timer that is usually computed based on the distance between the couple sender-receiver vehicles. If the initiated timer expires, the vehicle becomes a relay node and broadcasts the message. Data redundancy has been effectively mitigated by forcing vehicles to immediately canceling their scheduled transmissions upon hearing new transmission of the same scheduled message (inhibition rule). Among the main drawbacks of timer-based solutions, we can cite the use of a back-off timer at the application layer, which leads to an intermittent retransmission paradigm and noticeably expands the dissemination delay, particularly as we exploit the multi-hop retransmission technique over a large scale VANET network.

The work in [START_REF] Tonguz | Dv-cast: A distributed vehicular broadcast protocol for vehicular ad hoc networks[END_REF] addresses the simultaneous retransmissions problem of p-Persistence [START_REF] Wisitpongphan | Broadcast storm mitigation techniques in vehicular ad hoc networks[END_REF] scheme 9

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d through combining the furthest distance algorithm with the mobility of vehicles. It assigns the highest rebroadcast priority to the receivers far away from the sender and have similar movement direction, which could reduce the number of contending vehicles. The applicability of a probabilistic technique to different vehicle densities has been also studied in [START_REF] Tizvar | A density-aware probabilistic interest forwarding method for contentcentric vehicular networks[END_REF], revealing that adjusting the forwarding probability with the local density of vehicles could enhance the coverage capability with less communication burden. An approach to improve the reliability of the probabilistic forwarding consists of using fuzzy logic to calculate the broadcast probability of vehicles by taking into account the buffer load, angular orientation, and the movement direction of each vehicle [START_REF] Srivastava | Fuzzy-based beaconless probabilistic broadcasting for information dissemination in urban vanet[END_REF].

Timer-based solutions have gained important attention in the recent years. DRIVE [START_REF] Villas | Drive: An efficient and robust data dissemination protocol for highway and urban vehicular ad hoc networks[END_REF] introduces a sweet spot concept to maximize the message coverage capability under varying traffic conditions. The communication radius of the sender vehicles is divided into four quadrants, a sweet spot is defined in each quadrant as the most suited zone in which the next hop relay should be located. DRIVE aims to maximize the coverage capability by allowing the farthest vehicle inside each sweet spot to relay the disseminated data. However, the authors in DRIVE do not adjust their proposed inhibition rule to fit the sweet spot concept, instead they adopt the indiscriminate inhibition (discussed in Section 3), which disrupts the envisioned relays distribution model and easily lead to the chaotic distribution of relays. Additionally, an extra delay is induced by the adopted timer settings since there is no guarantee to find vehicles located within the sweet spots (i.e., the ones with the shortest transmission-timers).

A Contention-Based Forwarding (CBF) algorithm [START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF] is proposed by the ETSI as the current standard of data dissemination in VANETs. CBF can be seen as an improved version of DRIVE.

Instead of the sweet spot concept, CBF enables vehicles receiving one copy of the sent message to become relay nodes, realizing an on-the-fly relays distribution model dynamically adjusted to fit the senders' neighbors distribution. This perception enables CBF to adopt an uniform timer setting, the furthest receiver from the sender is assigned with the shortest transmission timer independently of the zone where it is falling inside. Although CBF achieves much better performance in network latency compared to DRIVE, it still suffers from the intermittent retransmission problem since there is no guarantee to find neighbors distant enough from the senders to ensure the rapid propagation of messages, especially under the sparse network scenario. In contrast, in dense scenario, CBF generates frequent simultaneous retransmissions since, in this particular scenario, there is a high probability to find equidistant neighbor from the sender, i.e., neighbors with equal transmission 10

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d timers. Moreover, like DRIVE, CBF adopts the indiscriminate inhibition rule, leading to the fail of the considered relays distribution model under multiples vehicular scenarios.

A pull-based data dissemination approach has been proposed in [START_REF] Turcanu | A multi-hop broadcast wave approach for floating car data collection in vehicular networks[END_REF] to aggregate real-time Floating Car Data (FCD). To disseminate the request messages, the authors in [START_REF] Turcanu | A multi-hop broadcast wave approach for floating car data collection in vehicular networks[END_REF] propose a reduced CBF (rCBF) to overcome the simultaneous retransmissions induced by the original CBF.

The main idea behind rCBF is to extend CBF's timer setting with an uniformly-distributed random component, hence avoiding the simultaneous retransmissions in case of equidistant neighbors from the sender, but with an extra delay. Several timer-based approaches have been proposed in the literature, they are mainly focusing on the high delay issue steaming from the contention process [START_REF] Bujari | Fast multi-hop broadcast of alert messages in vanets: An analytical model[END_REF][START_REF] Chuang | Deep: Density-aware emergency message extension protocol for vanets[END_REF], the collision problem that frequently occurred in case of defining short timer difference among neighboring receivers [START_REF] Yoo | Roff: Robust and fast forwarding in vehicular ad-hoc networks[END_REF], and the applicability of the timer-based approaches with the Decentralized Congestion Control (DCC) buffer [START_REF] Amador | Evaluation and improvement of etsi its contention-based forwarding (cbf) of warning messages in highway scenarios[END_REF][START_REF] Bellache | Dcc-enabled contention based forwarding scheme for vanets[END_REF]. In this regard, it should be noted that the information coverage has not so far been effectively addressed in previous literature.

Problem description

Actually, the relay nodes concept has been introduced to mitigate the broadcast storm problem by enabling only a subset of potential nodes to broadcast the sent messages and inhibiting the others, which could significantly reduce the channel competition and packet redundancy problems.

Although reducing the number of relays could efficiently reduce the communication burden, it brings additional challenges in terms of the network coverage, reachability and timeliness. These issues are hereafter discussed as follows:

1) Message coverage capability: To the best of our knowledge, regardless of whether the adopted relay selection mechanism is sender-oriented or receiver-oriented, existing dissemination schemes do not consider the requirements of the geometric distribution of relays when designing the relay selection and inhibition rules. This becomes more obvious when taking into account that the most common inhibition rule is designed based on the information redundancy ratio, which could easily lead to the the chaotic distribution of relays because of the indiscriminate inhibition of the relay candidates, hence the poor information coverage. For the sake of simplicity, a representative illustrations of the latter problem is shown in are the furthest from each other, hence they will be respectively the third, fourth, fifth and sixth re-broadcaster nodes. As seen in this example, vehicles V2, V5, V8 and V11 are a very critical relay candidates since they are the only ones that could forward the sent message towards the bottom network side. However, since each one of them will receive at least twice copies of the sent message, they will be indiscriminately inhibited. Therefore, the vehicles V12-V19 will not receive the sent message even-though they are considered as belonging to the targeted AoI, which leads to the poor coverage capability. In reality, the indiscriminate inhibition problem has been overlooked in most of the existing dissemination approaches. The indiscriminate inhibition issue has been addressed in the area advanced forwarding algorithm [START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF], proposed by the ETSI, by increasing the redundancy tolerance ratio, vehicles receiving redundant copies of the sent message and their number still less than a given inhibition threshold will be allowed to broadcast. However, the limited DSRC channel will be overwhelmed by the unnecessary retransmissions of redundant messages. Additionally, As shown in Fig. 1, it is a challenging task to define the optimal inhibition threshold under a timevarying vehicular distribution and density.

2) Network reachability and timeliness: Because of some inherent IVC characteristics, reachability is a unique problem in VANETs, particularly for the sender-oriented schemes and even-though the link performance is taken into account when selecting the relay nodes. Receiver-oriented mechanism could effectively avoid this problem, however, with an extra delay. Thus, a tight coupling of 12

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d both mechanisms in one scheme could be a promising solution to take advantage of their benefits while avoiding their shortcomings. First, a sender-oriented mechanism can be adopted as the primary relay selection mode, hence the disseminated data could be spread rapidly. As packets can be lost unexpectedly, a modified version of the receiver-oriented mechanism can be implemented as a recovery strategy to capture the lost packets and implicitly select alternative relays. However, this investigated coupling requires efficient inhibition rule and timer settings to ensure an ordered combination of both mechanisms, as well as a robust monitoring algorithm to efficiently capture the failed link connections, which is hard to achieved in a flat VANETs structure.

Basically, considering VANET as a flat network structure without a coordinator manager makes the design of such an envisioned relay distribution model a challenging task. To handle this problem, some previous works aimed to build a network hierarchy to organize the data transmission in a structured manner [START_REF] Liu | A data dissemination scheme based on clustering and probabilistic broadcasting in vanets[END_REF][START_REF] Wang | V2v-covad: A vehicle-to-vehicle cooperative video alert dissemination mechanism for internet of vehicles in a highway environment[END_REF]. Structure-based data dissemination solution brings an important improvement of the coverage capability. However, it often exhibits additional challenges for forming stable network hierarchy and reducing the structure creation and maintenance overheads. In this paper, we tend to take advantage of the fact that vehicles are basically distributed according to the road map topology, hence a partisan vehicular distribution along with the road lines is automatically formed. First, we envisaged one relay distribution model parallel to the road lines, as seen as the best fit between the city settings and the characteristics of VANETs. Then, we design one new message propagation pattern to realize a synergy between the relay nodes to build an on-the-fly network backbone along with the roads, hence improving the coverage capability while dispensing the stability requirement and the structure creation and maintenance cost. Moreover, we exploit the proposed message propagation pattern to ensure robust relay selection and inhibition rules.

Each vehicle could be able to make its own decision on relaying the data in a distributed manner, which opens up the possibility to the envisioned tight coupling of both investigated relay selection mechanisms.

System overview

In this section, we will give out an overview of the proposed data dissemination scheme by presenting the following aspects.

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Assumptions

(1) All vehicles are equipped with a DSRC device, static digital map and a positioning system, e.g., GPS receiver. Thus, each vehicle can be aware about its position, velocity and the roads topology.

(2) Each vehicle is aware about the surrounding one-hop neighbor conditions, such as neighbor identifier, position, velocity, etc. According to the ETSI [START_REF] Etsi | Intelligent transport systems (its); vehicular communications; basic set of applications; part 2: Specification of cooperative awareness basic service[END_REF], the latter information can be gathered by means of the Cooperative Awareness Message (CAM) exchanging process and maintained in vehicles' Local Dynamic Map (LDM) [START_REF]ETSI, Intelligent transport systems (its); vehicular communications; basic set of applications[END_REF].

(3) Vehicles' transmission range is larger than the width of the roads.

Notice that assumptions 1 and 2 have been referred by the ETSI [START_REF] Etsi | Intelligent transport systems (its); vehicular communications; basic set of applications; part 2: Specification of cooperative awareness basic service[END_REF][START_REF]ETSI, Intelligent transport systems (its); vehicular communications; basic set of applications[END_REF], as well as assumption 3 is reasonable and has been referred by several other works, e.g., in [START_REF] Ukkusuri | Geometric connectivity of vehicular ad hoc networks: Analytical characterization[END_REF][START_REF] Wu | Analytical models for information propagation in vehicle-tovehicle networks[END_REF].

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Node state

In the following, we refer to the vehicle that falls closest to a given junction compared to all its neighbors as a Junction Vehicle (JV). A JV incorporates its state and the associated junction identifier inside its CAM messages, notifying its one-hop neighbors about its present state. When receiving a CAM from a JV, each receiver roaming inside one of the roads overlapped in the associated junction considers the sender JV belongs to the same road as it. The goal is to make each JV simultaneously belong to all overlapped roads. The pseudo-code given in Algorithm 1 details the JV selection process.

Relays distribution model

As described earlier, the key to ensure an efficient message coverage capability is to find how to distribute the relay nodes intelligently inside the AoI. Considering assumption 3, i.e., vehicle's transmission range is larger than the width of road, each road can be considered as a one-dimensional plane [START_REF] Ukkusuri | Geometric connectivity of vehicular ad hoc networks: Analytical characterization[END_REF]. Thus, it is sufficient that a set of potential vehicles distributed parallel to the road line broadcast the message to ensure the coverage of the entire road area, suggesting that the most adaptive relay distribution is parallel to the road line. Besides to the coverage enhancement, the main benefits behind the latter suggestion are two-folds. The former corresponds to the simplicity of realizing this envisioned relay distribution in a distributed manner by enabling a synergy between vehicles to form an on-the-fly backbone network along with the road line. Hence, dispensing the extra overheads incurred by the network structure forming and maintaining phases. The latter corresponds to reducing the signal blocking from the physical obstacles in the road sides e.g., the buildings, advertising boards, vegetation, traffic lights and so on, since the sent messages will be forwarded parallel to the road line. Hence, reducing the channel fading operation and enhancing the relay selection robustness by providing an obstacle avoidance forwarding strategy.

Message propagation pattern

In this paper, in order to avoid the chaotic distribution of relays and improve the message 1) The receiver is not a Junction Vehicle (JV): In this case, the receiver follows the in-road propagation of messages, which is designed to disseminate messages under one road segment, i.e., between vehicles roaming inside the same road. As each road can be handled as a one-dimensional plane, hence the propagation of messages could be at most in two different road line directions.

To do this, our proposed in-road propagation pattern enables messages to be forwarded from the rear side of the current hop relay towards its front side by means of a front neighbor, and from the front side of that relay towards its rear side by means of a rear neighbor. To illustrate the envisioned message propagation pattern, an example is shown in Fig. 2, where we assume that vehicle V1 is the current hop relay and has received the message from a rear neighbor roaming inside the same road as it. Based on the above discussion, V1 should forward the received message towards its front side by means of a potential front neighbor (vehicle V2 in this example). Notice that, considering assumption 3, the broadcast performed by V1 will cover the entire road area AV1, where the dimensions of AV1 are proportional to the sender's transmission range for length and the road width for width. Receiving the message, V2 will find that the previous relay V1 falls in its front side, hence it will forward the message towards its rear side by means of V3. The same process is repeated until reaching the last vehicle in that road, basically a JV. In this way, we ensure the coverage of the entire road progressively area by area with few number of relays and less signal

blocking.

An Elector vehicle E judges whether a Neighbor N falls in its front or rear side based on the angle formed between its velocity vector, denoted as -→ V E , and the line vector --→ EN that connects vehicles E and N (represented by Θ in Fig. 3). N is considered as a front neighbor if Θ E,N ∈ [0, 90],

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and rear neighbor if Θ E,N ∈ ]90, 180]. As vehicles move in two-dimensional plane (X-Y plane), we can write -→ V E and --→ EN in their corresponding components as given bellow,

-→ V E = V Ex i + V Ey j (1)
--→ EN = (x N -x E ) i + (y N -y E ) j = EN x i + EN y j (2)
Where (x N , y N ) and (x E , y E ) are the geographical coordinates of vehicles N and E respectively.

Mathematically Θ E,N can be calculated by Equation 3as given below,

Θ E,N = cos -1 V Ex EN x + V Ey EN y V 2 Ex + V 2 Ey EN 2 x + EN 2 y (3)
2) The receiver is a Junction Vehicle (JV): Actually, the in-road propagation of messages enables a synergy between the relay nodes to build an on-the-fly backbone network parallel to one road line.

In order to merge the overlapped in-road backbones and make messages able to spread over the entire AoI, an inter-roads propagation of messages should be performed by splitting the message into multiple copies and comprehensively switching them towards the uncovered roads. In this work, we refer to the JVs as the most potential vehicles to perform the latter task for two main reasons: their ability to be simultaneously belong to all overlapped in-road backbones, and particularly their potentiality to perform the inter-roads propagation of messages without intersecting the physical obstacles in the road sides. This is because the JVs are the most likely to be within the intersection zones, i.e., the zones with less radio obstacles.

Forwarding algorithm

In contrast to most of the existing dissemination schemes that were designed to operate exclusively based on either a sender-oriented or receiver-oriented relay selection mechanism, we rather aim to take advantages of both investigated mechanisms by combining them in one hybrid scheme.

When one vehicle receives the message, it first needs to judge whether or not the message propagation pattern has been fulfilled under its coverage area by comparing the different angles of arrival of the sent message. If yes, meaning that the message has been successfully propagated under its vicinity and the vehicle is a noncritical relay candidate, it will discard the received message. Otherwise, it determines its relevance for relaying the message by computing a back-off timer associated with the following priority assignment metrics. explicitly selected relays, hence enabling a continuous retransmissions at the application layer to ensure a short latency. To do this, each vehicle behaving as a relay node should incorporate its own associated relay list inside the message before broadcasting it. On the other hand, in order to avoid the explicit relay selection shortcomings, especially the poor reachability incurred by the unexpected link failure problem, we adopt one new recovery strategy inherited from the receiveroriented mechanism. Each receiver that has not been explicitly selected to relay the message and falls in its propagation direction should monitor the propagation of the sent message. If a recovery timer is expired and the message propagation pattern was not fulfilled under the receiver's vicinity, which means that a link failure has been occurred, the receiver will compensate for this issue by relaying immediately the message. In other words, the proposed forwarding algorithm provides a tight coupling between both existing relay selection mechanisms by enabling vehicles to collaboratively handle the multi-hops retransmissions of messages in an efficient manner. Hence, besides to the coverage enhancement, messages could be forwarded rapidly with few overheads and high reachability rate.

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Proposed BACKNET-HSR data dissemination scheme

In light of the above description, this section details the proposed BACKNET-HSR scheme.

The flowchart depicted in Fig. 5 presents the whole dissemination process of our scheme, which includes the following parts.

Inhibition rule

As mentioned earlier, consider a flat network structure, the lack of an efficient message propagation pattern leads to an indiscriminate inhibition of the relay candidates, resulting in a poor message coverage capability. To deal with this problem, each vehicle should make its own decision on relaying the data in a distributed manner based on its potentiality for realizing the envisioned message propagation pattern under its coverage area. To do this, each vehicle monitors the propagation of the sent message under its coverage area and infers whether or not the envisioned propagation pattern has been fulfilled in that area. By assuming that a given vehicle heard the transmissions of the same message from two neighbors falling in the two different road line sides (i.e., front and rear neighbors), hence it can be deduced that the vehicle should not be considered as a potential relay candidate, since the expected in-road backbone has been already built inside its monitoring area.

Otherwise, if the vehicle has received the message from neighbor(s) falling in one road line side, meaning that a disconnection of the envisioned in-road backbone has been occurred, the vehicle becomes a critical relay candidate due to its high potential for fixing the disconnection issue by relaying the message towards the uncovered road side. As a result, as shown in Fig. 5 (left dotted rectangle), the only case in which a vehicle becomes inhibited to relay the message is the fulfillment of the message propagation pattern under the vehicle's vicinity, which is achieved when hearing the transmission of the same message from at least two neighbors falling in two different road line sides.

Explicit selection of relays

In order to handle the delay sensitive VANET-based applications, the sender-oriented relay selection mechanism has been exhibited as a promising solution to spread data rapidly over multiple depots. By adopting the explicit selection of relays, a continuous retransmission at the application layer can be realized. The sender nodes should incorporate the identifiers of the next dissemination entities inside the disseminated data, which will be able to rebroadcast immediately. Because of the unique characteristics of VANETs, ensuring a good network reachability represents the [START_REF] Wang | V2v-covad: A vehicle-to-vehicle cooperative video alert dissemination mechanism for internet of vehicles in a highway environment[END_REF] This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d major challenge of the explicit selection of relays. Thus, taking into account the robustness of the forwarding links during the process of relays selection is quite important for enhancing the data delivery capability. Next, we will introduce our proposed relay selection metrics for improving reachability, then we will detail the explicit relays selection algorithm.

Relay selection metrics

As discussed in [START_REF] Ren | A mobility-based scheme for dynamic clustering in vehicular ad-hoc networks (vanets)[END_REF], the mobility metrics show better performance results in the context of a good network reachability in VANETs. For this reason, we aim to provide sufficient connection duration between neighboring relays by considering the mobility of vehicles. Thus, improving the stability of the wireless link connections and mitigating the rapid link failure problem. On the other hand, as roads are not always straight, we aim to fit the strip-shaped roads by taken into account the curvature of the road lines when selecting the next hop relays. The goal is to realize our envisioned obstacle avoidance forwarding strategy in different road line geometries without exploiting the received radio strength (RSS) metric that were considered as unsuitable in VANETs due to its poor precision [START_REF] Ren | A mobility-based scheme for dynamic clustering in vehicular ad-hoc networks (vanets)[END_REF][START_REF] Etsi | Intelligent transport systems (its); security; pre-standardization study on misbehaviour detection[END_REF]. Additional solutions for improving reachability could be included in our relay selection metrics, but remind that we focus on the recovery strategy to achieve this goal, as described in Section 5.3. The proposed relay selection metrics are described as follow:

1) Distance factor: In order to achieve the desired coverage with few number of relays, we exploit the greedy forwarding algorithm to assign priority to the neighbors further away from the elector for becoming relay nodes. However, considering the high mobility constraints, the greedy mode easily lead to an unexpected link failure problem [START_REF] Kaur | The importance of selecting clustering parameters in vanets: A survey[END_REF][START_REF] Alfarraj | Neighbor predictive adaptive handoff algorithm for improving mobility management in vanets[END_REF] since the farthest away (i.e., the ones that fall closer to the communication radius of the elector vehicle) are the most likely to be moved outside the elector's communication radius, resulting in a poor reachability between neighboring relays. To cope with this problem, we tend to adjust the greedy algorithm with the mobility of vehicles for ensuring stable communication links. To achieve this goal, we assign priority to the neighbor falling furthest in distance and remaining within the transmission range of the elector vehicle for a given period of time, measured as the time interval between two successive beacon messages (referred to as ∆t). Thus, the distance factor d E,N between an elector E and its neighbor N can be computed as: [START_REF] Oliveira | Reliable data dissemination protocol for vanet traffic safety applications[END_REF] This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d

d E,N = 1 - (x E -x N ) 2 + (y E -y N ) 2 -d opt d opt , (4)
where (x N , y N ) and (x E , y E ) denote the geographical coordinates of vehicles N and E respectively, and d opt stands for the optimal distance between two neighboring relays which can be evaluated as:

d opt = d max - d max 2v max ∆t ,
where d max denotes the maximum transmission range of the adopted DSRC device, and v max represents the allowed maximum speed of vehicles.

2) link straightness factor: The goal behind this evaluation factor is to comprehensively adjust the relays distribution according to the road line curvature, thus maximizing the dissemination coverage capability over one road-segment, as well as ensuring our envisioned obstacle avoidance forwarding strategy even in case of strip-shaped roads. To do this, we first exploit the mobility direction of the elector vehicle as an indicator of the road curvature. To be noted that the movement trajectory of vehicles is basically parallel to the road line. Then, we tend to assign priority to the neighbor where the angle between its location and the elector's velocity vector, i.e., the angle Θ described in Equation 3, approaches to 0 (zero -angle) or 360 (complete -angle) for becoming an associated Frontal Relay Node (FRN). On the other side, the neighbor that forms a straight angle (i.e., approach to 180) is more likely to play the role of associated Rear Relay Node (RRN). For the purpose of the link straightness factor evaluation, the elector assigns priorities to the neighbors with the optimal angle Θ E,N . How to compute Θ E,N depends on the state of the associated relay candidate, i.e., FRN or RRN candidate, as given below,

Θ E,N =      1 - Θ E,N 90 , Θ E,N ∈ [0, 90] Θ E,N 180 , Θ E,N ∈ ]90, 180] (5)
Where Θ E,N stands for the angle Θ described in Equation 3.

Relay selection algorithm

Actually, Designing an efficient message propagation pattern opens up the possibility of a proactive selection of relays, hence dispensing the computation overload during the dissemination process.

In fact, based on the investigated propagation pattern, the network backbone can be constructed

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d in a proactive manner by enabling each vehicle to proactively build its own Associated Relays List (ARL) based on the information gathered from the received CAM messages. Then, upon behaving as a relay node, the vehicle incorporates its own ARL inside the message and broadcasts it. How to elect the associated relays depends on the vehicle's status, based on which the following two cases are distinguished.

1) The vehicle is not a JV -Algorithm 2: In this case, the vehicle could follow the in-road propagation pattern. It elects, among the neighbors roaming inside the same road as it, the most potential one falling in its front side as an associated Frontal Relay Node (FRN), and the most potential one falling in its rear side as an associated Rear Relay Node (RRN).

2) The vehicle is a JV -Algorithm 3: In this case, the JV is intended to perform the inter-road propagation of messages. For each set of neighbors roaming inside such an overlapped road, it elects the most potential one as an associated relay, i.e., one potential neighbor for each overlapped road.

An elector vehicle E determines the capacity of each associated relay candidate N based on the above relay selection metrics, as given bellow:

ωf E,N =      αd E,N + (1 -α)Θ E,N , if E is a JV d E,N , Otherwise , (6)
where α represents a weight parameter such that α ∈ [0, 1]. In this work, we tend to dominate the distance influence factor by setting α to 0.8, as the most adaptive value in our simulation study.

At this point, it can be noticed that the ARL is composed of at least two associated relays, e.g., FRN and RRN. Hence, it is obvious that the fact of selecting more than one neighbor to relay the sent message could easily incur the simultaneous retransmissions and hidden nodes problems.

To solve these issues, we adopt an index-based timer that enables the explicitly selected relays to schedule their transmissions for a T send timer, computed based on the relay's index in the received ARL. The one with index zero rebroadcasts immediately, the second rebroadcasts after λt delay, and so on. T send is calculated as given below,

T send = i j λt, (7)
where i j denotes the index of the explicitly selected neighbor N j in the ARL, and λt represents one waiting time slot.

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P r e p r i n t n o t p e e r r e v i e w e d

Algorithm 2: Associated relays selection process: the vehicle is not a JV

Implicit selection of relays

Basically, considering the unique characteristics of VANETs, it is complex to guarantee robust wireless link between mobile vehicles. In other words, important packet loss still occurred because of the unexpected link failure problem, even-though taken into account multiple link condition parameters. Thus, adopting one new recovery strategy for compensating the lost packets while not increasing the dissemination delay is quite important to enhance the dissemination efficiency. To

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if ωf E,N > ωf max E,N then 9 ωf max E,N ← ωf E,N 10 M AP ← insert(R i .ID, N.address) 11 end 12 end 13 end 14 ARL ← M AP
achieve this goal, we first adjust our proposed inhibition rule with the message propagation pattern perspectives by making all vehicles able to monitor the propagation of the sent message under their transmission ranges. Then, each vehicle could make its own decision on relaying the message in a distributed manner, independently on whether or not they are explicitly selected to relay the data. One simple and efficient solution to implement this is to let every vehicle receiving the sent message and fall in its propagation direction to hold it, and schedule a recovery timer, denoted as T rec , computed as:

T rec = T max rec α 1 - d R,P d max + (1 -α)(1 -Θ R,P ) , (8)
where T max rec denotes the maximum recovery timer value; d R,P represents the distance between the Receiver R and the Previous relay node P, computed as:

d R,P = (x P -x R ) 2 + (y P -y R ) 2 ,
where (x N , y N ) and (x P , y P ) denote the geographical coordinates of vehicles N and P respectively;

and Θ R,P stands for link straightness factor, computed as given by Equation 5. In order to ensure robust relay selection process, remark that both implicit and explicit relay selection metrics are compliant with each other, except of the mobility parameters since the implicit selection has no 24

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If T rec expires and no inhibition occurred, i.e., the vehicle captures a link failure, the vehicle recovers quickly this issue by immediately broadcasting the message. A vehicle considers itself as falling in the message propagation direction if it is not inhibited to broadcast and has received the message from neighbor roaming inside the same road as it.

Besides, as VANETs have a time-varying density, we introduce an additional timer, namely Backup or T bkp , for fitting the sparse network scenario where the density of vehicles is not enough to ensure the envisioned propagation of messages. In this way, vehicles that receive for the first time the sent message and do not fall in its propagation direction will schedule their transmission for a backup timer, which is computed as given bellow:

T bkp = T max bkp + µ(0, 0.1), (9)
where T max bkp denotes the maximum backup timer value, and µ(0, 0.1) represents an uniformly distributed random component to avoid the simultaneous retransmissions problem. If the vehicle is not inhibited after elapsing T bkp time, meaning that a network partition is captured, the vehicle should immediately relay the message inside the road that is belonging to.

A case study

To illustrate the proposed dissemination scheme, an example scenario is shown in Fig. 4, where we assume that the Source Vehicle SV starting the dissemination process. In the beginning, SV incorporates its ARL, e.g., JV1 as FRN and V2 as RRN, and broadcasts the message. Receiving for the first time the sent message from one neighbor roaming inside the same road as them, all the receivers V2, V5, V15-V18 and JV1 are considered as falling in the message propagation direction.

Thus, the explicitly selected relays JV1 and V2 should schedule their transmissions for T send , while the others schedule their recovery timers T rec . Having a JV status, the ARL of JV1 is formed based on the inter-road propagation of messages by selecting one vehicle for each overlapped road, i.e., vehicles V5, V12-V14. Upon hearing the broadcast performed by JV1, the vehicles V5, V17 and V18 should immediately cancel their scheduled transmission, since the message propagation pattern has been already fulfilled in their transmission range by receiving twice copies of the same message from neighbors falling in two different road line directions (SV and JV1). As JV1 simultaneously belongs to all the overlapped roads, the explicitly selected relays V12-V14 broadcast after T send ,

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d while the other receivers schedule T rec . For example, V13 finds that the message was received from a rear neighbor, hence it should forward it towards its front side. Similarly, V2 forwards the message towards its front side by means of its FRN V9. However, in order to activate the implicit selection of relays, we assume that V9 has been moved outside the communication radius of V2, hence, it does not hear the transmission made by V2. Following the investigated implicit relays selection algorithm, vehicles V3 and V6-V8 are falling in the propagation direction of the message forwarded by V2, hence they schedule their transmission for T rec . Consider that V3 has the shortest T rec and V9 does not broadcast, V3 will be an implicitly selected relay. Notice, that the broadcast made by V3 will make the monitored message propagation pattern of vehicles V6-V8 fulfilled, which will force them to cancel their scheduled transmissions. The same process is repeated until ensuring the coverage of the entire AoI.

Performance evaluation

In this section, we present the performance assessment of our proposed solution using the OM-NET++ 5.6.2 network simulator [START_REF] Varga | An overview of the omnet++ simulation environment[END_REF]. The proposed BACKNET-HSR protocol is compared to the current standard of data dissemination in VANETs, CBF [START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF], and the sender-oriented BDSC scheme with the variant (LQ×d) as the most efficient approach compared to the other convolution schemes proposed in [START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF]. We generate the mobility of vehicles using the road traffic simulator 26

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 [START_REF] Krajzewicz | Recent development and applications of sumo-simulation of urban mobility[END_REF]. OMNET++ is coupled with SUMO by using Veins 5.1 [START_REF] Sommer | Bidirectionally coupled network and road traffic simulation for improved ivc analysis[END_REF], a popular network simulator framework that implements the required protocol stacks and other relevant features of the vehicular communication process, such as the IEEE 802.11p communication technology and the channel fading operation.

Simulation scenario

For evaluation purposes, we consider two urban simulation scenarios. The first simulation study is performed under a Manhattan grid scenario comprised of 81 evenly-spaced intersections in an area of 2,5 km 2 with bidirectional roads. The second simulation study is performed under a more realistic scenario known as Luxembourg SUMO Traffic (LuST) Scenario [START_REF] Codecá | Luxembourg sumo traffic (lust) scenario: Traffic demand evaluation[END_REF][START_REF] Codeca | Luxembourg sumo traffic (lust) scenario: 24 hours of mobility for vehicular networking research[END_REF] in an area of 2 km× 2,5 km square. The vehicular traffic is generated randomly according to the random trips model provided by SUMO. The maximum speed of each vehicle is around 14 m/s.

In this simulation study, we consider six different vehicles densities ranging from 30 to 125 27 This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d vehicles/km. Each simulation experiment lasts 120 s (with 20 s of warm-up period), where the dissemination process is triggered every 10 s from 10 randomly selected vehicles. Each disseminated message comprises 1024-byte data, which represents an emergency warning message to notify the vehicles roaming inside the area of interest. In order to assess the dissemination performance under a large scale network, we consider the whole network region as area of interest. Each simulation experiment is repeated 5 times with random sender vehicles, from which we obtain the mean value of each point in the graph. The main simulation parameters are summarized in Table 2.

Performance metrics

As mentioned in [START_REF] Amador | Evaluation and improvement of etsi its contention-based forwarding (cbf) of warning messages in highway scenarios[END_REF][START_REF] Abbasi | Towards fast and reliable multihop routing in vanets[END_REF], messages in VANETs should be spread rapidly with high delivery capability and efficient utilization of the radio interface. For this reason, our performance assessment of all three investigated protocols is based on the following metrics:

• Dissemination coverage: The ratio of the successfully receiving nodes from the total number of nodes roaming inside the area of interest.

• Dissemination Delay: The average elapsed time that a message takes to reach a given destination node.

• Saved Rebroadcasts: This metric is used to determine the usage efficiency of the radio interface [START_REF] Rehman | Forward link quality estimation in vanets for sender-oriented alert messages broadcast[END_REF], it determines the percentage of nodes that did not rebroadcast the message.

Hence, the more the rebroadcasts are saved, the lower the allocation and contention on the shared channel.

Numerical results and performance analysis

Fig. 6 shows the dissemination coverage ratio among three protocols for varying vehicular densities under the Manhattan-Grid and LuST scenarios. From this figure, it is apparent that the dissemination coverage is less effective in low node densities. The reason is that in poor vehicle density, the network connectivity can not be ensured, hence the probability of finding one complete routing path between two far nodes becomes low. For a better clarification of this case, Fig. 7 shows the dissemination coverage as a function of the distance from the originator vehicle (i.e., the vehicle that trigger the disseminated message) under the sparse network scenario, e.g., node density ≤50 vehicles/Km. For the lowest vehicular density (30 vehicles/km), the information coverage is sharply decreasing as the distance from the originator vehicle increase. This means that the higher the distance from the sender, the smaller the number of available links within that distance. In average, it can be observed that our proposed BACKNET-HSR exhibits much better performance compared to CBF and BDSC for both considered scenarios under the sparse networks. For a node density ≤50 vehicles/km under the LuST scenario, BACKNET-HSR can reaches on average more than 81%

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d based relays selection mechanism, hence the probability of finding equidistant neighbors from the sender (i.e., with equal transmission timers) in dense scenario is high. As a result, more data collision will occur because of the simultaneous rebroadcasts from nearby nodes, which subvert the availability of the network and affect the coverage capability. This problem is less likely to occur in the Manhattan grid scenario since, as described earlier, the neighbors of each sender vehicle (i.e.

the contender nodes) can be only distributed following a vertical and/or horizontal road structures.

Hence, the number of contender vehicles having similar retransmission timer is reduced, which explains the robustness of CBF's coverage performance in dense scenarios under the Manhattan grid scenario. As shown in Fig. 8, BDSC has an inconsistent coverage performance since it highly depends on the availability of the selected next hop relays. effective scheme in terms of the dissemination coverage. Fig. 9 illustrates the average dissemination delay for different node densities. As expected, CBF has the worst performance for both scenarios, since it involves the contention windows before each retransmission. Compared to BDSC, BACKNET-HSR not only adopts the sender-oriented mechanism during the dissemination process, but also propose the use of the receiver-oriented mechanism as a recovery strategy, thus it adds some extra delay that varies according to the vehicular traffic densities. In fact, for low traffic density (e.g., for 30 vehicles/Km, case of the Manhattan grid), BACKNET-HSR has twice higher dissemination delay compared to BDSC, while they have approximately equivalent delay in case of dense network (e.g., for 125 vehicles/Km of the same scenario). This is simply due to the backup mechanism adopted by BACKNET-HSR that is more used as the node density decreases. As can be seen from Fig. 9, the dissemination delays are much higher for the Manhattan Grid for all three protocols. This is simply because there is less diversity of next relay candidates in the Manhattan grid scenario, hence the sent messages require much more number of hops for reaching vehicles far away from the originator. For all three protocols, the lowest delay was achieved when the node density is very low (i.e., 30 vehicles/Km). The main reason is that, according to Fig. 7, the dissemination coverage is restricted only to a subset of close nodes, which basically requires few number of retransmissions to be fully covered. They reach a peak when the network density is approximately comprised between 40-75 vehicles/Km (vary according to the considered scenario and/or scheme). In fact, as shown in Fig. 6, the real beginning of the coverage enhancement has occurred with these densities range,

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d meaning that the density becomes higher enough to cover vehicles relatively far away from the message originator. However, it does not become higher enough to ensure the optimal behavior of the dissemination process, especially for CBF and in smaller proportion for BACKNET-HSR and BDSC. For CBF, the involved back-off timers depend on the distance from the sender nodes.

As a result, for low and medium densities, there is no guarantee to find one neighbor far enough from the sender to ensure the rapid propagation of messages. Therefore, the near neighbors are responsible for rebroadcasting the sent message, however with an expended back-off timers. As already stated, the delay incurred by BACKNET-HSR in that range of node densities is mainly due to the adopted backup mechanism, designed to compensate the mismatching of the envisioned propagation pattern with the low vehicular densities. BDSC appears as the less affected by this phenomena, because it adopts a simple sender-oriented dissemination process. By increasing the network density, we reach the optimal behavior of the dissemination process, which can noticeably reduce the transmission delay. However, when exceeding one threshold, e.g., 75 vehicles/Km for the Lust scenario, we observe a slight increase in the transmission delay. Actually, this fact can be attributed to the collision problem in dense vehicular scenarios as described earlier, since the delay mounting can be due to the channel allocation and competition caused by the extra overhead in these particular scenarios. This rise in delay is less remarkable under the Manhattan Grid scenario since, as stated before, the collision problem is less likely to be occurred in this scenario. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d propagation pattern, the number of rebroadcasts mainly depends on the considered road maps topology. The higher the number of roads, the higher the number of rebroadcasts. On the other hand, the broadcast decision in CBF and BDSC is mainly based on the distance and/or the link stability factors, independently from how the vehicular traffic is distributed. This is confirmed by the fact that the saved-rebroadcasts of BACKNET-HSR are noticeably improved under the Manhattan Grid scenario (the one with the lowest number of roads), while it remains the same for the other investigated protocols.

In general, as can be seen in both considered scenarios, BACKNET-HSR has the lowest savedrebroadcasts, especially in case of sparse networks (the case where BACKNET-HSR noticeably improves the information coverage). In reality, this suggests the trade-off between the coverage requirement and the overhead constraints. Meanwhile, it is observed from Fig. 10 that the increase of the traffic density leads to more and more convergence between BACKNET-HSR and the two other protocols, which means that BACKNET-HSR exhibits more robustness with respect to the traffic density variation. In other words, in order to achieve better dissemination coverage, the propagation pattern designed for BACKNET-HSR tends to fit the road topology maps, independently from the vehicular traffic density. In fact, in low and medium densities (<= 75 vehicles/Km) for all three protocols, the amount of the saved-rebroadcasts is increased linearly with the increase of the traffic density. However, for CBF and BDSC, this improvement becomes less remarkable when exceeding that range of densities (> 75 vehicles/Km). For the case of CBF, this confirms our previous analysis about its poor performance in terms of information coverage and delay in dense networks, since the packets collision are basically steaming from the simultaneous rebroadcasts among vehicles with similar back-off timers, resulting in an additional communication burden. In BDSC, the adopted relays selection algorithm is highly dependent on the link quality between vehicles. This means that, in dense networks, it is more likely that a given relay elects its near neighbors as the next relaying vehicles, which can noticeably increase the number of multi-hop retransmissions.

Conclusion

In this work, we developed a Robust BACKbone NETwork based on Hybrid Selection of Relays (BACKNET-HSR) to solve a series of challenging problems of data dissemination in VANETs.

The goal is to ensure the timely delivery of public interest messages under different traffic densities and complex urban scenarios. Firstly, we aim to overcome the problems stemming from the 34 This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d chaotic distribution of relays by designing an efficient relays distribution model suitable to the city settings and some specific characteristics of VANETs. The relays selection and inhibition rules are comprehensively adjusted to realize the envisioned distribution model in a distributed manner and without any extra overheads. To do this, we design one new message propagation pattern to build an on-the-fly backbone network that integrates a subset of potential relay nodes distributed parallel to the road lines, enabling messages to be disseminated in a structured manner with less signal blocking. Moreover, our proposed scheme addresses the trade-off between latency and reachability in sender-oriented and receiver-oriented mechanisms by exploiting the best features of both mechanisms in one hybrid scheme. To do this, an explicit selection of the relays is adopted as the primary relays selection algorithm, enabling a continues retransmission at the application layer to ensure low dissemination latency. As the explicit selection of relays has a high sensitivity with the frequent disconnection of the link connections in VANETs, an implicit selection of relays is adopted as a recovery strategy to compensate for the lost packets each time a link failure is occurred. In a word, a tight coupling of both sender-oriented and receiver oriented mechanisms is realized in one hybrid scheme to enhance the robustness of the relays selection algorithm.

Numerical simulation results reveal that our proposed BACKNET-HSR provides an interesting improvement compared to other typical dissemination protocols under two different simulation scenarios, particularly in terms of information coverage capability and latency. However, it adds some extra overheads depending on the considered road-map topology. The applicability of other relays distribution models without loss of BACKNET-HSR generality is an open issue in our future extension of this work. Meanwhile, it should be noted that BACKNET-HSR's relays distribution model is designed as the first part of a misbehavior reporting scheme with the ability of distributed data merging. BACKNET-HSR will be used to polls the vehicles roaming inside an area of interest to report their own misbehavior analysis. Then, we will exploit the coverage capability of the realized in-road backbones to merge the aggregated reports and backward the results toward the misbehavior authority.

  lection rule Explicit selection of relays -Before each broadcast, the sender vehicle should select the next hop relays and incorporate their identifiers inside the disseminated message. Implicit selection of relays -Upon receiving the message, the vehicle should hold it and schedule a back-off timer. The vehicle relay the message once the initiated timer expires. Inhibition rule Only the receivers finding their identifiers incorporated inside the sent message are allowed to broadcast, the other are inhibited.

Fig. 1 .

 1 In this figure, we consider the case of multiple selection of the next hop relays[START_REF]Intelligent transport systems (its); vehicular communications; geonetworking; part 4: Geographical addressing and forwarding for point-to-point and point-to-multipoint communications; sub-part 1: Media-independent functionality[END_REF][START_REF] Villas | Drive: An efficient and robust data dissemination protocol for highway and urban vehicular ad hoc networks[END_REF][START_REF] Rehman | A hybrid relay node selection scheme for message dissemination in vanets[END_REF][START_REF] Rehman | An adaptive relay nodes selection scheme for multi-hop broadcast in vanets[END_REF][START_REF] Turcanu | A multi-hop broadcast wave approach for floating car data collection in vehicular networks[END_REF], as they could achieve better coverage compared to the other solutions. Consider that the Source Vehicle SV initiates the dissemination process 11This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d

Figure 1 :

 1 Figure 1: Effects of the indiscriminate inhibition rule on the information coverage capability

Figure 2 :

 2 Figure 2: Proposed message propagation pattern over one-dimensional road line

Figure 3 :

 3 Figure 3: Front and rear neighbors determination

Algorithm 3 : 6 foreach

 36 Associated relays selection process: the vehicle is a JV 1 // E: The ID of the vehicle that execute the algorithm 2 // J: The Junction ID that the junction vehicle E associated with 3 Map < string, address > M AP ← null 4 foreach Road R i associated with J do 5 ωf max E,N ← 0 Neighbor N roaming in R i do 7 ωf E,N ← Compute ωf E,N as given in Equation

Figure 4 :

 4 Figure 4: Example of the proposed dissemination scheme

P r e pFigure 5 :

 5 Figure 5: The flow chart of the proposed Dissemination scheme

Figure 6 :

 6 Figure 6: Information coverage ratio vs. vehicle density.

Figure 9 :

 9 schemes. In CBF, the indiscriminate selection and inhibition of relays leads to low dissemination coverage, especially under sparse scenarios. In contrast, in case of dense network, the number of contender nodes will considerably increase, leading to a serious packets collision problem. As for BACKNET-HSR, by adopting a hybrid selection of relays while respectively adjusting the relays distribution according to the road lines geometry, the latter exhibits the best robustness for varying traffic densities and for different simulation scenarios. Thus, independently from the considered scenario, BACKNET-HSR is able to cover on average more than 85% of vehicles, as the most

Figure 10 :

 10 Figure 10: Saved rebroadcasts ratio vs. vehicle density.

Fig. 10

 10 Fig.10illustrates the saved rebroadcasts ratio for the investigated protocols and for varying vehicular densities under both considered scenarios. For BACKNET-HSR, due to the proposed

Table 1 :

 1 Comparative study of sender-oriented and receiver-oriented relays selection mechanisms

	Features	Sender-oriented mechanism	Receiver-oriented mechanism
	Relays se-

  The ID of the vehicle that execute the algorithm 2 // CR: The ID of the road in which E is roaming in

	3 if stateJV.f irst = T rue then
	4	goto Algorithm 3
	5	return
	6 end
	7 ωf max F RN , ωf max RRN ← 0
	8 Map < string, address > M AP ← null
	9 foreach Neighbor N do
	10	if N falls in CR then
	11	Θ E,N ← Compute the angle Θ as given in Equation 3
	21	if ωf E,N > ωf max RRN then
	22	ωf max RRN ← ωf E,N
	24	end
	25	end
	26	end
	27 end

1 // E: 12 ωf E,N ← Compute ωf E,N as given in Equation 6 13 if Θ E,N ∈ [0, 90] then 14 // N will be handled as an FRN candidate 15 if ωf E,N > ωf max F RN then 16 ωf max F RN ← ωf E,N 17 M AP ← insert( ′ F RN ′ , N.address) 18 end 19 else 20 // N will be handled as an RRN candidate 23 M AP ← insert( ′ RRN ′ , N.address) 28 ARL ← M AP

Table 2 :

 2 Main simulation parameters

	Parameter	Value
	Simulation time	120 s
	Mac model	IEEE 802.11p
	Vehicle density	30-125 vehicles/km
	Maximum transmission power	3 mW
	Maximum transmission range	≃ 250 m
	Bit rate	6 Mbit/s
	Carrier frequency	5.89 GHz
	Beacon size	32 Bytes
	Beacon frequency	1 /s
	α	0.8
	λt	0.01
	dmax	250 m
	vmax	14 m/s
	t max rec	0.1 s
	t max bkp	0.02 s

  Figure 7: Mean information coverage vs the distance from the originator vehicle for different low vehicular density scenarios.of the participating vehicles, while only 60% and 48% of vehicles are covered by CBF and BDSC respectively. In reality, this is already expected since both CBF and BDSC adopt an indiscriminate inhibition of the relay candidates (please refer to section 3), which becomes a serious problem when the number of available next hop relays is small. Also, we can see that the indiscriminate inhibition effect is more remarkable under the Manhattan Grid scenario, where BACKNET-HSR improves the dissemination coverage by approximately 24% and 42% with respect to CBF and BDSC. This is due to the fact that vehicles under the Manhattan Grid scenario follow only a vertical and horizontal distribution with sufficient spaces between parallel road lines to minimize the variety of available next hop relays in terms of polar distribution, making the issues described in Fig.3more reproducible. Summing up, BACKNET-HSR exhibits much better performance in terms of the coverage capability compared to CBF and BDSC for the low vehicular densities scenarios. For instance, it can achieve more than 90% of the coverage ratio under relatively sparse networks (e.g., 50 vehicles/km) while only 75% and 68% of vehicles are covered in CBF and BDSC respectively, which suggests that considering the vehicular distribution brings a significant enhancement in terms of the dissemination coverage.By increasing vehicle density, the network fragmentation becomes less possible and the number of available links toward far vehicles increases, resulting in the improvement of the coverage ratio for all the protocols as shown in Fig.8. However, for the case of CBF, when exceeding one density threshold, e.g., vehicle density = 100 vehicles/km for the LuST scenario, the coverage ratio starts to decline as the distance from the originator increases. The reason is that CBF adopts a distance

	.8 0.8 Figure 8: Mean information coverage vs the distance from the originator vehicle for medium to high vehicular density 1.2 1.6 2 2.4 information coverage in % distance from the sender in km 30 (Vehicles/km) BACKNET-HSR (LuST) CBF (LuST) BDSC (LuST) BACKNET-HSR (Manhattan-Grid) CBF (Manhattan-Grid) BDSC (Manhattan-Grid) 0.4 0.8 1.2 1.6 2 2.4 40 (Vehicles/km) 0.4 0.8 1.2 1.6 2 2.4 50 (Vehicles/km) 0 20 40 60 80 100 0.4 1.2 1.6 2 2.4 information coverage in % distance from the sender in km 75 (Vehicles/km) BACKNET-HSR (LuST) CBF (LuST) BDSC (LuST) BACKNET-HSR (Manhattan-Grid) CBF (Manhattan-Grid) BDSC (Manhattan-Grid) 0.4 0.8 1.2 1.6 2 2.4 100 (Vehicles/km) 0.4 0.8 1.2 1.6 2 2.4 125 (Vehicles/km) P r e p r i n t n o t p e e r r e v i e w e d scenarios.
	abstract=4303246

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This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/

This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4303246 P r e p r i n t n o t p e e r r e v i e w e d