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Service discovery in mobile social networks

机译:移动社交网络中的服务发现

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摘要

We present a new service discovery algorithm, termed SIDEMAN, which considers human mobility for service dissemination and discovery. In particular, SIDEMAN takes advantage of mobile social networking characteristics, such as user membership to a restricted number of communities, and interest for similar services among users in the same community. We evaluated the performance of SIDEMAN via simulations in a scenario based on traces collected at the IEEE conference Infocom in 2006. Our algorithm has been compared to the social version of two popular data dissemination techniques, namely, flooding and gossiping. We have measured how proactive an algorithm is in distributing services of interest (Recall), how many services are already with a user when they are needed (Gain), the energy cost necessary for service discovery, and the time needed to reply to a service query. Our results show that SIDEMAN obtains perfect Recall and a Gain that is always comparable to that of the other algorithms. Furthermore, most services are retrieved in reasonable time and at a remarkably lower energy cost than that of the flooding and gossiping-based solutions.
机译:我们提出了一种称为SIDEMAN的新服务发现算法,该算法将人的移动性考虑为服务的传播和发现。特别地,SIDEMAN利用了移动社交网络的特性,例如,用户成为受限数量的社区成员,以及对同一社区中用户之间相似服务的兴趣。我们基于在2006年IEEE大会Infocom上收集的跟踪数据,通过模拟对SIDEMAN的性能进行了评估。我们的算法已与两种流行的数据分发技术的社交版本(即泛洪和闲聊)进行了比较。我们已经测量了算法在分配感兴趣的服务时的积极性(调用),在需要时已经与用户一起获得了多少服务(收益),服务发现所需的能源成本以及答复服务所需的时间查询。我们的结果表明,SIDEMAN获得了完美的查全率和一个始终可与其他算法相媲美的增益。此外,与基于洪泛和闲聊的解决方案相比,大多数服务都可以在合理的时间内获得,并且能源成本显着降低。

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