Pocket switched networks and human mobility in conference environments

Hui, Pan; Chaintreau, Augustin; Scott, James R.; Gass, Richard; Crowcroft, Jon; Diot, Christophe

doi:10.1145/1080139.1080142

Cited by 785 publications

(622 citation statements)

References 8 publications

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“…IBM used RFIDs to track sessions and meal attendance at a conference [17]. Bluetoothenabled mobiles were also used to track networking of conference attendees [10] and for sensing organisational aspects [8]. Networks from blutoothed mobiles were also studied for characterising some statistical properties of human mobility and contact [14].…”

Section: Related Workmentioning

confidence: 99%

Social Dynamics in Conferences: Analyses of Data from the Live Social Semantics Application

Barrat

Cattuto

Szomszor³

et al. 2010

Lecture Notes in Computer Science

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Abstract. Popularity and spread of online social networking in recent years has given a great momentum to the study of dynamics and patterns of social interactions. However, these studies have often been confined to the online world, neglecting its interdependencies with the offline world. This is mainly due to the lack of real data that spans across this divide. The Live Social Semantics application is a novel platform that dissolves this divide, by collecting and integrating data about people from (a) their online social networks and tagging activities from popular social networking sites, (b) their publications and co-authorship networks from semantic repositories, and (c) their real-world face-to-face contacts with other attendees collected via a network of wearable active sensors. This paper investigates the data collected by this application during its deployment at three major conferences, where it was used by more than 400 people. Our analyses show the robustness of the patterns of contacts at various conferences, and the influence of various personal properties (e.g. seniority, conference attendance) on social networking patterns.

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Section: Related Workmentioning

confidence: 99%

Social Dynamics in Conferences: Analyses of Data from the Live Social Semantics Application

Barrat

Cattuto

Szomszor³

et al. 2010

Lecture Notes in Computer Science

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“…Within any network enabled device (e.g. router, switch, network element or terminal such as a computer or smartphone) it is the packet processing subsystem that manages the traversal of the multi-layered network or protocol stack from the lower, physical and network layers all the way through to the application layer The internetworking protocol developed to support the network, called ARPA net, [6] was called TCP or Transmission Control Program. As research and development progressed and the size of the network grew, it was determined that the internetworking design that was being used was becoming unwieldy and it did not exactly follow the layered approach of the OSI Model.…”

Section: Packet Statistical Reportmentioning

confidence: 99%

Anomaly Based Detection of Violations in Web Applications

2017

IJAERD

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“…Random waypoint [12], random walk [20], and Gauss-Markov [2] mobility models are all examples of generic mobility models. Realistic mobility models [11,14] describe real scenarios and capture real movement characteristics. In this paper, we propose a new mobility model for PNs.…”

Section: Introductionmentioning

confidence: 99%

“…Currently in the literature, it is assumed that a single user or vehicle carries one mobile device. Some mobility scenarios of ad hoc networks have been studied, where persons (each carrying a mobile device) move in an area [11,14]. However, in our work, many embedded devices move together with the user or vehicle.…”

Section: Introductionmentioning

confidence: 99%

Mobility Modeling for Personal Networks

Prasad

Niemegeers

2009

Wireless Pers Commun

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A Personal Network (PN) is a user-centric design interconnecting numerous devices belonging to a user in different geographic locations, such as home, office, car, etc., to form a single global network to offer fully personalized services. In PNs devices of the user move in different groups, where these groups merge and split. In this paper, we design and simulate a PN Mobility Model (PNMM) to capture the characteristics of movements of devices in PNs. We propose a simple stability evaluation method for group mobility models and apply the method to PNMM. Through the stability evaluation, we find that PNMM possesses long-term steady state behavior. Moreover, for the evaluation of mobility models, some evaluation methods have been proposed, which include non-homogenous node mobility, relative node mobility in a group, and dynamics of group merging and splitting. Analysis shows that PNMM is better than other models to represent the PN mobility properties. In addition, the impact of PNMM on the performance of a PN Clustering Protocol (PNCP) has been studied. Simulation results provide insights into the performance of PNCP, and provide guidelines for future design of PN clustering. PNMM can be easily applied to any Personal Area Network or Body Area Network with slight modifications.

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Pocket switched networks and human mobility in conference environments

Cited by 785 publications

References 8 publications

Social Dynamics in Conferences: Analyses of Data from the Live Social Semantics Application

Social Dynamics in Conferences: Analyses of Data from the Live Social Semantics Application

Anomaly Based Detection of Violations in Web Applications

Mobility Modeling for Personal Networks

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