A Trace-Driven Analysis of Wireless Group Communication Mechanisms

Surendar Chandra, Xuwen Yu
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引用次数: 2

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 e ff ort 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.
无线群通信机制的跟踪驱动分析
无线接入越来越普遍,而使用无线接入的移动设备资源丰富。这些趋势使无线用户能够相互协作。我们研究了协作应用程序背后的各种群体通信范式。我们使用无线设备可用性跟踪来合成成员协作的持续时间。无线用户可以在不同的地点操作。因此,我们分析了无线用户在大学、公司、会议场所和城市热点的行为。我们表明,在企业中可用性持续时间较长,其次是大学,然后是热点。在所有场景中,同时可用的无线用户数量都很小。会话长度越来越短,而会话之间的持续时间越来越长。我们在所有情况下都观察到用户流失。我们展示了同步机制需要更少的努力来维护组成员之间的更新同步性。然而,分布式机制需要大量的副本,以便在用户之间传播更新。对于异步机制,我们展示了基于拉的机制自然地随机化更新传播的时间,从而获得比基于推的机制更好的性能。我们开发了一种自适应方法,该方法使用上次会话持续时间自定义更新频率,并表明当所需的更新频率间隔较大时,该机制表现出良好的性能。我们还表明,对于给定数量的八卦,最好是将更新传播到所有可用的节点,而不是在增加频率的同时相应地减少传播更新的节点数量。我们开发了一个中间件来说明我们方法的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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