Francisco Nunes
email: fjfnunes@gmail.com

Henrique O'neill
email: henrique.oneill@iscte.pt

Trust-Based Access Control in Storage Middleware Grids: a Reference Framework Proposal to Deploy in the Financial Sector

Keywords: Data storage systems, TBAC, grid data storage, virtual organizations

Fostered by the development of the Web, the financial sector has been able to develop a broad set of shared IT services. Despite the high levels of maturity that have been achieved there are still improvement opportunities concerning the sharing of services by financial institutions. This research addresses the sharing of data storage resources among different financial organizations to fulfil the needs for unplanned peaks of data storage, or to help shortening the time needed to start projects requiring allocation of storage space when this is not available in the organization. To answer to these requirements it was proposed a data grid infrastructure (SRM), centrally managed by a versatile storage resource manager middleware. Senior IT infrastructure managers of representative financial organizations have been questioned to assess the proposed solution. Security has been identified as a key concern that prevents the dissemination of this type of solutions. These solutions may be fostered by the adoption of a security mechanism that would consider the behaviour of the distinct organizations in the use of the shared resources. To meet this requirement the research proposes an algorithm for controlling the access to the storage resources based on trust, where the level of trust in the joint organizations will vary dynamically according to the fulfilment of the rules concerning the use of the shared storage by its users.

Introduction

This applied research project described in this paper has been sponsored by AdI under the "PhD in the Enterprise" initiative 1 , a program that aims to contribute to the improvement of the Portuguese economy by addressing specific problems of the industry in topics that require further research. The project aims to improve the use of data storage resources by firms of the financial sector. It was developed in collaboration with two of the most important Portuguese banks. Like many other institutions in several sectors, banks have several ongoing IT projects of the most diverse nature. Sometimes these organizations have some difficulty in initiating some of these projects that rely on computational power in general and in particular depend on the availability of space in data storage systems. These projects that need data space may begin immediately, if the disk space is available, or take up to three months or more if the disk space does not exist and involves an operation of procurement. To meet this need there are some institutions that aim to drastically reduce the average time of purchase and installation of new storage equipment by redesigning procurement processes.

After a thorough analysis of the problem [START_REF] Zissis | Addressing cloud computing security issues[END_REF] a framework was created to address the problem of availability of storage resources in order to deploy space in storage systems immediately or almost immediately, particularly for projects developed in the studied financial sector institutions. This framework will comprise the creation of a federated environment composed by different financial institutions with a centralized management. Each institution contributes with the storage resources that can provide at a given time, so it can help to fulfill immediate needs of any other institution belonging to this federated environment that does not have storage resources available at that time. The way to implement this framework implies that the shared storage resource management is done through the implementation of a common grid storage by using the same kind of middleware. The proposed middleware is based on the Storage Resource Manager (SRM) [START_REF] Sim | Grid, Storage and SRM[END_REF]. It meets the requirements of data operation of financial institutions and has been accepted by the architects and IT managers of these institutions. However the use of SRM for temporary data sharing lack security features (access control, acces and operations log) [START_REF] Foster | Cloud Computing and Grid Computing 360-Degree Compared[END_REF]. This is an issue also identified by the experts of the institutions that participated in the investigation. So, an element of security to control data access based on dynamic trust management systems was created and added to the framework. It enables to manage not only the access and use of resources by users of various institutions with access to the pool of shared resources, but also assesses the reputation and trust of the entities that provide the resources.

This work relies on a series of research results on models on Trusted Based Access Control, collaboration and sharing to generate an integrated framework. It also addresses issues related with the technical feasibility of the infrastructure and its implementation.

Contribution to Cloud-based Engineering Systems

Typically Cloud Computing refers to the hardware and software resources that are available via the Internet [START_REF] Armbrust | A view of cloud computing[END_REF][START_REF] Erdogmus | Cloud Computing: Does Nirvana Hide behind the Nebula? Software[END_REF]. The resources made available in this way are called IT services [START_REF] Foster | Cloud Computing and Grid Computing 360-Degree Compared[END_REF]. The features of these IT services are distinguished by being scalable, configurable, measurable and able to provide an easy access from the perspective of auto use.

The infrastructure that supports these services must be a structure with sufficient elasticity to satisfy the business services requirements. The infrastructure proposed in this research is based on a grid of data storage with clustering of resources dictated by the availability of each institution that belongs to the group that makes up the grid [START_REF] Foster | Cloud Computing and Grid Computing 360-Degree Compared[END_REF].

In the context of IT infrastructure and Cloud Computing the proposed grid data storage with centralized management, has precisely the main advantage of allowing of inclusion of resources in the grid space to meet peak needs or to remove these resources when there if less need for space data [START_REF]IBM Cloud Computing und Green IT -Ausbildung 2010[END_REF]. This requires the ability to monitor the needs of the users and to adjust the elasticity of the Cloud supply.

The application of this technology can support different types of offering Cloud Computing services [START_REF] Andreozzi | Cloud Storage as a new Storage Class : QoS Characterization and Cost Analysis[END_REF]. An example is to use the platform as part of a shared services infrastructure, for example by deploying a Private Cloud serving various companies of the same economic group. An alternative approach will be to share resources between various financial enterprises despite the allocation of a resource to be assigned specifically to one of the group companies [START_REF] Marsh | Formalising Trust as a Computational Concept[END_REF]. This sharing of resources will be partial and temporary in nature. It will be guaranteed not to harm the infrastructure, the resource will be temporarily allocated according to a set of rules and the recovery of the resource will be ensured. By using the Cloud with this collaborative network approach, those who provide resources for these effects will also benefit from them in times of unforeseen need. This versatility in the context of data storage can be materialized by a grid infrastructure for data storage with centralized management, able to integrate the storage devices capabilities of institutions that have joined this sharing group in the federate environment.. The uses of a data storage shared infrastructure can thus be a privileged resource in the context of Cloud systems, as the type of application described or other that will be implemented.

Related Work

For trust management, access policies and authorization different approaches have been explored in distributed environments with centralized management. However, no unified definition of trust exists in the current literature of computer science [START_REF] Boursas | Trust-Based Access Control in Federated Environments[END_REF].

Most settings found in work related to the classification of trust tend to only use a number, a slight degree, a marker or a combination of all. In this context, there are several ways to define and establish a trustful relationship. The trust is paramount in a relationship and can be negotiated if the collaboration is established between actual organizations. In other scenarios, the trust agreement may be specified by one party (e.g. a service provider) and accepted by the other parties, without negotiation (e.g. a service consumer). Yet another example of establishing trust implies that the trust agreement may be declared by a supervisory authority and be applied by all parties involved (e.g., global policies declared by the supervisor of the federated environment).

In fact, one of the initial works that tried to provide a formal trust management, which could be used in computer science, was presented by [START_REF] Marsh | Formalising Trust as a Computational Concept[END_REF] [START_REF] Marsh | Formalising Trust as a Computational Concept[END_REF]. Marsh's model is based on social trust properties and provides a motivation for the integration of some of the aspects of trust based on the concepts of sociology and psychology. But these sociological foundations proved that the model is quite complex and can hardly be implemented in electronic communities. Furthermore, the model places emphasis on the experiences of their own bodies, neglecting the views of others, a factor that prevents a network of trust to be built collectively. Later, 2009, Boursas [START_REF] Boursas | Trust-Based Access Control in Federated Environments[END_REF] developed a framework in order to manage federated environments that include a model of trust management that was accepted by the cientific community.

Shared Resources and Trusted Based Access Control

In this section we present the research developed around the middleware for grid storage control, its key features and capabilities. We will also present the Trusted Based Access Control algorithm inserted into the framework that allows varying levels of confidence of participants of the Sharing Group. Finally a prototype used to validate the developments carried out in the research model will be presented.

This work built a varying trust model that is the basis of a framework that allows trust based access control to shared resources by different institutions in the financial sector, in a federated environment of centralized management, which are themselves providers of resources storage (when resources are available) while customers of that environment.

Middleware Storage Resource Manager

The elected grid storage middleware management system was a modified version of the Storage Resource Manager (SRM) [START_REF] Alfieri | From gridmap-file to VOMS: managing authorization in a Grid environment[END_REF] implementation. The StoRM (Storage Resource Manager) works in a distributed fashion and with high availability across multiple systems ("Cluster", "GRID"). It allows to manage (share, transfer and access) data storage in an easy, fast and flexible way. The implementation can be distributed over several "datacenters" even when the geographical distance between them is very large. Its main characteristics are flexibility, scalability, high performance, able to run on various types of "filesystems" and independence of the storage manufacturer. It implements the mechanisms of SRM V2.2 interface standard (https://sdm.lbl.gov/srmwg/). A StoRM application runs on Linux systems on "POSIX filesystems" (ext3, ext4, xfs, etc.), enabling the grid computing to simultaneously provide a direct of multiple systems to a common "filesystem" (e.g. GFS for Linux, HP-UX CFS and Veritas, IBM GPFS, etc.).

For sharing the storage resource data all suppliers and customers in the Sharing Group must have installed SRM in their infrastructure. SRM is used by various academic solutions from simple "grid map files" to Role Based Control Access (RBAC) systems, with Virtual Organizations Management Systems (VOMS) among other proposals [START_REF] Boursas | Standards and New Technology for Systems and Virtualization Management: A Report on Svm'08[END_REF], despite its breach in access control. This is not the case of the financial sector institutions which have tight security requirements. The implementation of TBAC in SRM and its application to financial sector was a major contribution of this research in order to solve the difficult problem of managing the storage resources in the day-to-day operation of the financial institutions. TBAC is one of the control access models that has large acceptance and works fine when we are dealing with IT communities. Because is a more interesting base to acess control by level of trust in an entity than by the role the person has in his own organization (like RBAC did). It is believed that virtualization can help to significantly improve the application of more stringent security policies and finer granularity with the SRM as a virtual machine that provides basic insulation through Virtual Organizations (VOs) to share resources and policies to monitor application properties. VO's are the way how an organization is created in the storage grid.

Algorithm for Trust Variation

The approach presented in this paper sought a quick and cost effective way to supplement the static nature of the federated environments, with a set of new mechanisms for dynamic reliability assessment, without affecting others or compromising the integrity of the federated environment [START_REF] Boursas | Standards and New Technology for Systems and Virtualization Management: A Report on Svm'08[END_REF]. A notable advantage of the presented solution is to reduce the effect of the arbitrariness of classical evaluation methods of confidence that are usually solely based on the classification of individuals. The proposed approach is based on the evaluation, updating and aggregation of trust by reputation and from past experiences. Three functions were used one to enhance, another to decrement and other neutral for the confidence levels and are used as follows:

= 1 - ∑ , x ∈ {0, 0.5, 1}, α ∈ Ν. (1)
• The function (1) depends on the number of interactions, performs the incremental curve of confidence values that represent reliable behavior (above the axis of 0.5). The asymptotic values increases, but never touch the axis of one (indicating the absolute confidence) such that the confidence value is closer shaft requiring a large set of interactions. This function, on one hand, facilitates the rapid increase of the level of trust from the neutral level of trust for a higher level, but on the other hand, ensures that sufficient positive interactions must be made to achieve Absolute Trust Level.

g(x) = ∑ , x ∈ {0, 0.5, 1}, α ∈ Ν. (2)
• The second function is the inverse function of the previous one. The same principle is defined for all values of trust representing an unreliability. Similarly, the curve rises rapidly to confidence values below 0.5, while rises more slowly when approaching the axis of 0 which represents the Absolute No Trust Level.

ℎ = 0, x ∈ {0, 0.5, 1}. (3)
• The function ( 3) is a static function, zero, representing that no modifications are required by Neutral Trust Level, which of course can improve or degrade under the other two above functions

• (x) is a set of interactions with a rating level represented by discrete values: x ∈ {0, 0.5, 1} • The parameter α represents the convergence factor of the curve of the exponential function.

Implementation of the Prototype

A prototype was implemented on virtual machines (Figure 1) where each machine implements a service and adopts the following authorization flow: 1. All the entities are made known to the system. Each one has to send an id and the role (user or provider) for the Services server that recognizes and keeps the records of the entities. If the entity that manages the shared resources confirms which entities are forwarded in accordance with the policies of the VO, and no reputation problems arises, then writes the data and the role of the user.

2. The Bank B, which aims to provide resources, creates and sends the VO, VO-id, the VO policy and public key pair for the server managers of the shared resources, which are stored on the server resource services (SSR ).

3. The assets manager notifies the different participants, with user role, which has resources available.

4. The Bank C, needs resources and questions whether the SSR VOs are available in accordance with their technological needs and if the supplier complies with the desired level of trust. If so the SSR registers the request and analyzes the reputation of the Bank C, the requestor.

5. After the validations the SSR delivers the public key of B VO customer to Bank C. Thus the Bank C can enter the VO.

6. If the Bank C complies with the contractual agreement, the index will increment its trust in a reliable server, if some of the clauses violate the agreement its trust will be decremented. In the future, if there are many institutions competing for the same resource, it will be privileged the entity that holds the higher levels of trust.

Discussion of Results, their Validation, and Critical View

Given the nature of the research carried out, its assessment should be taken into account in its different dimensions. We considered two dimensions, one Formal and another Functional. Formal assessment was necessary to evaluate the coherence of the research where, in this case, comprised the validation by an expert panel of the acceptance in the sector and by other hand base the mathematical model that was proposed in other derivative models. Concerning the functional assessment we have to demonstrate that things really work and this was done by testing a prototype implementation and by validating that the grid storage solution may be applied to the financial sector, if the context meets certain requirements that enable the solution acceptance.

Formal Assessment

With respect to the adequacy of the Middleware Data Storage System Oriented for a Grid implementation to the financial sector, an expert panel was created and it was explained to the panel members the middleware that was developed to become a proof of concept. Unanimously the panel members agreed that the use of virtualization technology would be the way forward for the financial industry and even suggestions were given that provided good contributions to the prototype that was developed.

Regarding the adequacy of the dynamic variation of the trust model used, it was formally presented in the doctoral thesis of [START_REF] Marsh | Formalising Trust as a Computational Concept[END_REF] [START_REF] Marsh | Formalising Trust as a Computational Concept[END_REF], which has profoundly demonstrated its validity as well as the mathematical representation of the belief model considered. Later, mentioned above, [START_REF] Boursas | Trust-Based Access Control in Federated Environments[END_REF] [START_REF] Boursas | Trust-Based Access Control in Federated Environments[END_REF] with a variation introduced, applied this representation in the framework presented in her doctoral thesis. We proceeded to work in this setting, maintaining and ensuring semantic issues in the Body of Real Numbers, keeping unchanged its initial algorithmic essence.

Functional Assessment

In order to validate the acceptance by the financial industry an expert panel that studied the issue was created and agreed that the proposal made in this research was a good idea. The expert panel also contributed with suggestions that helped to improve the results of the research, namely in the security middleware component used in.

With respect to the prototype it has to be evaluated according to all the expected benefits that will be learned from its implementation. The performance has no significant impact in the operations. Conversely, the impact of their gaps must also be assessed to foster future improvements and extensions.

Conclusions and Further Work

The proposed trust model was developed just to solve an issue of lack of security found in the middleware that was adopted in the framework. The middleware was chosen as a solution to the needs of disk space available for start-up projects in the financial sector. The middleware was the option to provide central management of the Sharing Group. It was found to be suitable for the purpose since no prior knowledge of each element that needs to use the resources available in the group becomes necessary.

The adaptation of the framework applied to address the problem, assessing the suitability of the dynamic trust management model, as well as the formal evaluation of the developed mathematical model, are key components of the research developed. The suitability of the framework presented in this research was also sustained by leveraging the knowledge base of frameworks previously investigated, developed and applied in doctoral thesis such as Boursas [START_REF] Boursas | Trust-Based Access Control in Federated Environments[END_REF], which enabled to justify its application in this context the financial sector.

The mathematical model that was created followed the standards of mathematical inference of parametric models based on the Marsh's theory of belief (2004), thus justifying the application of the framework to the financial sector. The approach presented in this research complements the nature of more traditional systems with a new trust mechanism for evaluating trust dynamics. The proposal for a broader concept of trust, allowing dynamic trust values contributed to the body of knowledge of the specific area Trusted Based Access Control. This approach sought an efficient cooperation between members of the Sharing Group and any external organization without compromising the integrity inside the Sharing Group or affecting any thirdparty. Basically it allows a trade-off between flexibility, speed and degree of automation in the configuration of cooperation agreements and the level of security and privacy hit. As future work, certain points that can enable to evolve and enrich this research are:

• The research of inter-organizational trust and Service Level -there is a need to investigate this point since inter organizational trust agreements may conflict with organizational security policies, SLAs and restrictions

• Research of other dimensions of trust, aimed at identifying the behavior of other elements of trust. For instance the research of belief in case of an organization is absolute unknown of the group and the new contribution to the model once itself is very flexible.

Fig. 1 .

 1 Fig. 1. Auth Flow

AdI -Agência de Inovação -Doutoramento em Empresa


Marcos A Pisching
email: marcos.pisching@usp.br

Diolino Fabrício Junqueira

Santos Filho

Paulo E Miyagi
email: pemiyagi@usp.br

Fabricio Junqueira

Diolino J Santos Filho
email: diolinos@usp.br

Service Composition in the Cloud-Based Manufacturing

Keywords: Cloud-Based Manufacturing, Cyber-Physical Systems, Industry 4.0, Internet of Things, Service Composition, Virtual Enterprises

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The Industry 4.0 is focused on creating smart products, procedures and processes. It was first presented in 2011 at Hannover Fair and launched in April, 2013 [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF]. This concept has meeting the smart manufacturing industry concerns that are dealing to spark design innovations and bring new products to market faster, and additionally, they are looking for satisfying the individual customer desires. In the Industry 4.0 this behavior changes the production concepts from mass to individualized production. Objects, sensors and actuators should communicate and exchange information among them all the time [START_REF] Lasi | Industry 4.0[END_REF]. These tasks are realized by two concepts, the Cyber-Physical Systems (CPS) and Internet of Things (IoT) [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Lasi | Industry 4.0[END_REF], [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF], [START_REF] Heng | Industry 4.0 -Upgrading of Germany's Industrial Capabilities on the Horizon[END_REF].

In the Industry 4.0, also referred as smart factory, the CPS and IoT concepts are converging to the Internet of Services that widely uses the cloud-based approach for creating, publishing, and sharing the services [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Lasi | Industry 4.0[END_REF], [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF], [START_REF] Ungurean | An IoT Architecture for things from industrial environment[END_REF]. In this context, the services represent manufacturing processes, which could be offered by virtual enterprises (VE). Thus, any dispersed partner around the world can meets the demands according to his ability, capacity, and availability. These issues have been gained force at worldwide industrial sector, and its complexity implies on the demand of collaborative and smart services, which should be available and shared on the Internet infrastructure [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Heng | Industry 4.0 -Upgrading of Germany's Industrial Capabilities on the Horizon[END_REF], [START_REF] Ungurean | An IoT Architecture for things from industrial environment[END_REF].

Service composition is one of many concerns in the Industry 4.0. For example, the customer could require one virtual service, and then the virtual system must set a composition of services, in a way to comply with the customer specific demand. This research is centered on service composition and how can it be possible in a way to offer smart services and how it can integrate the real systems to the virtual systems, to contribute for Industry 4.0 expectations. This paper presents a survey about service composition in a cloud-based manufacturing over the Industry 4.0 context, for a future perspective of a collaborative and integrated environment, on which VE could be established to provide services and goods to the customers. It could help any enterprise regardless of size, but small and medium-size enterprises (SMEs) could be more competitive by joining business and knowledge.

Benefits from Cloud-based Engineering Systems

In the Industry 4.0 the end-to-end engineering and the vertical and horizontal integration can have a significant increase by the extensive use of CPS and IoT. Consequently, it is expected that the number of projects, data and services over the Internet infrastructure should have an exponential growth. Therefore, the cloud-based engineering systems can benefit the emergent Industry 4.0 in a way to offer infrastructure, platforms, and software among the partners [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF] and also contributing to the development of SMEs [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Lasi | Industry 4.0[END_REF], [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF]. By these resources, the services and data could be available for any partner regardless of the platform and operational system. The cloud-based technology could be decentralized, and it is favorable for the deployment and sharing of services among the member of projects. In the worldwide context, where the service demands should rapidly increase, the stakeholders must be prepared to improve the ICT to answer the demands in a short time. The cloud-based infrastructure could be scalable and dynamic to attend the entrepreneur needs faster. In addition, these systems could support the service composition based on serviceoriented architecture (SOA) for the establishment of VE, where SMEs could be favoured to the design of new products and, in the same time, to become faster in the answers to market fluctuations [START_REF] Gruner | Extending Lifecycle of Legacy Systems -An Approach for SME to Enhance Their Supported Business Processes through a Service-Integration-System[END_REF]. The Industry 4.0 and VE require more flexible environment and need autonomous system reconfiguration to support the market concerns. Then, according to [START_REF] Wu | Cloud Manufacturing: Strategic Vision and State-of-the-art[END_REF], cloud-based manufacturing should comply task as service oriented, customer centric, and demand driven manufacturing, in a way to enable industrial control systems, service composition, and flexibility [START_REF] Xu | From Cloud Computing to Cloud Manufacturing[END_REF].

Fundamental Concepts

Industry 4.0

The Industry 4.0 concept, also referred as the fourth industrial revolution [START_REF] Schuh | Global Footprint Design on Genetic Algorithms -An "Industry 4.0" perspective[END_REF], integrated industry, or smart factory [START_REF] Heng | Industry 4.0 -Upgrading of Germany's Industrial Capabilities on the Horizon[END_REF], is centered on network and Internet architecture [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], on which is possible to integrate the virtual world with the real world by using Information and Communication Technology (ICT). In the smart factory, all the relevant "things" involved in the manufacturing processes could be recognized, and then the hardware and software can automatically behave, with less human intervention, to perform all the tasks in a production line. It also depends on Cyber-Physical Systems (CPS) and Internet of Things (IoT) concepts. Its main purpose is to improve the efficiency and productivity of industrial processes by the smart automation environment and by the industry integration [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Lasi | Industry 4.0[END_REF]. Accordding to [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF] in the Industry 4.0 context the products can control their own manufacturing process, and additionally, the customer should be more involved in the creation processes of new products. This project has been leading by German government, German industries, and German Research and Development [START_REF] Lasi | Industry 4.0[END_REF]. However this term is little know in the world, it has been spreading and being the issue in some technology conferences, and research and development [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF].

Cyber-Physical Systems and Internet of Things

The Cyber-Physical Systems (CPS) and Internet of Things (IoT) are the basis of Industry 4.0. The Fig. 1 shows the relation of CPS and IoT with the Industry 4.0. The CPS are related with the integration of computation technologies with physical processes [START_REF] Shi | A Survey of Cyber-Physical Systems[END_REF]. The CPS are based on a structure composed by embedded systems (ES) and physical environment, on which are expected the ubiquitous computing that provide information anytime and anywhere [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF]. Communication technology such as distributed application and service provision, and embedded system technologies such as robots, control systems, sensors and actuators are converging in a way to offer a distributed and embedded web-based system represented by services.

On the manufacturing, the CPS have been used at shop floor tools and equipment to integrate the manufacturing processes and to enable the machine-to-machine communication [START_REF] Jazdi | Cyber Physical Systems in the Context of Indurstry 4.0[END_REF]. Additionally, the CPS infrastructure enables the communication between real and virtual systems, and vice-versa. By the virtual systems is possible to design, model and simulate products that should be exchange to real world to be produced. On the other way, the physical processes for manufacturing products could be visualized by a virtual environment such as three-dimensional environment or augmented reality environment.

The IoT is a concept that is also based in the ICT, which uses the Internet infrastructure. It consists of sensory and smart object interconnection to offer connectivity of devices, systems and services. Its main purpose is to connect everything including resources, information, objects, people and machines to create the Internet of Things and Services [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF]. In the IoT each object must be addressed with a unique identification that enable the interaction and cooperation with neighbours to reach common goals. Both, CPS and IoT resources, could be virtualized as services, and then deployed over a cloud-based infrastructure, on which is possible to store, exchange, share, and process data. Furthermore, the stakeholders could deploy and share manufacturing processes as a service. All this resources can be used in a collaborative and integrated environment (CIE) to model and design goods and services by VE, and may be favorable for the SMEs and start-ups, in a way to facilitate design innovations and provide new products for an increasingly sophisticated, dynamic and demanding market.

Service Composition

In the context of manufacturing, all the objects, features and resources that represents their states, information, and mode operations are considered as services [START_REF] Wang | An Interoperable Solution for Cloud Manufacturing[END_REF]. These services can be described, published, located, and invoked over a network, which purpose are to perform actions as answers from requests between service consumers and providers [START_REF] Dustdar | Services and Service Composition[END_REF]. Services could be implemented on a single or on a large number of servers [START_REF] Dustdar | Services and Service Composition[END_REF], and over the cloud-based technology. Such services, when working alone, could be more difficult to perform the actions according to demands. Therefore, the combination of exiting and available services from different enterprises, which is called service composition, can perform both simple or complex tasks [START_REF] Dustdar | Services and Service Composition[END_REF], [START_REF] Liu | A Solution of Dynamic Manufacturing Resource Aggregation in CPS[END_REF].

In the Industry 4.0, CPS components, hardware and software are represented as services. When it is published in a collaborative environment they could be used to compose an integrated service, which aim to solve problems of common interest [START_REF] Liu | A Solution of Dynamic Manufacturing Resource Aggregation in CPS[END_REF], [START_REF] Silva | A Service-oriented and holonic control architecture to the reconfiguration of dispersed manufacturing systems[END_REF]. The Fig. 2 depicts a single situation, where the stakeholders or partners, such as SMEs, can deploy and publish their virtual services on a cloud-based infrastructure in a way to establish virtual enterprises, which the main purpose is centered on a collaborative work to provide solutions according to the customers demand. Therefore, the customer could request a service by a virtual environment, and then a background system over the cloud should verify the availability of services and the best way to compose it to solve the customer need.

Research on Service Composition over the Industry 4.0 Concepts

The Industry 4.0 platform is in initial stage, hence the researches on this field must have many issues to explore and one of them is the service composition based on CPS and IoT concepts.

Based on CPS, [START_REF] Liu | A Solution of Dynamic Manufacturing Resource Aggregation in CPS[END_REF] propose a dynamic manufacturing resource aggregation (MRA) architecture, on which they consider a virtualization model and describe in detail the implementation process of the manufacturing resources and a dynamic service composition.

In the [START_REF] Seiger | Modelling Complex and Flexible Processes for Smart Cyber-physical Environments[END_REF] the CPS resources are related as components, for further modelling for complex and flexible process for smart environments. The authors present a process meta-model and use Unified Modelling Language (UML) to represent component composition using object-oriented approach, and then it is used to model process component and its composition.

For a cloud-manufacturing implementation focused on customer centric solutions, the [START_REF] Wu | Cloud Manufacturing: Strategic Vision and State-of-the-art[END_REF] present an overview about cloud manufacturing, and show the current issues over the architectures, models and framework, for further exposure about the potential impact and future work. They also present the relation of service composition with the cloud-manufacturing systems, on which is presented a review about methods and implementation considering service composition in VE and virtual marketplace, for further presentation of model, framework, infrastructure, and architecture of cloudmanufacturing for flexible, cooperative and collaborative virtual enterprises.

Based on VE establishment, the work [START_REF] Li | Everything-as-a-service platform for on-demand virtual enterprises[END_REF] adopt the everything-as-a-service concept to propose a service-oriented platform for on-demand virtual enterprise. The suggested platform supports flexible integration of networked resources and help the formation of VE considering trusted service composition, data service centric business collaboration, and business process utility. Considering collaborative and integrated environment, a modeling of service composition by interpreted Petri net for system integration is presented in [START_REF] Fattori | Service Composition Modeling using Interpreted Petri Net for System Integration[END_REF], on which is proposed a coordinated and collaborative control of a dispersed productive system.

A widely approach about service composition based on ontology was realized in [START_REF] Cai | An Approach for Composing Services based on Environment Ontology[END_REF]. The authors present a method based on algorithms, on which automatic service composition is studied to decompose the requirements, the rules to determine the relation among the services, and the algorithms for composing services.

Associated to the new paradigms such as cloud computing and Web of Things, [START_REF] Sheng | Web Services Composition: A Decade's Overview[END_REF] report an overview about the lifecycle of web services composition (WSC) and present issues about standards, research prototypes, and platforms, which is assessed using a set of criteria. They show the state-of-the-art of WSC, and present a generic model for the lifecycle from it, which is used to compare with different prototypes using the defined criteria.

These studies show general issues and concerns around the service composition such as architecture, models, and methods that could be explored and applied on Industry 4.0.

Discussion on Service Composition for Industry 4.0

In the Industry 4.0 is expected a large growth of the objects and services available over the web due its worldwide trends involving the growing adoption of CPS, IoT and services.

Service composition, which is also applied in the smart manufacturing industry, is one of the essential problems of service-oriented computing [START_REF] Liu | A Solution of Dynamic Manufacturing Resource Aggregation in CPS[END_REF]. In [START_REF] Wu | Cloud Manufacturing: Strategic Vision and State-of-the-art[END_REF] the author points to the concerns over the automation and control, business model, information and resource sharing, distributed system simulation as services.

The research [START_REF] Dustdar | Services and Service Composition[END_REF] points to the problem around the composability, adaptive, autonomic composition, quality of services, and service governance, management, and administration.

The [START_REF] Seiger | Modelling Complex and Flexible Processes for Smart Cyber-physical Environments[END_REF] suggests a decentralized and distributed workflow across several orchestration peers in a way to increase the availability of the workflow process. They also work on a process component repository and a semantic domain-model for the classification of process components. Additionally, they will investigate the agentbased technology to find appropriate process composition.

The SMEs have been demonstrating significant importance around the economic growth of the European Union, on which several of them are consolidated and new companies have being created [START_REF] Gruner | Extending Lifecycle of Legacy Systems -An Approach for SME to Enhance Their Supported Business Processes through a Service-Integration-System[END_REF]. According to [START_REF] Gruner | Extending Lifecycle of Legacy Systems -An Approach for SME to Enhance Their Supported Business Processes through a Service-Integration-System[END_REF] these SMEs have been found difficulties to meet demands and react to the business changing due their manufacturing limitations, interoperability, and its lack of collaborative capabilities. It could be improved by SOA, which has been used to undertake inter-enterprise collaboration [START_REF] Silva | A Service-oriented and holonic control architecture to the reconfiguration of dispersed manufacturing systems[END_REF] by the orchestration and composition of services to join the SMEs in a interconnected network to form a virtual enterprise.

According to [START_REF] Cai | An Approach for Composing Services based on Environment Ontology[END_REF], subsequent research will extend the ontology approach for supporting the service composition in various domains. To [START_REF] Fattori | Service Composition Modeling using Interpreted Petri Net for System Integration[END_REF], the integration and coordination of dispersed productive system is a problem that need investigation. In [START_REF] Sheng | Web Services Composition: A Decade's Overview[END_REF], web services composition has been an active sector for research and development, and activities including standardization, research, and system developments have been produced.

Considering the recommendation from [START_REF] Kagermann | Recommendations for Implementing the Strategic Initiative Industrie 4.0[END_REF], [START_REF] Macdougall | Industrie 4.0 -Smart Manufacturing for the Future[END_REF], [START_REF] Heng | Industry 4.0 -Upgrading of Germany's Industrial Capabilities on the Horizon[END_REF], all these issues also need attention and could be exploited over the Industry 4.0. Additionally, issues like integration of CPS focused on collaborative, dynamic and smart services should be considered on smart industry researches.

Conclusions

The Industry 4.0 project promises to break-thru the boundaries of the conventional industries by the Information and Communication Technology (ICT). In addition, it is expected the increase of the number of members on the production chain in a collaborative environment, on which their location is indifferent and all the resource could be accessed by ubiquitous systems from any place of the world. In the same way it is expected that all the objects involved on the production processes can be available as services, and that they could communicate and exchange information among them.

The Industry 4.0 expectations and its complexity caused by the large number of interconnected machines, products, processes and people could increase the challenges and expand the opportunities for the research fields such as data security, standardization, and services interoperability. The SMEs may gain force on the Industry 4.0 by the virtual enterprise establishment. The shared skills, knowledge and resources as services over the cloud-manufacturing context, should leverage the business potential and improve the customer satisfaction. Although, strategies and methods should be adopted to improve the service composition among thousands of objects, services, and business.

Fig. 1 .

 1 Fig. 1. The Industry 4.0 and its relation with CPS and IoT in a cloud-based manufacturing. Industry 4.0 depends on CPS and IoT technologies. These two concepts are converging to the Internet of Services that provide a set of services, which represent manufacturing processes. A cloud-based manufacturing is used to compose a set of services to offer solution for VE.

Fig. 2 .

 2 Fig. 2. Stakeholders publish their CPS components as services to provide a common solution in order to establish a VE to answer a specific market need.

Acknowledgments. The authors would like to thank the financial support of the Brazilian government agency MEC/CAPES, for funding the DINTER USP-IFSC.


Giovanni Di Orio

Diogo Barata

André Rocha

José Barata

A Cloud-based Infrastructure to Support Manufacturing Resources Composition

Keywords: Cloud Manufacturing, Service-oriented Architecture, Service Composition, Device Profile for Web Services

Current development in emerging technologies, such as the Internet of Things (IoT), service-oriented and high-performance computing combined with the increasing advancement of manufacturing technologies and information systems, triggered a new manufacturing model. Modern industrial automation domain is characterized by heterogeneous equipment encompassing distinct functions, network interfaces and I/O specifications and controlled by distinct software/hardware platforms. To cope with such specificity, manufacturing enterprises are demanding for new service-oriented models that aimoc to abstract physical systems in terms of their functionalities/capabilities. In this scenario, Cloud Manufacturing (CMfg) arises as a new networked, service-oriented, customer centric and demand driven paradigm where manufacturing resources and capabilities are virtualized as services available in the cloud to users.

Introduction

Nowadays, manufacturing companies are more and more concerned with meeting the dynamic requirements imposed by the globalization [START_REF] Wu | Enhancing the Product Realization Process With Cloud-Based Design and Manufacturing Systems[END_REF]. Researchers and industry practitioners are striving for constant improvements and innovation in the business processes as a necessary condition for keeping the manufacturing companies competitive in market sharing [START_REF] De Souza | SOCRADES: a web service based shop floor integration infrastructure[END_REF]. In this scenario, the combination of new emerging technologies and paradigms such as IoT, Machine-to-machine (M2M), Cloudcomputing/manufacturing, service-oriented architecture (SOA), service-oriented computing (SOC) together with the wider dissemination of information technology (IT) are driving powerful and, above all, new business opportunities for manufacturing enterprises. As deeply exposed in [START_REF] Davidsen | IBM MQ: Integrated messaging to connect your enterprise[END_REF], for many years, business infrastructures has been mainly focused on connecting IT systems within the business environment. However, there are many businesses that are characterized by thousands of heterogeneous and geographically distributed devices deployed across the enterprise which are generating and consuming data and are isolated/separated from the enterprise IT backbone. This is particularly true in the manufacturing domain where the production processes are typically known for their plethora of heterogeneous equipment encompassing distinct functions, form factors, network interfaces and I/O specifications supported by different software and hardware platforms [START_REF] Candido | Enhancing device exchange agility in Service-oriented industrial automation[END_REF]. Today, mostly manufacturing enterprises have their operation technologies (OT) separated from the IT backbone infrastructure implying that the data generated by the field equipment is rarely used within business. As stated in [START_REF] Davidsen | IBM MQ: Integrated messaging to connect your enterprise[END_REF], the business leaders of today are becoming more and more conscious about the possibilities and opportunities of gaining access to this data. In particular, data can be used for identifying important production events, predicting market fluctuations, savings costs and/or improving the overall quality of the products while optimizing their production processes. Furthermore, the rapid convergence of OT and ITtriggered by the proliferation of plant-floor Ethernet, smart devices, sensors networks, local computing solutions and network technologies -is rapidly changing the way the data can be used by enabling from one side the transformation of information into insight and from the other side extending the reach of the business [3][5]. In this context, cloud-based systems enable manufacturing enterprises to improve data management even further and move performance and profitability to a level once thought impossible while accommodating operational spikes more easily, procuring manufacturing resources when needed -and only when needed, on demand and as shared resource [START_REF] Katzel | Power of the Cloud[END_REF].

Finally, the introduction of cloud-based system in the world of manufacturing production systems can bring into the game the necessary degree of dynamicity and capability to change to enable enterprises to survive in current dynamic environment, i.e. to be able to respond to competitive challenges and to sustain their competitive advantage in order to reach the success [START_REF] Jassbi | The Impact of Cloud Manufacturing on Supply Chain Agility[END_REF].

Contribution to Cloud-based Engineering Systems

The embedded technology progresses are promoting the transfer of more complex functionalities -currently hosted on powerful back end systems -in the world of manufacturing resources at shop floor level [START_REF] De Souza | SOCRADES: a web service based shop floor integration infrastructure[END_REF]. This technological revolution is radically changing the way production systems are designed and deployed, as well as, monitored and controlled. The dissemination of smart devices inside production processes confers new visibility on the production system while enabling for a more efficient and effective management of the operations. Taking advantage of the current technological trends, CMfg aims to integrate manufacturing resources into the cloud manufacturing services in order to expose them as a service to the users [START_REF] Zhang | Flexible management of resource service composition in cloud manufacturing[END_REF]. The binomial manufacturing resource/service will push the entire manufacturing enterprise visibility to another level while enabling the global optimization of the operation and processes of a production system and -at the same time -supporting its accommodation to the operational spike easily and with reduced impact on production. The present work implements a cloud-based infrastructure for achieving the resource/service value-added i.e. to facilitate the creation of services that are composition of currently available atomic services. In this context, manufacturing resource virtualization (i.e. formalization of resources capabilities into services accessible inside and outside the enterprise) and semantic representation/description are the pillars for achieving resource service composition (RSC). In conclusion, the present work aims to act at the manufacturing resource layer where physical resources and shop floor capabilities are going to be provided to the user as SaaS (Software as a Service) and/or IaaS (Infrastructure as a Service).

Supporting Concepts

Cloud Manufacturing

CMfg is a new paradigm where manufacturing resources and capabilities are virtualized as services available in the cloud to users. This concept was firstly proposed by [START_REF] Li | Cloud manufacturing: a new service-oriented networked manufacturing model[END_REF] with the intent to transform the manufacturing business into a new paradigm where manufacturing resources (i.e. physical devices, machines, products, processes, etc.) are transformed into cloud entities. This transformation is also called virtualization and enables for full sharing and circulation of virtualized resources that are capable of providing fundamental information about their own status. This information can potentially be used for local and global optimisation of the whole lifecycle of manufacturing. The current work addresses this theme by presenting a cloud-based infrastructure that enables manufacturing devices virtualization, deployment and selection by users for dynamically assembling them into a virtual manufacturing solution.

Service-Oriented Architecture (SOA)

SOA paradigm has emerged and rapidly grown as a standard solution for publishing and accessing information in an increasingly Internet-ubiquitous world. SOA defines an architectural model aiming to enhance efficiency, interoperability, agility and productivity of an enterprise by positioning services as the building blocks through which solution logic is represented in support of realization of strategic goals [START_REF] Erl | Service-Oriented Architecture: Concepts, Technology, and Design[END_REF].

The existence of Web Services technology has enabled and stimulated the implementation and development of SOAs. The application of SOA and Web Services in the context of manufacturing layer is still scarce, since a set of persisting technical challenges exists as pointed in [START_REF] Ribeiro | IT support of mechatronic networks: A brief survey[END_REF]. SOA and Web Service are considered promising techniques for integrating all the existing layers within a manufacturing enterprise spacing from business to the physical process. The capability of encapsulating functions and tools as services through standard interfaces and protocols, enables their access and usage by clients without the need to know and control their specific implementations. All these aspects promote the SOA paradigm and its most used implementing technology (Web Services) as the de-facto standards for fast, secure and, above all, easy integration of any new functionality within existing software solutions while electing them as one of the pillars for implementing the CMfg paradigm.

Service Composition

Services are the building block of a SOA, they provide simple interactions between client and server provider. However, sometimes atomic services need to be straightforwardly combined and/or assembled in order to generate more complex ones rising the service abstraction as referred by [START_REF] Kavantzas | Web services choreography description language version 1.0[END_REF]. In this scenario as argued in [START_REF] Hazenberg | Meta Products. Building the Internet of Things[END_REF], the term service composition is referred to the process of developing a composite service. Moreover, a composite service can be defined as the service that is obtained by the composition of the functionalities of several simplest services. Currently in the domain of SOA-based systems, two main approaches can be used for the service composition, namely [START_REF] Ashton | That 'internet of things' thing[END_REF]: orchestration and choreography.

Devices Profile for Web Services

The Device Profile for Web Services (DPWS) is a standard by the OASIS Web Services Discovery 1 and Web Services Devices Profile Technical Committee 2 . It defines two main elements: the device and the hosted services. The device element gathers all the meta-information about the attached physical device that is provided during the discovery activity. The hosted services gathers the main functionalities of the device. As explained in [START_REF] Candido | SOA at device level in the industrial domain: Assessment of OPC UA and DPWS specifications[END_REF], the application of Web Services at device level implies significant improvements in both operational and development aspects while unifying the ICT protocols of a manufacturing enterprise by providing a single stack to communicate from device-level to MES or ERP level over Web Service technology.

Cloud-based Infrastructure

The proposed infrastructure (see Fig. 1) is composed by three main components/resources, namely: the deployer, the cloud server manager and the client UI. These three components/resources are together responsible for: 1. virtualizing the manufacturing resources available in the physical system in terms of capabilities and functionalities and deploying such virtualized resources in the cloud (cloud entities); 2. Exposing the capabilities/functionalities of the cloud entities for enabling their invocation by external users that are accessing the cloud in order to execute certain tasks on the physical system. In the next sections, a detailed description of the developed components/resources is given.

Cloud Server Manager

Deployer

The deployer is the component/resource responsible to scan the network (i.e. the local network in which it is connected) searching for DPWS-enabled devices. Whenever a new device is encountered then the following tasks are executed:

• Virtualization: an abstract description will be associated to each device in order to transform the physical device into a cloud entity. • Deployment: make the virtualized devices available on the cloud for allowing the users to invoke the functionalities/services hosted by the device according to their needs. Taking into account these tasks, the architecture of Fig. 2 has been designed and implemented for the deployer. The proposed architecture is constituted by the following core task-oriented components:

• Device Explorer: it allows to search the network for available DPWSenabled device. • Device Virtualization: once a device is discovered this component extracts all the information from the device with the objective of creating a virtual entity with all the capabilities of the physical device.

• Device Repository: it is responsible to store all the information about the devices in the network and push it into the cloud. This information will be internally used by the Device Handler (whenever a new request comes from the cloud) and externally by the server component/resource. • Device Handler: it is responsible to handle requests asking for the execution of some functionality that come from the cloud.

Cloud Server Manager

The cloud server manager component/resource (see Fig. 3) is actually hosted into the Amazon Web Services3 (AWS) free tier. This cloud provide a virtualized resources that enables the accessibility of the cloud server manager component/resource from everywhere while allowing the configuration of the storage and processing power according to the user needs. The cloud server manager component/resource provide two Web Service endpoint to permit from one side the communication with the deployer and from the other side the communication the client. Moreover, it includes a local database that is used to store all the information about the devices connected to the deployer and their related functionalities. Furthermore, the database also stores all the requests performed by the client using the client UI and all the responses to these requests performed by the deployer. Thereby, the cloud server manager is also responsible to guarantee the communication between deployers and client UIs.

Client UI

The client UI (User Interface) is a simple graphical form that allows the users connected to the cloud to both select the capabilities/functionalities that they need and to graphically compose them to create complex tasks to execute on the physical process. Therefore, the client UI is logically composed by two main components, namely: a graphical control that allows the creation of the composition of capabilities/functionalities and an internal engine that translates the graphical representation of the composite tasks into requests to be sent to the cloud server manager.

Experimental Setup

As proof of concept, the MOFA kit by Staudinger GmbH has been used. This educational kit simulates a flexible manufacturing system and is composed by four machines, a buffer area, a crane robot, local transporters (conveyors or tables) and sensors to detect product positions. The original control equipment was replaced by Inico 4 S1000 components. The S1000 is a smart remote terminal unit (RTU) capable of real-time control, field data processing and web-based monitoring, programming and configuration tool. Moreover, it offers an embedded web server and implements a XML/SOAP interface based on DPWS standard. More details about the system used and its related monitoring and control solution can be found in [START_REF] Candido | Enhancing device exchange agility in Service-oriented industrial automation[END_REF].

The developed cloud-based infrastructure has been instantiated on the presented kit. The system configuration is presented in Fig. 4. The deployer is a local entity that will gather all the information about the physical devices (Inico S1000) connected and the capabilities/functionalities hosted. This information is passed to the cloud server manager that will expose it in order to be accessed and eventually requested by cloud users. Moreover, the cloud server manager also keep the information about the deployer localization. Finally, the cloud UI will provide a user interface where the user can pick the capabilities/functionalities he required and compose them to create a process plan. For the time being, the focus of the present work was to provide an infrastructure capable from one side to transform manufacturing resources into virtualized cloud entities deployed into the cloud and, from the other side, to expose the resources capabilities in order to enable external users to create simple processes by combining the available capabilities (using the provided graphical tool).

Conclusions and Future Works

The present infrastructure provides a cloud-based manufacturing system where available manufacturing resources are virtualized as cloud entities and which capabilities/functionalities are exposed for enabling the creation of processes by composition of such capabilities/functionalities. During this work some fundamental pillars of the CMfg paradigm have been approached, namely: virtualization access, deployment into cloud and service encapsulation of physical manufacturing resources. The present work proves the feasibility of the CMfg paradigm if it is supported by smart/intelligent devices. Moreover, the implemented infrastructure provides a normalized layer where the typical heterogeneity of the automation domain is hidden into a generic semantic representation. Furthermore, since the solution is supported by open web standards it leaves the doors open for the integration of more internet-based solution such as Self-Learning solutions [START_REF] Orio | Adapter module for self-learning production systems[END_REF]. However, some improvements opportunities can also be found. First of all the integration of a more sophisticated graphical tool for service composition is required (BPMN, BPEL, etc.). Secondly, the semantic representation can be significantly improved by introducing ontologies (OWL, OWL-S, etc.).

Fig. 1 .

 1 Fig. 1. Infrastructure Architecture

Fig. 2 .

 2 Fig. 2. Detail of the deployer architecture

Fig. 3 .

 3 Fig. 3. Detail of the cloud server manager component/resource

10 Fig. 4 .

 104 Fig. 4. Generic System configuration and workflow

http://aws.amazon.com/free/

http://www.inicotech.com/index.html

Acknowledgments. This research was partially developed under the"ProSEco" project, Grant agreement no: 609143", European Commission under the FP7 Programme.


Robson Marinho Da Silva

Edson H Watanabe
email: edsonh.watanabe@usp.br

Maurício F Blos

Fabrício Junqueira

Diolino J Santos Filho
email: diolinos@usp.br

Paulo E Miyagi
email: pemiyagi@usp.br

Modeling of Mechanisms for Reconfigurable and Distributed Manufacturing Control System

Keywords: reconfigurable control system, service-oriented architecture, holonic and multi-agent system, Petri net, cloud manufacturing system

This paper presents the modeling of fault diagnosis mechanisms extending a method to design reconfigurable and distributed manufacturing control system. The method combines different techniques: service-oriented architecture, holonic and multi-agent system, production flow schema and input-output place-transition Petri net. An application example demonstrates advantages of the proposal, such as at cloud-based engineering, reuse, implementation and reconfiguration flexibility.

Introduction

Reconfigurable control systems have been proposed to implement manufacturing systems with different strategies because its business processes can modify due new demands and in case of fault occurrence [START_REF] Da Silva | A method to design a manufacturing control system considering flexible reconfiguration[END_REF]. Furthermore, geographically distributed manufacturing subsystems need communicating and collaborating with each other in a dynamic environment. To propose a feasible solution to design Reconfigurable and Distributed Manufacturing Control System (RDMCS), characteristics of different techniques should be combined. In [START_REF] Da Silva | A method to design a manufacturing control system considering flexible reconfiguration[END_REF][START_REF] Da Silva | A service-oriented and holonic control architecture to the reconfiguration of dispersed manufacturing systems[END_REF], a method which associates top-down and bottom-up approaches through Petri Net (PN) [START_REF] Hasegawa | On resource arc for Petri net modelling of complex resource sharing system[END_REF][START_REF] Gomes | The input-output place-transition Petri net class and associated tools[END_REF] combining Service-Oriented Architecture (SOA) [START_REF] Candido | Applications of dynamic deployment of services in industrial automation[END_REF] and Holonic and Multi-Agent System (HMAS) [START_REF] Barbosa | Self-organized holonic manufacturing systems combining adaptation and performance optimization[END_REF] concepts to model RDMCS was presented. The HMAS concept facilitates the development and integration of distributed and heterogeneous systems and SOA paradigm allows considering interoperability with other manufacturing systems. This paper extends that method to model RDMCS focusing on modeling of fault diagnosis mechanisms and describes an application example.

Relationship to Cloud-based Solutions

In preview studies, the HMAS, SOA and PN concepts are combined to propose a method to design RDMCS [START_REF] Da Silva | A method to design a manufacturing control system considering flexible reconfiguration[END_REF][START_REF] Da Silva | A service-oriented and holonic control architecture to the reconfiguration of dispersed manufacturing systems[END_REF]. The basic assumption of this research is meeting the needs of goal-directed behavior in a distributed, dynamic and unpredictable environment, using patterns to facilitate the development of new models and a suitable semantic. The SOA paradigm is applied to define interfaces for communication in models based on HMAS concepts. The semantic definition of business processes is combined in a top-down and bottom-up approach based on PN to organize specifications, reuse and integrate social structure. The dynamic models are edited using a web tool for Input Output Place Transition (IOPT) PN [START_REF] Pereira | Web based IOPT Petri net editor with an extensible plugin architecture to support generic net operations[END_REF] which has modules for edition and simulation.

Therefore, according to cloud-based manufacturing statements [START_REF] Li | Cloud manufacturing: a new service-oriented networked manufacturing model[END_REF], this method is related to this vision due characteristics as: (i) avoiding repetition and overlapping tasks through reuse; (ii) facilitating the analysis and communication between different de sign staffs through PN models and their available web tools; (iii) allowing reconfiguration flexibility for both rational use of resources and larger safety to fault detection through proposed control mechanisms; (iv) considering human interaction in dynamic environment of productive processes; and (v) allowing design a large complex system through modular models and collaboration between distributed subsystem.

State of the Art and Related Works

An overview of methodologies, architectures and applications as well as trends and challenges in HMAS are presented in [START_REF] Leitão | Past, present, and future of industrial agent applications[END_REF]. Some architectures have a product-oriented vision and pay more attention to scalability and generic components of the system [START_REF] Hsieh | Collaborative composition of processes in holonic manufacturing systems[END_REF]. Others have a machine-oriented vision, paying more attention to an optimal utilization of the machine level than to the specific product performance [START_REF] Barbosa | Self-organized holonic manufacturing systems combining adaptation and performance optimization[END_REF]. However, in real applications much more complex and/or distributed subsystems may be combined into larger systems. On the other hand, SOA has revolutionized the distributed computing paradigm and made various kinds of inter-enterprise collaboration a reality [START_REF] Candido | Applications of dynamic deployment of services in industrial automation[END_REF]. Although SOA provides the framework for integrating cross-company services or technical interoperability, it does not address formal methods to ensure a systematic implementation of the design specifications [START_REF] Obitko | Applications of semantics in agent-based manufacturing system[END_REF].

According to [START_REF] Da Silva | A method to design a manufacturing control system considering flexible reconfiguration[END_REF][START_REF] Hasegawa | On resource arc for Petri net modelling of complex resource sharing system[END_REF], the PFS associated to ordinary PN is a solution for transformation of abstraction into application level, a gap into design of discrete event systems and specifically in RDMCS. Furthermore, tools for edition of IOPT PN [START_REF] Gomes | The input-output place-transition Petri net class and associated tools[END_REF][START_REF] Pereira | Web based IOPT Petri net editor with an extensible plugin architecture to support generic net operations[END_REF] can be used to model a control system with the additional advantage that the models can quasiautomatically be converted to programs for industrial controllers.

Modeling of Diagnosis Mechanism for RDMCS

Modeling of the holons starts using a derivation of channel/ agent PN, called Production Flow Schema (PFS) [START_REF] Hasegawa | On resource arc for Petri net modelling of complex resource sharing system[END_REF]. The PFS models represent modifications on the flow1 of items, activities and inter-activities. Then successive refinements are applied and the PFS model is more detailed at each level to generate the dynamic models in non-autonomous PN named IOPT [START_REF] Gomes | The input-output place-transition Petri net class and associated tools[END_REF]. This combined approach allows modeling system structures as well as system behaviors in a more simplified and transparent manner than ordinary Petri net representations.

The holons of this control architecture are: (i) product holon (PrH) which represents the raw material2, intermediate or final product. The set of PrHs form the production plan holarchy which represents a recipe of how to join raw material and intermediate products to obtain the final product; (ii) task holon (TH) which represents the business processes strategies to attend the product order. The TH also is conceived to request the reconfiguration strategies; (iii) supervisor holon (SuH) which contains all the knowledge to coordinate the operations, registering components and the messages exchange and providing services combined with other entities; and (iv) operational holon (OpH) which represents the resource such as, the equipments, the staff manager and operators. Therefore, PrH, TH and SuH form the holarchies to represent the set of operations of the high level control (enterprise and factory control level); and each OpH represents an atomic service which can be combined with atomic services by other holons forming holarchies to represent the supervisory and shop floor control level.

Modeling of PrHs and THs is made by activities of PFS and the internal workflow is modeled using IOPT. To model the workflow, a place represents a state while a transition represents an event or operation that conducts the flow from one state to another. Modeling of SuH involves the workflow of resources abilities, messages exchange between holons, supervision and command to implement actions related to fault treatment. The register of messages are represented though PFS distributors. OpHs represent resources (control object) and are directly modeled in IOPT. To model them with the requirement of fault tolerance, each control object in IOPT includes normal and fault states (represented by places) and conditions (represented by transitions) for the change of states; these conditions are represented by logical represented by guards. Thus, the OpHs models consider real component behavior including influence of the environment and their faults. The synchronization of the holons can be made with auxiliary places or through guard expression which contains command signals represent by input or output signal which in turn can be fired by input or output event.

Concerning fault diagnostic, the method presents a mechanism called diagnoser. To model the diagnoser, it is necessary to define observable and non-observable events [START_REF] Sampath | Failure diagnosis using discrete-event models[END_REF] that are related to fault specification. The steps for this modeling are: (i) diagnoser construction, initially considering normal operations only; (ii) linking the strategies implemented by means of transitions and guard to the possible observable and non-observable events that may occur from the initial state, and linking the states obtained according to input or output signal of actuators and sensors states; and (iii) linking the strategies implemented by means of transitions and guard to the events.

Modeling of Diagnosis Mechanism for RDMCS

The method is applied in a modular manufacturing system composed by WorkStations (WSs) described in Fig. 1. It is noteworthy that all the models are linked through of the PN elements representing real situations. Each WS controller is connected to internet allowing operators and clients interact with the system, that fits to the engineering cloud vision. The aim of this system is joining workpieces (wps). The devices, their control functions, commands and signals of actuation and detection of each WS are also identified. The identification is made according to specifications DIN/ISO 1219-2:1996-11 and IEC 61346-2:2000-12. For instance, in the nomenclature, 1S2: 1 = circuit number, S = device code, and 2 = device number.

handling (H-WS), assembling (A-WS) and robot (R-WS). The aim is joining workpieces (wps): a cylinder body (black [bcb], red [rcb] or aluminum [acb]), a piston (black [bp] or aluminum [ap]), a spring [s] and a cover [co], to be obtained the final products: (i) [bcb + ap + s + co]; (ii) [rcb + bp + s + co]; and (iii) [acb + bp + s + co].

This paper describes some D-WS models, illustrated on the right of Fig. 1

with its related sensors and actuators. The D-WS function is providing [bcb], [rcb] or [acb]

wps (on left at the bottom in Fig. 1) which are stored in the "stacking magazine" buffer. A double-acting piston pushes one wp out this buffer one at a time to the magazine. A swivel arm gets a wp in magazine via a suction gripper vacuum to move it to the transfer point of the Te-WS. Figure 4 presents some control objects models of D-WS (represented according to codes listed in Fig. 1) which put the "magazine" in front or back position. As above stated, the OpHs are directly modeled in IOPT considering faults states.

Each TH has diagnoser and its sub-diagnosers model which are modeled at a similar manner of the models in Fig. 5 where an example for D-WS (represented by TH-[Diagnostic for D-WS] and TH-[Diagnostic for 1ARetreating]) are illustrated. The models evolve together and according to the executed control strategy, the possible states are diagnosed (see highlighted blue dashed line). The transformation of PFS into IOPT model is not presented but is similar to example in Fig. 3. Commands signals (represented in Fig. 3) and the input and output signals of all control objects of D-WS (such as represented in Fig. 4) are linked in these models. 1. For instance, the "ArmToDWS" transition has associated the "G: 1B1=1 AND 1B2=0" that means "magazine is front position" and the "1B1 sensor" is sending signal "on". Thus, a token is fired for "ArmInDWS" place sending an output signal "3Y1="1 that in turn modifies the state of this solenoid. This IOPT has also input events: (i) "StartOn" of "StartD-WS" transitions to initiate the D-W S, (ii) "ResetOn" to reset the D-W S, and (iii) FaultTreatment to solve fault occurrence.

Conclusions and Further Work

This paper proposes the modeling of fault diagnosis mechanisms for Reconfigurable and Distributed Manufacturing Control System (RDMCS). These mechanisms extend a method which uses holonic and multi-agent system and service-oriented architecture concepts through a combined top-down and bottom-up approach based on Petri nets extensions: production flow schema and input output place transition. This approach allows modeling the complex system structures of RDMCS as well as system behaviors in a more simplified and transparent manner than ordinary Petri net representations; avoiding repetition and overlapping tasks through reuse; utilization of web tools for automatic generation of controller languages; collaboration among distributed subsystems; and cloud engineering facilitating the analysis and communication between different design staffs. Furthermore, the fault-tolerant mechanisms allow reconfiguration flexibility for larger safety and new production demands. An application example presents the developing and composition of the models highlighting the advantages of the proposal. Plans for further work include

Fig. 1 .

 1 Fig. 1. Modular manufacturing system composed by workstations (WSs): distributing (D-WS), testing (Te-WS), transporting (Tr-WS), handling (H-WS), assembling (A-WS) and robot (R-WS). The aim is joining workpieces (wps): a cylinder body (black [bcb], red [rcb] or aluminum [acb]), a piston (black [bp] or aluminum [ap]), a spring [s] and a cover [co], to be obtained the final products: (i) [bcb + ap + s + co]; (ii) [rcb + bp + s + co]; and (iii) [acb + bp + s + co].

Figure 2

 2 illustrates the PFS of production plan of the modular manufacturing system, refinement of intermediate product PrH-[rcb] and sub-refinement of TH-[request provides wp of D-WS to Te-WS] wich is detailed using IOPT model in Fig. 3. To clarify how communication/translation between different notations is assured, in this figure the related activities of the PFS in Fig. 2 are also illustrated inside the transitions and places of their IOPT model.

Fig. 2 .

 2 Fig. 2. PFS of workflow to obtain PrH-[rcb]. The services are represented by THs which are reuse in other products, such as [request to provide wp of D-W S to Te-WS] wich is used by all wps. The THs are: [request to provide wp of D-WS to Te-WS] in which D-WS through "swivel arm" takes a wp in its buffer out and put it in "buffer in" of Te-WS; [request rcb identification in Te-WS] in which Te-WSs checks color and height to identify wp; and [request sends rcb to Tr-WS] in which Te-WSs sends the identified wp to Tr-WS.

Fig. 3 .

 3 Fig. 3. IOPT for control of D-W S. Each transition has signals represented by "Guard (G)" which represent the equipments listed in Fig.1. For instance, the "ArmToDWS" transition has associated the "G: 1B1=1 AND 1B2=0" that means "magazine is front position" and the "1B1 sensor" is sending signal "on". Thus, a token is fired for "ArmInDWS" place sending an output signal "3Y1="1 that in turn modifies the state of this solenoid. This IOPT has also input events: (i) "StartOn" of "StartD-WS" transitions to initiate the D-W S, (ii) "ResetOn" to reset the D-W S, and (iii) FaultTreatment to solve fault occurrence.

Fig. 4 .

 4 Fig. 4. OpHs of D-W S modeled with normal and fault states (see codes in Fig. 1). For instance, OpH-[1Y1] has normal states "1Y1Off" to advance piston and "1Y1On" to retreat piston; and fault state "1Y1OffPiston" which maintaining the piston only in advanced state. The models are linked, such as OpH-[1Y1] is linked to OpH-[1A] through "Air1ARetreat" and "Air1AAdvanced" auxiliary places; and OpH-[1B1] and OpH-[1B2] is linked to OpH-[1Y1] and OpH-[1A] through input and output signals. The input events represent external changes, which can be a fault, such as "1Y1SFault".

Fig. 5 .

 5 Fig. 5. Diagnoser for D-W S linked to control strategy and signals of control objects. For instance (see highlighted dashed red line in both figures), "Piston Retreated" control strategy (place in Fig. 3) is linked to "1APistonRetreated" transition of diagnoser through the guard "G:PistonRetreated"; while the "InitDiagFor1A" transition in TH-[Diagnostic for 1ARetreating] has "G:Diagn1ARetreat" guard linking to TH-[Diagnostic for D-WS].

Terms associated to PN are in Arial font.

Terms associated to ontology are in Courier font.

R. M. Silva et al modeling of decision-making mechanism as well as other case studies.

Acknowledgments. The authors thank the partial financial support of the agencies: CNPq, CAPES and FAPESP.