GSFord:迈向可靠的地理社会通知系统

Kyungbaek Kim, Ye Zhao, N. Venkatasubramanian
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引用次数: 13

摘要

任何通知系统的最终目标都是将适当的消息以非常高的可靠性及时地传递给所有相关的接收者。我们特别关注极端情况下的通知(例如灾难),在这种情况下,地理上相关的故障阻碍了到达相应故障区域内的收件人的能力。在本文中,我们介绍了GSFord,一个可靠的地理社会通知系统,它意识到(a)信息需要传播的地理位置和(b)预期接收者的社会网络特征,以最大化/增加覆盖范围和可靠性。GSFord构建了强大的地理感知P2P覆盖,以提供高效的基于位置的消息传递和可靠的接收者地理社会信息存储。当事件发生时,GSFord能够有效地将消息传递给(a)位于事件区域或(b)与事件有社会关联的接收者(例如,受事件影响者的亲戚/朋友)。此外,GSFord利用地理社会信息触发社会扩散过程,该过程通过电话和人际接触等带外渠道运作,以便接触到在失败地区被隔离的接收者。通过广泛的评估,我们表明GSFord是可靠的,即使在大量地理相关区域失效的情况下,GSFord增强的社会扩散过程也达到99.9%的期望接受者。我们还表明,即使在用户群体分布不均的情况下,GSFord也是有效的。
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GSFord: Towards a Reliable Geo-social Notification System
The eventual goal of any notification system is to deliver appropriate messages to all relevant recipients with very high reliability in a timely manner. In particular, we focus on notification in extreme situations (e.g. disasters) where geographically correlated failures hinder the ability to reach recipients inside the corresponding failed region. In this paper, we present GSFord, a reliable geo-social notification system that is aware of (a) the geographies in which the message needs to be disseminated and (b) the social network characteristics of the intended recipient, in order to maximize/increase the coverage and reliability. GSFord builds robust geo-aware P2P overlays to provide efficient location-based message delivery and reliable storage of geo-social information of recipients. When an event occurs, GSFord is able to efficiently deliver the message to recipients who are either (a) located in the event area or (b) socially correlated to the event (e.g. relatives/friends of those who are impacted by an event). Furthermore, GSFord leverages the geo-social information to trigger a social diffusion process, which operates through out-of band channels such as phone calls and human contacts, in order to reach recipients which are isolated in the failed region. Through extensive evaluations, we show that GSFord is reliable, the social diffusion process enhanced by GSFord reaches up to 99.9\% of desired recipients even under massive geographically correlated regional failures. We also show that GSFord is efficient even under skewed distribution of user populations.
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