mca 12(2): e5

Research Article

A Trace-Driven Analysis of Wireless Group Communication Mechanisms

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  • @ARTICLE{10.4108/mca.2012.07-09.e5,
        author={Surendar Chandra and Xuwen Yu},
        title={A Trace-Driven Analysis of Wireless Group Communication Mechanisms},
        journal={EAI Endorsed Transactions on Mobile Communications and Applications},
        volume={1},
        number={2},
        publisher={ICST},
        journal_a={MCA},
        year={2012},
        month={8},
        keywords={Wireless LAN, group communication mechanisms},
        doi={10.4108/mca.2012.07-09.e5}
    }
    
  • Surendar Chandra
    Xuwen Yu
    Year: 2012
    A Trace-Driven Analysis of Wireless Group Communication Mechanisms
    MCA
    ICST
    DOI: 10.4108/mca.2012.07-09.e5
Surendar Chandra1, Xuwen Yu2
  • 1: FX Palo Alto Laboratory, Palo Alto, CA 94304, USA
  • 2: VMware Inc., Palo Alto, CA 94304, USA

Abstract

Wireless access is increasingly ubiquitous while mobile devices that use them are resource rich. These trends allow wireless users to collaborate with each other. We investigate various group communication paradigms that underly collaboration applications. We synthesize durations when members collaborate using wireless device availability traces. Wireless users operate from a variety of locations. Hence, we analyzed the behavior of wireless users in universities, corporations, conference venues, and city-wide hotspots. We show that the availability durations are longer in corporations followed by university and then in hotspots. The number of simultaneously available wireless users is small in all the scenarios. The session lengths are becoming smaller while the durations between sessions are becoming larger. We observed user churn in all the scenarios. We show that synchronous mechanisms require less effort to maintain update synchronicity among the group members. However, distributed mechanisms require a large number of replicas in order to propagate updates among the users. For asynchronous mechanisms, we show that pull-based mechanisms naturally randomize the times when updates are propagated and thus achieve better performance than push based mechanisms.We develop an adaptive approach that customizes the update frequency using the last session duration and show that this mechanism exhibits good performance when the required update frequency intervals are large. We also show that for a given number of gossips, it is preferable to propagate updates to all available nodes rather than increasing the frequency while correspondingly reducing the number of nodes to propagate updates.We develop a middleware to illustrate the practicality of our approach.