Mohammad S Hashemian
email: m.hashemian@usask.ca

Kevin G Stanley

Nathaniel Osgood
email: osgood@cs.usask.ca

FLUNET: Automated Tracking of Contacts During Flu Season

Keywords: component; Sensor Networks, Contact Measurement, Delay Tolerant Network, Epidemiological Modeling I

By analyzing people's contact patterns over time, it is possible to build efficient delay tolerant networking (DTN) algorithms and derive important data for parameterizing and calibrating epidemiological models. Significant research has been performed in the automated acquisition of contact patterns using mobile devices such as Zigbee motes or Bluetooth-enabled cellular phones. However, the limited number of studies described to date do not capture the breadth of human experience or specifically include the acquisition of health related information. In this paper we present Flunet, a mobile contact-tracking network deployed in a Canadian university environment during flu season. Flunet tracked contact patterns of 36 participants and their proximity to 11 stationary nodes using MicaZ motes over a period of three months. Participants filled out weekly surveys on their state of health. This study is distinct from others because we incorporate health information and the impact of sub-zero temperatures on mobility patterns. This paper presents a preliminary analysis of the data set, primarily from a DTN perspective. We present fundamental attributes of the dataset, the efficiency of routing for single pass and flooding-based algorithms and a preliminary look at the relationship between network characteristics and health status.

INTRODUCTION

Automated contact tracing between human agents has direct applications to health and networking research. In networking research, contact traces can provide detailed maps of contact duration and inter-contact separation, which can be directly applied to the design and validation of delay tolerant network routing algorithms [START_REF] Jain | Routing in a delay tolerant network[END_REF]. In health research, contact patterns provide insight into critical factors underlying the spread of contagions, such as for sexually transmitted infections [START_REF] Jolly | Sexual Networks and Sexually Transmitted Infections: A Tale of Two Cities[END_REF] like HIV, and for airborne illnesses such as influenza or tuberculosis [START_REF] Al-Azem | Social network analysis in tuberculosis control among the Aboriginal population of Manitoba[END_REF]. The resulting network structure and dynamics can be used directly in agent-based and network models or can be processed to provide mixing matrices for population level models.

Several attempts have been made to derive contact patterns in human environments. Traditional contact tracing has relied on self-report, which is labor-intensive and timeconsuming [START_REF] Morris | International Union for the Scientific Study of Population. Network epidemiology: a handbook for survey design and data collection[END_REF]. Individuals subject to contact tracing are sometimes reluctant to report contacts for reasons of confidentiality. Even given a willingness to offer contact histories, individuals can have limited ability to recall the occurrence and timing of a contact, particularly for those of shorter duration. Partly as a result of these limitations, researchers working with self-report contact data have found that the incorporation of geographic place into social network analysis can offer significant epidemiological insight [START_REF] Al-Azem | Social network analysis in tuberculosis control among the Aboriginal population of Manitoba[END_REF].

Data sets, particularly those publicly available on the CRAWDAD repository, have been obtained from automated contact tracing, either directly using Wi-Fi, Bluetooth or Zigbee devices, or indirectly using time-stamped GPS coordinates. Example datasets include university students and staff [START_REF] Eagle | Reality mining: sensing complex social systems[END_REF], conference attendees [START_REF] Hui | Pockets Switched Networks and Human Mobility in Conference Environments[END_REF], university wireless usage [START_REF] Kotz | Analysis of a Campus-wide Wireless Network[END_REF], rollerblade tours [START_REF] Tournoux | The accordion phenomenon: Analysis, characterization, and impact on dtn routing[END_REF] and GPS traces at theme parks [START_REF] Lee | Slaw: A mobility model for human walks[END_REF]. Researchers have also attempted to use secondary measures to estimate contact patterns by inferring them from published or recorded schedules. Examples include student attendance in classes based on anonymized schedules [START_REF] Srinivasan | Analysis and Implications of Student Contact Patterns Derived from Campus Schedules[END_REF], vehicular networks such from bus schedules [START_REF] Lebrun | Bluetooth Content Distribution Stations on Public Transit[END_REF], or subway transit records [START_REF] Mcnamara | Media sharing based on collocation prediction in urban transport[END_REF].

While these datasets have enhanced our understanding of inter-human contact patterns and allowed the construction of more realistic synthetic algorithms for creating mobility models [START_REF] Lee | Slaw: A mobility model for human walks[END_REF], they still do not capture the breadth of human endeavor, or include medical data which would make the contact records more applicable to epidemiological modeling. To fill this gap we present Flunet, a contact tracing experiment conducted at the University of Saskatchewan.

Flunet tracked 36 participants and 11 fixed nodes over the course of three months during a Canadian winter. Participants provided health information through weekly surveys, which reported symptoms characteristic of influenza-like illnesses. Flunet is distinct from other data sources for the following reasons:  Medical Data: We collected health data from each of the participants in weekly surveys, allowing us to examine changes in contact dynamics for sick and healthy individuals. This paper presents a preliminary analysis of the dataset from both a DTN routing and epidemiological perspective. Section 2 describes our experimental setup. Section 3A presents a preliminary contact data analysis, section 3B verifies that classic DTN routing algorithms function as expected, and section 3C examines the health information provided in the participant surveys. A brief discussion is provided in section 4, future work in section 5 and conclusions in section 6.

II. EXPERIMENT SETUP

We were interested in the contacts between participants, the amount of time they spend at public places and how this might correlate with health conditions. To collect this data, we used contact tracing using MicaZ motes and weekly health surveys.

A. Contact Measurement

We selected 36 participants and asked them to carry a wireless module (MicaZ by Crossbow®) for 3 months, starting Nov. 9 th , 2009 and ending Feb. 9 th 2010. The participants were from 7 graduate labs in the Computer Science Department, departmental staff and undergraduate students. We also placed 11 stationary nodes in public places through the campus to measure the amount of time each person spent in specific public areas. Stationary locations were chosen by experimenters in high traffic, public locations.

Out of 11 stationary nodes, 3 were connected to a networked PC and acted as data sinks. The mobile nodes buffered the recorded contact information and offloaded the buffered data accumulated since the last offload time. To collect all the data at a central location, these base stations were connected to a central MySQL database which periodically uploaded collected data from the network to the main database. Contact with a base station triggered clock synchronization by setting the mobile node"s internal clock to the value received from the server. When two mobile nodes established a new contact, they synchronize their clocks to the node which had more recently visited the server. This algorithm caused the synchronized time to propagate through the network, mitigating clock drift in mobile nodes with infrequent server contact. Half of the mobile nodes were equipped with MTS310 sensor boards to periodically measure the temperature of their surroundings.

To probe adjacent nodes, each node broadcasts a "HELLO" message every 30 seconds (4-second interval for stationary nodes) with random drift of +/-2 s to prevent packet collision. If a node currently in contact failed to receive 4 consecutive HELLO messages from its partner, it labeled the partner as departed and adds a new contact record to its internal buffer. Each contact record includes: control flags, adjacent node ID, contact start time, contact end time, distance (discretized to "Close", "Medium", and "Far" based on received signal strength indicator (RSSI) value), and temperature (if applicable).

B. Surveys

Health information was collected via weekly surveys, which also requested participants estimate their total contact time with other members of the study to provide data on the difference between automated and self reported data collection. Participants were also asked to fill a one-time demographic/background survey which included questions on demographic variables, average amount of time spent with people and on campus, flu shot and H1N1 vaccination information, and their attitudes to the wireless module.

C. Maintaining the Integrity of the Specifications

The wireless module failures can be divided into two main categories: technical problems and human carelessness. The primary technical failure mode was a failure in the MicaZ receiver amplifier. The node could not receive HELLO packets from other nodes, but other nodes could record the faulty node"s existence. We suspect this problem was due to electrostatic discharge (ESD) damage to the receiving amplifier, due to the prototype design of MicaZ motes and the dry, cold conditions which dominate Saskatchewan winters. Thirty-two nodes experienced receiver failure during the study. Defective nodes were replaced after failure detection. We have mitigated the impact of this failure node by defining contact between a pair of nodes as the union of their contact records. Battery failure or displacement, sensor board displacement caused by shaking the module, and storage memory failure were other technical problems which occurred rarely during the study.

Human error was dominated by participants forgetting to carry the module, and forgetting to replace the battery periodically. When the participant forgot to carry the module, either the module was left on or off. In the former case the module recorded additional erroneous data and in the latter case we lost potential contact information. We tried to minimize compliance issues by sending reminders, mentioning in the weekly surveys, and directly reminding the more egregious offenders. During the study we observed that as time progresses, people cared less about the mote, and more often forgot to change the battery or to keep the device on. Voluntarily turning the node off, and forgetting to switch the device on after turning it off are other examples of human carelessness which rarely affected data collection.

D. Simulation

We can consider the dataset as a delay tolerant network (DTN) with semi-predictable connectivity. To analyze data from this point of view, we implemented a DTN in Network Simulator 3 (ns-3) using collected data from all 47 nodes (mobile and stationary). We applied two fundamental DTN routing algorithms on the simulated network: 1) Direct Message Passing to measure the upper bound of end-to-end delivery time and the lower bound of energy consumption, and 2) Epidemic Routing (Flooding) [START_REF] Vahdat | Epidemic Routing for Partially-Connected Ad Hoc Networks[END_REF] to measure the lower bound of delivery time and the upper bound of energy consumption.

In simulation, we discretized the time into 30-second time slots, and computed the connectivity pattern at each time slot using the dataset. The result for each node was imported as its contact pattern during the simulation. For both algorithms, we generated 12,500 packets in the network during the simulation, using a uniform random variable with 0.1% generation rate; therefore each node generated approximately 3 messages per day. Buffer Size was set to 1000 packets for all the experiments and no Packet TTL was specified. The packet size was fixed to 29 bytes (the default packet size in TOS). The Flooding algorithm did not employ any anti-packet methods [START_REF] Small | Resource and Performance Tradeoffs in Delay-Tolerant Wireless Networks[END_REF]. The carrier drops the packet as soon as delivery to the destination, but might receive the packet again in the future from other nodes.

III. RESULTS

Participants in this study consist of 75% males and 25% females, while 47% of them were in contact with other participants just on campus, and 53% were in contact off campus as well. 14% of the participants received a regular flu shot, and 39% of them had H1N1 vaccination. In addition, 83% of participants never smoke, while 6% smoke occasionally, and 11% smoke every day.

A. Dataset Characteristics

For the first set of results from the collected dataset, we focused on the data and its characteristics. The average duration of contacts at different hours of the day is interesting from DTN perspective. As shown in Fig. 1, contacts which happened in the morning between 7 AM to 9 AM are longer than other times of the day and the contact durations get shorter during afternoon. This can be explained by considering the effect of contacts between staff members during working hours at their offices, while the shorter contacts happen in afternoon between graduate students. During midnight to 6 AM, the number of contacts is much smaller and at shorter duration. Fig. 2 shows the complementary cumulative distribution function (CCDF) of contact duration. In addition to CCDF for all the collected data, we also removed contact durations more than 10 hours (0.03% of total reported contacts) from dataset because we assumed contact of this duration was due to motes abandoned near each other. Removing this section of data shows a considerable difference in the result plot. Actual data of this duration would have required that participants use the washroom together. Although the graph shows a small fluctuation between 300 and 400 minutes, it is difficult to separate the cause of the departure from the curve, because while it is likely due to abandoned nodes behaving like stationary nodes, it could also be caused by people changing their behavior when in continuous proximity. Fig. 3 shows contact duration and number of reported contacts for all mobile nodes during the experiment. This graph is plotted for "Close", "Medium", and "Total" reported contacts, based on the RSSI value. All of the contact proximities show the same trend in data: there are fewer nodes which have long contact duration and a large number of reported contacts, while there are many nodes with small to medium contact duration and fewer contact records.

Fig. 4 shows duration of reported contacts from two selected participants with all other nodes in network, sorted by duration of contact. Out of 36 participants, 3 of the plots were similar to "Sample 2", which is indicative of people with high centrality. Even though those people do not have extended contact durations with other people, they have seen all other participants at least once during the study. The plot for the other 33 people was similar to "Sample 1" which shows a power law behavior in their contact pattern [START_REF] Chaintreau | Pocket Switched Networks: Real-World Mobility and its Consequences for Opportunistic Forwarding[END_REF]. This is reasonable specifically for people who worked exclusively in a lab, as they spent a considerable amount of time close to their lab mates, but they did not have contacts with as many other people in the study.

B. DTN Results

The collected data can represent a DTN network with unpredictable and opportunistic connectivity [START_REF] Jain | Routing in a delay tolerant network[END_REF]. We used collected data for all 47 nodes to simulate a DTN network and implemented two basic routing algorithms: Direct Pass, and Flooding. Fig. 5 shows packet delivery ratio for both algorithms, with infinite TTL and buffer size equal to 1000 packets. With this buffer capacity, Direct Pass does not face buffer overflow, while in Flooding each node faces buffer overflow during the simulation. The buffer overflow ratio in flooding depends on the popularity of the node in the network. If the node has large number of contacts, it receives more packets and fills its buffer faster, and therefore potentially enters buffer overflow. If the node has fewer contacts, it receives fewer packets, and faces limited buffer overflow.

As it can be seen in Fig. 5, delivery ratio in Direct Pass constantly increases with time, while delivery ratio in Flooding does not have a notable change after two weeks, Figure 6. Delivery ratio at different hours of day where it reaches to a saturation point at less than 100% delivery. This non-ideal delivery is partly due to the packets which are generated in the nodes near the end of simulation, when insufficient time remains for delivery, and partially due to dropped packets caused by buffer overflow.

Because the dataset represents a human environment, we suspected that most of the message deliveries happened during the day. Fig. 6 validates this hypothesis. As shown in this figure, the number of messages delivered between Midnight and 6 AM is negligible. Packet delivery increases at 7 AM and reaches its peak at 2 PM, and it decreases during afternoon and evening. This peak can change in different human environments. In this study, majority of participants were students with their own work schedules, and the minority were staff with fixed working hours. However, these schedules tended to overlap in the afternoon, increasing the delivery probability. Fig. 7 shows histogram for end-to-end delivery time for the flooding and direct pass algorithms, discretized using 8 minute bins. As the histogram shows, a portion of generated packets can be delivered quickly, likely because the source and destination are in close proximity (e.g. the same laboratory) when the packet is generated, or one of the nodes is highly connected. The chance of delivering the packet decreases with time, and in Flooding histogram it approaches zero after two weeks. The number of delivered packets at each bin of the Direct Pass plot is smaller than its Flooding counterpart, but falls more gradually leaving a non-zero chance of delivery even after 2 weeks. This difference is as expected, because Flooding provides faster throughput than Direct Pass, but at the risk of buffer overflow.

C. Dataset and Health

We recorded information on participants" health during the study using weekly surveys. Compliance with the survey was sporadic, and we were forced to remove 5 participants due to insufficient data. Fig. 8 shows total number of sick days reported by each participant during the study. This data can be used to analyze the relation between peoples" contact patterns and their likelihood of being ill. We felt that participants were logically grouped into those who did not report a sick day, those that did reported less than 5 sick days, and those with greater than 5 sick days. While we recognize that processes of viral infection in humans are incompletely captured with aggregate statistics, we sought to determine if there was any correlation between the report of illness and participants" contact patterns in an attempt to validate the automated approach and to inform both future analysis of this data and the collection of new data. Descriptive statistics are shown in Table I.

While there were differences in contact duration for those that reported less than 5 days of illness and those with 5 or more days, there are no apparent differences between those who reported more than 5 sick days and those who reported none. While this may indicate some kind of correlation in our dataset, further research will be required to tease out the underlying causes, or eliminate the correlation. We suspect that some participants who reported no sick days did not fill out the surveys properly, underreporting their sickness causing a misclassification. However, these human factor issues can be difficult to isolate in data, and may require additional experiments to resolve. The trends noted are also influenced by important confounders, as older participants were more strongly represented in the more than 5 days category, and older participants in the study tended to be office staff, with consistent and prolonged contact patterns rather than students with more sporadic schedules.

To further visualize if sick days was correlated to network structure we plotted betweenness versus reported sick days as a scatter plot of participants in Fig. 9. Like the table, the results are ambiguous. More detailed epidemiological study will be required to further investigate this finding to determine if it is an effect or artifact.

We wanted to make a preliminary investigation of the utility of the dataset for agent-based epidemiological modeling. We assumed the virus spread from an infected node to an adjacent node, if two nodes stay in contact for at least 5 minutes with a "Close" categorization of RSSI value. This represents a 100% infection rate if the conditions are met, characteristic of a worst-case virulence human pathogen or a novel computer virus [START_REF] Su | A preliminary investigation of worm infections in a bluetooth environment[END_REF]. A packet representing the virus was introduced into the system, and its propagation monitored. Fig. 10 shows the result of 9500 trials at different simulation times. Some trials infected the whole community, but many infected a small fraction, if the primary infection point was poorly connected or the packet was generated near the end of simulation. The time required to infect a given percentage of the population is shown on the left axis, and the number of trials where that percentage was infected is shown on the right axis.

IV. DISCUSSION

We have presented a new dataset incorporating automated contact monitoring using MicaZ motes and health survey data. Our contact pattern measures and DTN performance are similar to those in previously reported analyses [START_REF] Eagle | Reality mining: sensing complex social systems[END_REF]. We had expected to see some distinctions between the contact patterns we observed, and the contact patterns observed in other studies due to the inclement weather typical of winters in Saskatchewan. However, our results are similar to those in studies like Reality Mining [START_REF] Eagle | Reality mining: sensing complex social systems[END_REF]. We expect that this similarity is due to work habits of North American Computer Science and Engineering graduate students, who spend the vast majority of their walking hours in indoor laboratory environments regardless of the weather. However, we are hopeful that the weather will aid in future analysis of the role of the stationary nodes because the winter weather strongly motivates students to utilize indoor routes between buildings, passing several nodes in public areas.

Although our preliminary analysis of the combined contact and medical data hinted at correlations, the simple analysis tools we employed were unable to unearth any conclusive findings. However, we have identified potential interactions, meriting additional research. The analysis of the data, and of confounders such as age, employment status and location caused us to note several potential pitfalls of directly mapping contact patterns to health data.

V. FUTURE WORK

This paper reports a preliminary analysis of our dataset, which itself results from a pilot exploration of the collection of simultaneous health and data. Our future work will focus on three areas: employing the data we have collected for the development and evaluation of DTN routing algorithms, analyzing our data from an epidemiological perspective to gain insight into the potential for automated data collection to contribute to infectious disease modeling, and as a starting point for longer and more detailed future studies employing more compelling, robust and comprehensive wireless sensor systems.

VI. CONCLUSION

We have presented the preliminary analysis of a new study conducted at the University of Saskatchewan covering 36 participants over a single flu season. Our data offers information both on contact patterns and analysis of participant health. We have found the general character of the data obtained in good agreement with similar studies from the point of view of the contact patterns themselves and the behavior of classic DTN routing algorithms using the aforementioned contact data. Our preliminary analysis of the health data suggests possible associations between contact rates and risk of infection, but significant additional work will be required to validate this finding with statistical rigor. We plan to follow this research with more analysis, new algorithms and additional studies.



  Duration: We have collected data for an entire flu season, encompassing over 1000 person-days of records, which is significantly more than other Zigbee-based experiments.  Temperature: The mean temperature during our experiment was -12º C [13]. Such low temperatures both contribute to mobility patterns and facilitate the spread of influenza.

Figure 1 .Figure 2 .Figure 3 .

 123 Figure 1. Average contact duration at different hours of the day

Figure 4 .Figure 5 .

 45 Figure 4. Contact duration between two sample participants and other nodes during the experiment

Figure 7 .

 7 Figure 7. End-to-End delivery time histogram for Direct Pass and Flooding algorithms

Figure 8 .Figure 9 .

 89 Figure 8. Total sick days for each participant

Figure 10 :

 10 Figure 10: Time required to infect a given percentage of the population (left) and percentage of trials where at least the given percentage of the population was infected (right)

TABLE I

 I

	.	DESCRIPTIVE STATISTICS ABOUT PARTICIPANTS WITH
	DIFFERENT SICK DAYS
			Never	< 5 Days	≥ 5 Days
	No. of People		12	9	10
	Mean Duration -Close (Hour)	1.42	1.08	1.42
	Mean Duration -Any (Hour)	3.23	2.52	3.19
	Mean Contacts		36.37	29.18	32.2
	Male/Female		75%/25%	89%/11%	60%/40%
	Flushot		0%	11%	10%
	Mean Age		29.8	28.7	31.2
	Std Dev Age		7.3	5.6	10.9

This work was partially sponsored by the National Science and Engineering Research Council (NSERC) of Canada, Discovery Grant and RTI programs.WiNMee 2010


The Breton Language : from Taboo to Recognition Introduction In 1993, while doing a study among students from the public high-school of Landerneau (Finistère) on individual and family practice of the Breton language, I observed the following reactions. When I presented the theme of my study, many students could not help laughing, others blushed and only a few of the "best" students sitting in the front row remained calm, raising their hand to ask for further technical details. This was exactly the behavior that my junior high-school classmates and I had adopted twenty years ago while attending a class on sexual education… This awakened my curiosity. Might there be a link between the repression of the Breton language and the repression of sexuality ? Later in the 1990's, as I was carrying out semi-directive interviews on Breton identity, this premonition seemed to be confirmed by the lapsus or the embarrassment expressed by several of the adults being questioned. Some of them seemed to harbor a secret and deep-seeded discomfort regarding issues of language and identity. These questions evoked something dirty and immoral, perhaps even dangerous, which should be hidden at all cost. Was this not a taboo, or the remains of a taboo ? This is the hypothesis I shall be presenting here. As far as the Breton language is concerned, there remains a taboo. A policy of recognition is needed for such a taboo to be lifted once and for all.

I. The Taboo

"Taboo" is a Polynesian word meaning a prohibition system of a sacred nature applied to something impure. If one admits that we are indeed dealing with a taboo, then the "sacred" might well be the French Republic "one and undivided", which supposedly liberates individuals from community oppression and gives them access to modernity and to universality. That which is Breton would then be considered "impure", such as "tradition", which inhibits individuals and binds them to their social condition and to their ancestral territory. Finally the prohibition system would be mainly, but not only, enforced by the school system. During the entire first half of the century schools did indeed punish children who spoke Breton, and went so far as to set up a system encouraging them to tell on each other, thus giving them a humiliating image of themselves. Yet in the broader sense, the prohibition system is not limited only to schools. From the 19th century until the second World War, images of backward Bretons and of an insignificant and ridiculous Brittany were spread across France by way of literature1 , popular writings, travel guides, comic books, songs, figurines, etc. The comic-book character, Becassine, a good-for-all maid "so stupid but so devoted"2 , is a perfect illustration of the widespread image of Brittany as folkloric and ridiculous. As a result of all this, many generations of Bretons have harbored feelings of shame, even perhaps of self-loathing, leading them to repress their singularity -most notably the pleasure of practicing their mother tongue -as if these were inadmissible practices. Today this shame and self-hatred are far from having disappeared. They are latent among many Bretons, and especially present among those who felt particularly stigmatized for their language or their accents. Such is the case of Aline (a farmer born in 1960) who compares the Breton language to an infirmity.

Aline : When I was little in school it was almost shameful to live in an environment like we had at home. I mean, to have parents who always spoke to us in Breton (…) We felt this to be a defect. And we had to hide it. So we considered it a bit like an abscess that we shouldn't show. (…) In my opinion, that's what it's like. Like someone who has a lump on his back. It's a handicap [START_REF] Coadic | L'Identité bretonne[END_REF] .

Helen, born in 1953 and married to a fisherman, describes how her accent represents the trauma of her life.

Helen : I'm a bit embarrassed because of my Breton accent. And ever since I was very small in school I was teased because of it. And that stayed with me until today. (…) I was embarrassed, really embarrassed, yes. (…) Even though at home I was forbidden to speak Breton. My parents always spoke Breton and forbade us to answer in Breton. Forbidden ! (…) My teachers often told me… Teasing me a little. They said : "But it's going to prevent you from finding work !" (…) Sometimes I'd say to myself : "Oh, if I could have lived somewhere else, if I could go away… " (…) I even cried about it for a while. Really. I was really affected ! (…) So when someone came to the house, like now, the way you just arrived, I would leave. I would go out of the house. I would go down to the river, over there 4 . Despite these terrible examples, it seems that today the taboo is progressively being lifted.

II. Recognition

The first sign that the taboo is being lifted is that for some time now one has been hearing much talk about the Breton language, especially in the press and in regional media. In fact so much so that a reporter at Ouest-France 1 wrote : "As far as the Breton language is concerned, the less it is spoken, the more it is talked about"… Indeed, the rates of practice of the Breton language continue to decrease : from 75 % at the beginning of the century, they have gone down to 17 % in the 1990's (approximately 240 000 speakers). The taboo is being lifted because the Breton language presently poses much less of a threat to French unity. Nowadays there are no more monolingual native speakers of Breton, and the rate of practice is so low that the few remaining people who still consider the language to be a threat to the Republic appear to be waging an out of date battle. Presently, 88 % of those living in lower-Brittany think it "necessary to preserve the Breton language" 2 . The ambiguity lies in this notion of "preservation". Do we want to preserve traces of our linguistic heritage in the same way that we preserve totems in museums ? Or do we want to lift the implicit prohibition which still weighs upon many minds and encourage both popular practice of the Breton language and its transmission through the generations ?

Lifting the taboo would mean bringing Bretons to sincerely believe that expressing oneself in Breton is not shameful, and consequently, that they can pass on their language to their children. Today we are still far from having reached such a point. While young militants have struggled for recognition of the Breton language, for visibility within French society, and for the language to be taught in schools and used in the media, in practice they have not been followed by native speakers of the language. Members of the latter group (retired people, farmers, factory workers and artisans), are mostly over fifty years old, relatively uneducated and settled in rural areas. Their practice of the Breton language is endogamous. In other words, they only speak Breton with people who belong to the same milieu as themselves (family members, friends, neighbors), or sometimes with individuals whose age, accent, demeanor and behavior indicate that they belong to a similar social group. When a young person speaks Breton it disturbs their image of the world. Except perhaps in recent years, ever since media coverage of the Diwan 3 schools has made them so popular. Nowadays, meeting a child who speaks Breton has entered the realm of possibilities for native speakers, but they still regard it as unreal and artificial. When this happens, the first thing they do is ask the parents whether the child attends a Diwan school. Then they attempt to exchange a few words in Breton with the child. But very rapidly they prefer to switch to French, considering that "they do not speak the same Breton" or that the child speaks "real Breton". As long as native speakers remain passive witnesses to the cultural revival, the rate of transmission of the 1 Ouest-France is a regional daily newspaper. It has the highest circulation of any French daily newspaper.

2 Results of a poll on the practice of Breton done on a sample of 2 500 people by the TMO Ouest Institute in March-April of 1997, for Le Télégramme and France 3 Ouest. Cf. Le Télégramme, April 12-13, 1997, last page. [START_REF] Coadic | L'Identité bretonne[END_REF] The Diwan schools are cooperative schools in the Breton language, created in 1977. Their popularity has led to the creation of public and private catholic schools offering bilingual classes. 6 000 children are presently enrolled in the bilingual sections. language will remain close to zero1 . For indeed, new speakers of Breton are too few to have any real impact on overall statistics. What can be done to reverse the tendency ? Here are a few suggestions.

First of all, it would be useful to admit that there is a taboo, or rather that it existed in the past and has left wounds which remain unhealed. In order to free native speakers from their embarrassment, one must act positively. Diwan has done this by creating a parallel school system. Any form of demand expressed through negative actions (violence, vandalism, etc.) is likely to "recharge" the taboo like a battery and to confront the native speakers once again with their negative identity.

Secondly, a policy of recognition should be developed. As Charles Taylor explains : "recognition is not simply a way of being polite to people, it is a vital human need"2 . If such a policy is developed by the Republican State, which is still considered in some ways as sacred, it will have immediate effects. However, it is obvious that the State will enforce such a policy only if it is firmly encouraged to do so. The Breton militants have been expressing such encouragement for years now. I wish however to point out that a policy of recognition should not come only from the State, but it should begin with the promoters of the Breton language themselves.

Recognition begins with humility. All those who have worked at collecting idioms will agree to the following : each conversation with a native speaker offers treasures of unknown expressions and words, colorful images and wonderful proverbs to those who knows how to listen. The wealth of those born with the Breton language is immeasurable. Yet it is not always easy for the young, urban, well-educated militants, often working in the academic and intellectual professions, to see that in the backwoods of the countryside, the most humble speakers remain the true kings of the Breton language. This, however, is the most important fact. Yet as long as native speakers do not value it and do not pass it on to their children, their wealth remains unproductive. This is why its value must be recognized.

In order to do this, one must first of all heighten the neo-Breton speakers' awareness of the fact that learning any language necessarily entails immersing oneself among native speakers. Too often do we forget this obvious fact. Yet the truth is that colloquial Breton is made up of a variety of dialects found mainly in rural areas. Moreover, as we mentioned earlier, it is not considered "natural" in such an environment to be speaking in Breton to a young person, especially if the youngster is from the city. In order to communicate with native speakers, young neo-Breton speakers will therefore have to overcome their elders' resistance. With this objective in mind, they will have to become familiar with those living in rural areas. This requires them to they learn three lessons : first, some notions of dialectology ; second, practical knowledge of a few of the social codes most in use among those living in a rural environment ; third, a capacity to reflect upon the meaning of their own practice and upon the kind of language they wish to use and to transmit. Once these basic lessons have been learned, different types of training may be proposed.

The fact that throughout Brittany one finds approximately 240 000 native speakers should make it possible to set up an organized network of internships among rural families, for the benefit of those adults who wish to learn the language. The impact of such a network would be great. It would improve the quality of the language learned by adults, while at the same time having a psychological impact upon the native speakers whose language would thus be given more recognition. This might eventually bring them to develop a desire to read and write in their language.

Indeed, almost all native speakers of Breton are illiterate in their native language. Teaching them how to read and write should be a priority. Yet, strangely enough, there are practically no such training for those whose mother tongue is Breton, even though when it is offered reactions are quite favorable.

In addition to this, a simple policy aimed at helping children learn good quality Breton could be set up in schools. Each child would be required to meet regularly with an "elderly friend" living in his or her neighborhood. Elderly people would no doubt be very happy to make such a contribution and to receive the visit of a child to whom they could pass on part of their linguistic heritage.

In order to carry out the above mentioned steps it would be very useful to develop teaching materials which combine the vernacular language and the more classical written language. Such efforts have already been made, and should be encouraged. Finally, one might create opportunities for Breton-speakers from the city and Bretonspeakers from the countryside to meet with each other, by, for example, inviting native speakers to visit schools or language classes, or by sending schoolchildren and students to visit the homes of native-speakers. The ideal solution would be to set up several permanent meeting centers, offering various types of cultural activities, likely to attract both types of speakers and whose function would be to encourage regular exchanges.

Conclusion

Is the Breton language's present popularity merely a mean for cultural distraction or is it a sign of reproduction ? If the first hypothesis is true, rates of transmission among locals are likely to remain very low and the practice of Breton limited to a happy few. In this case, the language would likely become the cultural capital of a small community, similar to other present day minority groups who are sometimes at risk of living in a closed environment. The attempts at revival we are witnessing today might, as always in cases of endogamy, produce a strange fruit : a half-baked language made up of Breton or neo-Breton words and of French syntax and pronunciation.

In order for the natural reproduction of a living species to take place, two different partners must come together. As far as the Breton language is concerned, these two partners are the native speakers and the neo-Breton speakers.

For instance : Balzac, Les Chouans, Victor Hugo, Quatrevingt-treize and Flaubert, Par les champs et par les grèves.

Ory, Pascal, « La Bretagne dans la littérature enfantine et la bande dessinée », in Balcou et Le Gallo (ed.), Histoire littéraire et culturelle de la Bretagne, Paris-Genève, Champion-Slatkine, 1987, t.

3, p. 373.

Laurent, Loeiz, « La connaissance du breton », Octant, n° 56-57, 1993, pp. 7-12.

Taylor, Charles, Multiculturalisme. Différence et démocratie, Paris, Flammarion, 1994, p. 42.


Zhe Zhou

Mark Claypool
email: claypool@cs.wpi.edu

Robert Kinicki

Analysis of an IEEE 802.11 Network Activity during a Small Workshop

Understanding current performance and usage of IEEE 802.11 networks is valuable for effectively managing and deploying wireless networks in the future. This paper analyzes a wireless trace from NetGames'08 and compares the results with previous research. The analysis indicates increasing dominance of Web traffic, emerging p2p applications consuming significant uplink capacities, and differences in the overall volume and traffic patterns from prior wireless Internet traffic measurements. The workshop schedule greatly influences network usage with the number of people in the room significantly affecting the received signal strength.

I. INTRODUCTION

Advances in WiFi technologies, especially IEEE 802.11a/b/g, coupled with decreasing costs have made wireless Internet access more common than ever. Business and academic institutions often provide ubiquitous wireless access, while home users frequently deploy wireless to conveniently handle multiple networked devices. Currently, many professional gatherings, such as conferences and workshops, provide participants with free wireless Internet access. Understanding trends in usage and current 802.11 performance is valuable for effective management and planned deployment of future wireless local area networks (WLANs).

One of the earliest known studies of a public WLAN analyzed user behavior in the wireless network deployed at Stanford [START_REF] Tang | Analysis of a Local-Area Wireless Network[END_REF]. Similarly, other studies have analyzed wireless networks but without corresponding application level analysis [START_REF] Amit | Understanding Congestion in IEEE 802.11b Wireless Networks[END_REF]- [START_REF] Rodrig | Measbased Characterization of 802.11 in a Hotspot Setting[END_REF]. Known works that have analyzed both wireless layer and application layer characteristics include an in-depth look at wireless traffic from the 2001 SIGCOMM conference [START_REF] Balachandran | Characterizing User Behavior and Network Performance in a Public Wireless LAN[END_REF] and multi-layer network analysis of the WLAN at the University of Dartmouth [START_REF] Henderson | The Changing Usage of a Mature Campus-wide Wireless Network[END_REF]. While these works have been valuable for better understanding WLAN usage, the former case is now 8 years old and both cases are from considerably larger forums that are not representative of the many small to medium conference gatherings.

This paper examines wireless, network and application level characteristics for a ACM workshop. The merits of this trace are: 1) a, b and g: to the best of our knowledge, this is the first analysis of a WLAN with simultaneous IEEE 802.11 a/b/g traffic; 2) 2008 data: the recency of the data, from late 2008, has merit since IEEE 802.11 technologies and Internet applications are constantly evolving; and 3) size: the size of the forum, about 30-40 participants, represents a workshop or small conference size that is quite common, but not wellstudied.

The 7th annual workshop on Network and Systems Support for Games (NetGames'08), 1 was a single-track, ACMsponsored workshop that had about 35 participants, with about 20 of them bringing their laptops and using the provided wireless network. Wireless access to the Internet was provided throughout the workshop sessions, including outside the room during breaks. Over 2.7 GBytes of traffic traces were gathered by the wireless infrastructure and archived for post-processing and analysis when the workshop completed. The analysis of these traces seeks to answer the following questions:

1. What is the classification, frequency and duration of wireless network use during the workshop? Answer: both IEEE 802.11a and 802.11g are heavily used by two-thirds of the participants. The average aggregate bandwidth usage was only 700 Kbps, but the standard deviation was 1.36 Mbps with a maximum of 8.73 Mbps.

What applications are used by workshop participants?

Answer: despite the plethora of applications available to users, traffic is increasingly dominated by the Web,2 while only about one-third of the participants use email services. 3 The clear preference for Web applications may be attributed to their client-side simplicity and ability to pass through firewalls.

3.

What factors impact network use? Answer: external organization factors, such as session breaks, have a profound impact on traffic patterns. Wireless signal strengths have a negative correlation with the number of users in the room.

The rest of this paper is organized as follows: Section II presents related work; Section III describes the methodology to gather and analyze the wireless traces; Section IV analyzes traffic on the physical, link, transport, application and client layers; and Section V summarizes our work.

II. RELATED WORK

In one of the earliest known studies of public WLAN use, Tang and Baker used tcpdump and SNMP to trace 74 users in the Stanford Computer Science Department for 12 weeks [START_REF] Tang | Analysis of a Local-Area Wireless Network[END_REF]. They analyzed user behavior of the network, overall network traffic and load characteristics. Later work includes trace analysis of the Dartmouth campus wireless network conducted by Henderson et al. [START_REF] Henderson | The Changing Usage of a Mature Campus-wide Wireless Network[END_REF] They characterized user behavior in terms of application use and found residential traffic dominated all other traffic especially in residences with newer students. They also showed that some wireless cards roamed excessively, being unable to settle down with one AP. They compared traces gathered in 2001 and 2003/4 and found trends including an increase in the user population and roaming.

Balachandran et al. studied the SIGCOMM'01 wireless network traffic [START_REF] Balachandran | Characterizing User Behavior and Network Performance in a Public Wireless LAN[END_REF]. Their work resembles our work in that their trace was collected over an academic conference with similar analysis, but differs in the scale of the conference with SIGCOMM being much larger than NetGames. A comparison for all these three works in relation to ours is presented in Section IV.

Saroiu and Gummadi characterized Web and p2p traffic seen at the border routers on the campus of the University of Washington [START_REF] Saroiu | Measuring and Analyzing the Characteristics of Napster and Gnutella Hosts[END_REF]. They observed that outbound p2p traffic dominated. However, in the study at Dartmouth [START_REF] Henderson | The Changing Usage of a Mature Campus-wide Wireless Network[END_REF], the dominance of inbound traffic was observed. Our study also notices a dominance of inbound traffic, but a noticeable presence of outbound traffic.

Both [START_REF] Balachandran | Characterizing User Behavior and Network Performance in a Public Wireless LAN[END_REF] and [START_REF] Henderson | The Changing Usage of a Mature Campus-wide Wireless Network[END_REF] observed the dominance of Web traffic, while in the newer trace of [START_REF] Henderson | The Changing Usage of a Mature Campus-wide Wireless Network[END_REF] the dominance of Web was diminishing. Our studies reveals that Web traffic continues to dominate and has, in fact, expanded in its prevalence.

Other studies of wireless traces focused more on network performance than on user behavior. Jardosh et al. analyzed traces collected at the 62nd IETF meeting over two days in 2005 [START_REF] Amit | Understanding Congestion in IEEE 802.11b Wireless Networks[END_REF]. They found wireless rate adaptation rarely used the 2 Mbps and 5.5 Mbps data rates, and that these lower rates were detrimental to network performance during congestion. Rodrig et al. analyzed SIGCOMM'04 wireless traces and they concluded that 802.11 overhead was high and retransmissions are common [START_REF] Rodrig | Measbased Characterization of 802.11 in a Hotspot Setting[END_REF]. Also, clients switched data rates more often than not, and most transmission times were spent sending at 1 Mbps.

All studies aforementioned either examined IEEE 802.11b networks or investigated 802.11g networks but only with 802.11b rates, while our paper looks at a WLAN that supports both 802.11b/g and 802.11a.

III. METHODOLOGY

A. Network Configuration

NetGames'08 was held in Salisbury Labs, a multi-story, brick and steel building at Worcester Polytechnic Institute in which an IEEE 802.11a/b/g network is deployed for campus use. Figure 1 illustrates the floor plan showing the locations of wireless access points (APs) and the conference room where the workshop was held.

Each individual AP simultaneously supports 802.11a and 802.11b/g. Clients negotiate with the AP to determine which mode (a, b or g) to use based on client support, signal strength, and the AP load. The APs dynamically load balance across all available 802.11a and 802.11b/g channels. The subnet of APs

B. Trace Collection

Figure 2 shows the trace collection setup. Transmitted and received wireless frames for the four APs in the subnet are forwarded via Ethernet to a monitor. Each frame collected by the AP contains link, network, transport, and application layer data encapsulated within the TaZman Sniffer Protocol (TZP) before being sent to the monitor in a UDP packet. The monitor stores pcap traffic it collects to local files for later offline analysis. Additionally, a laptop with a 802.11a/b/g compatible wireless adapter placed inside the conference room measured the received signal strength (RSSI) using a Windows Management Instrumentation script that queried the windows registry once every second.

The two-day workshop was held in October 2008 during a WPI term break when most of the students were away from campus. The four APs collected 20 million frames over the two day workshop. Since the first day had atypical network behavior in that wireless was not immediately available (owing to some difficulties encountered by the WPI network providers) and because users were not familiar with the environment (e.g., the location of power outlets), this study focuses on the second day's traffic. Table I provides an overview of the trace statistics.

IV. ANALYSIS

Our analysis proceeds in a bottom-up fashion based on network layers: Section IV-A analyzes physical layer features, including channel information and RSSI variation with respect to the traffic (people and network) in the room; Sections IV-B and IV-C analyze link and transport layer traffic, respectively; Section IV-D shows the prominent applications used along with their inbound/outbound traffic rates during the day; and Section IV-E examines individual client activities and traffic.

A. Physical Layer

This section examines the physical layer aspect of the traffic traces including received signal strength indicator (RSSI) measurements obtained from the laptop in the conference room.

While control traffic, such as broadcast beacons, was sent on additional channels (2, 7, 48, 165, etc.), all observed traffic (shown in Table II) sent by the NetGames'08 participants appeared on channels 11 (IEEE 802.11b/g) and 60 (IEEE 802.11a). Generally, 802.11a provides data rates equivalent to 802.11g when wireless clients are close to an AP where the signal strength is good. Since the NetGames'08 participants were in a small conference room with the AP centrally located in the ceiling, the resultant strong signal strengths yielded more traffic on channel 60 than on channel 11. Our assumption is that when client laptops support 802.11a and have a good RSSI, 802.11a is employed to load balance the 802.11g channels. As a measure of link quality, the RSSI assists in AP association decisions and can be used in dynamic rate adaptation. RSSI values below a threshold are strong indicators of likely connection losses that interrupt or break applications relying on persistent connections. In this paper, the sniffing laptop was set to monitor channel 60 and recorded its RSSI value every second.

Figure 3 graphs RSSI over time in relation to background throughput on channel 60. RSSI varies considerably with little visual correlation to background traffic spikes. When the room is occupied, the RSSI fluctuates in a range of -50 dBm to -35 dBm, even though the AP is in the ceiling directly overhead. However, when the room empties shortly after noon for a lunch break, there is a marked decrease in the RSSI variance. Note that -50 dBm to -35 dBm typically provides for good signal strength and participants in the room may see little variation in their application's performance. While the graph shows RSSI does not correlate directly with the traffic, it indicates that RSSI is affected by the people (and their laptops) in the room using the network.

B. Link Layer

Since channel 60 traffic resembles channel 11 traffic, for brevity, only channel 11 frames are analyzed in Table III. Most frames are data and acknowledgments. RTS is little used and most CTS frames are mixed 802.11b/g CTS-to-self frames.

Figure 4 provides the cumulative distribution function (CDF) for the data and non-data frames for both the heavily used channels, 11 and 60. While dominated by small ack and CTS frames, the non-data frame distribution includes the larger beacon frames. The figure shows 802.11a data frames to be, in general, larger than 802.11b/g data frames with approximately 10% more channel 60 data frames at the 1500-byte Ethernet

C. Transport Layer

Transport layer (and some IP layer) data is presented in Table IV. Unlike in other conference measurement studies such as [START_REF] Balachandran | Characterizing User Behavior and Network Performance in a Public Wireless LAN[END_REF] where relatively low UDP usage is reported, 20% of the NetGames'08 traffic is UDP. Since smart p2p applications such as Skype will use UDP when participating p2p nodes are not behind NATed firewalls (such as at this workshop), the analysis in Section IV-D suggests this increased UDP component is most likely due to the one p2p file sharing application.

D. Application Layer

Applications are classified according the IANA port numbers list, understanding that the list suggests, but does not force, port number assignments. Thus, user applications are determined mostly from well-known, server-side port numbers except for a single p2p file sharing application (uTorrent), which is identified by client-side port numbers. Table V provides the top 10 applications classified by port number with all remaining applications lumped into the 'other' bin. Clearly, this data confirms that Web traffic (http and https) dominate, contributing 73% of the traffic volume. While email (pop3 and imap4), nat-t and openvpn traffic are not surprising members of the top 10 list, the p2p contribution sticks out as being different for NetGames'08 than for previous forums. Table VI compares the top five application types seen in NetGames'08 (where "session" is ssh, vpn and rdp combined) against those applications identified in three earlier An important caveat here is that the applications in Table VI, defined by port number, are not likely to provide one-to-one mapping to actual user activities. For instance, port 80 is used to access email (via Web mail) as well as traditional Web browsing services. However, from another perspective, the proliferation of Web-based applications expands Web traffic to include such user activities as email, games, chat, video and live radio. For example, in our trace the increasing proportion of Web traffic is coupled with diminishing existence of email traffic. 5 While Internet use has diversified [START_REF] Henderson | The Changing Usage of a Mature Campus-wide Wireless Network[END_REF], the dominance of traffic labeled as "Web traffic" (http/https) has increased rather than decreased.

The presence of p2p traffic in the NetGames trace testifies to the popularity of such applications even within an academic conference setting. However, the fact that the p2p traffic is generated by a single client using uTorrent restricts our ability to draw general conclusions about current p2p impact. Yet, it is noteworthy that the lone p2p client in the NetGames trace contributes over 12% of the total traffic volume in an academic conference setting where the typical "leisure" applications supported by p2p are not expected to be a large part of the daytime traffic.

Figure 5 shows inbound and outbound traffic for the major applications. All the applications have more downstream traffic than upstream except for the p2p application where the total upstream traffic exceeds the upstream traffic of all other applications combined. Measured application statistics are provided in Figure 6, showing the standard deviation of the mean and the coefficient of variation (CoV) in the overall traffic rate for each application type. To better understand application usage during the conference, Figure 7 aligns the throughput of the major applications over time. Web traffic shows a wide range in load, with periods of low, medium and high throughput easily identifiable. Email throughput remains fairly low throughout the day, except for the throughput bursts in the early morning and late afternoon. The continuous, horizontal band at about 300 Kbps indicates periodic email synchronization. Ssh activities are more scattered and have high variability. While p2p throughput varies, it stays within the 0 to 400 Kbps region. Vpn, nat-t and rdp patterns are tied to the handful of individuals that used these applications.

The organization of the workshop added external factors that affect network use. The second day schedule for the workshop was as follows:

9:00 -10:30 Morning session (3 speakers) 10:30 -11:00 Break 11:00 -12:00 Panel session 12:00 -13:30 Lunch break 13:30 -15:00 Afternoon session (3 speakers) The morning session has the most variation overall. In the first part of the morning there was high nat-t traffic, and then at about 9:20am there were a jump of network activities for Web, email and nat-t, showing a coordinated pattern. When the morning break started (indicated by the left-most vertical line), the overall throughput of Web and p2p dropped, indicating people left the room. After about 10 minutes, people started returning to the room and there was an increase in Web, vpn, nat-t, and p2p throughput. When the panel started at 11:00am, Web traffic diminished and then went up (but with fewer users, as shown in Figure 8), while vpn and nat-t went to their normal low. Most prominently, the lunch break at 12:00 provided a quiet period, with some traffic at the beginning and end. The small amount of periodic Web traffic seen during the lunch break was due to the authentication of clients to the WPI Web server, needed to retain guest access to the wireless network. In the afternoon session, nat-t, and vpn disappeared completely. Web traffic stayed comparably low to the morning except for a burst in the late afternoon. Email also had a burst in the late afternoon, possibly indicating some end-of-day checking and sending of email before the workshop ended and the participants dispersed. P2p's throughput covers large areas of the graph, except for during the breaks, but has a small Coefficient of Variation (CoV). Ssh has the largest CoV, followed by vpn and email, indicating more bursty traffic.

E. Clients

Client activeness provides another view into how participants used the wireless network. In particular, this section seeks an understanding of the number of clients that simultaneously used the wireless network during the workshop and how many clients used the popular applications of Web and email. A client is marked as active if it sends/receives a frame at least once a minute and active for Web/email if it sends/receives a packet to/from a Web/email port once a minute.

Figure 8 shows the number of active clients over time for Web, email, and all other activities. At any given time, there are fewer than 18 clients connected, about half of the 35 workshop participants. During lunch, the number of active clients drops to fewer than 4, and these clients generate periodic traffic that is likely an automatic refresh of Web pages or email. The number of active email clients is consistently from 1 to a maximum of 7. Figure 10 shows the complementary CDF (CCDF) of the inbound and outbound traffic of all clients. The trendlines are not heavy-tailed.

V. CONCLUSION

Growth in wireless networks has led to the increasing availability of wireless Internet access in forums such as workshops and conferences. Analysis of wireless traces can help better understand network use. While previous work is either outdated or from large-scale wireless local area networks, this paper analyzes wireless Internet access from NetGames'08, a small-scale, single-track ACM workshop typical of many small-group gatherings. Our analysis examines the physical, link, transport, application and client layers. The findings show: Web remains and is perhaps increasing as the dominant application; p2p and vpn are emerging in use; wireless use is directly influenced by workshop organization; and people using wireless in the vicinity of the wireless access point significantly affect received signal strength. Researchers can use this analysis and these traces to build synthetic workloads for experiments or plan for improved deployment of wireless networks at future forums.

Fig. 1 .

 1 Fig. 1. Floor plan of NetGames'08 Forum

Fig. 4 .

 4 Fig. 3. RSSI Variation over Time

Fig. 5 .Fig. 6 .

 56 Fig. 5. Inbound & Outbound Traffic

Fig. 7 .

 7 Fig. 7. Application Throughput over Time

Fig. 8 .

 8 Fig. 8. Clients over Time Figure 9 plots the inbound and outbound traffic volume for each client (identified by their MAC addresses), sorted from highest volume to lowest. Most clients used more downlink capacity, with the exception of client e1:9c that used more uplink capacity when running a p2p file sharing application.Figure10shows the complementary CDF (CCDF) of the inbound and outbound traffic of all clients. The trendlines are not heavy-tailed.

Fig. 10 .

 10 Fig. 9. Inbound & Outbound

http://netgames2008.cs.wpi.edu/

Ports 80 and 443.

Ports 993 and 995.WiNMee 2010

For details of the WPI network infrastructure see http://www.wpi.edu/Academics/CCC/Netops/Network/

The Dartmouth trace fraction of email traffic is

6.4%.