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B-SUB: A Practical Bloom-Filter-Based Publish-Subscribe System for Human Networks

机译:B-Sub:用于人类网络的实用盛开滤波器的发布 - 订阅系统

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The adoption of portable wireless devices is rapidly rising. The demand for efficient communication protocols amongst these devices is pressing. In this paper, we present a content-based publish-subscribe system, called B-SUB (Bloom-filter-based pub-SUB system), for the networks formed by human-carried wireless devices, which are called human networks (HUNETs). A novel data structure, called Temporal Counting Bloom Filter (TCBF), is proposed to perform content-based networking tasks. The TCBF's novelty is that it is able to handle temporal operations, which are not supported in the classic Bloom filter (BF) and are crucial to the success of forwarding messages in HUNETs. B-SUB uses TCBFs to encode users' interests and embed routing information. Using the TCBF, B-SUB can propagate interests by transmitting at most two TCBFs of dozens of bytes, which makes B-SUB space-efficient. B-SUB makes forwarding decisions through querying the TCBFs, which is simple and fast. These designs make B-SUB pretty suitable for resource-constrained HUNETs. However, the TCBF has false positives, which will potentially cause useless messages to be injected into the network. The issue that arises here is how to handle its false positives in queries, and at the same time maintain its spacial efficiency as well. So, we analyze several methods for controlling the TCBF's false positive rate. B-SUB's viability and usefulness are verified through extensive simulation studies using real-world human contact traces.
机译:便携式无线设备的采用正在迅速崛起。这些设备之间的高效通信协议的需求正在按压。在本文中,我们提出了一种基于内容的发布 - 订阅系统中,称为B-SUB(基于布隆过滤器的发布 - 订阅系统),用于通过人携带的无线设备,这是所谓的人际网络形成的网络(HUNETs) 。一种新颖的数据结构,称为颞计数布隆过滤器(TCBF),提出了执行基于内容的联网任务。该TCBF的新颖之处在于它能够处理时间的操作,这是不是在经典的布隆过滤器(BF)的支持,并在HUNETs转发消息的成功是至关重要的。 B-SUB采用TCBFs来编码用户的兴趣,并嵌入路由信息。使用TCBF,B-SUB可以在几十个字节的至多两个TCBFs传播通过发送利益,这使得B-SUB空间效率。 B-SUB使得通过查询TCBFs,这是简单而快速的转发决策。这些设计使得B-SUB非常适合资源有限的HUNETs。然而,TCBF具有假阳性,这将潜在地引起无用消息被注入到网络中。那这里出现的问题是如何处理它的误报的查询,同时保持其空间效率以及。因此,我们分析控制TCBF的假阳性率的几种方法。 B-SUB的可行性和有效性,通过使用现实世界的人类接触的痕迹广泛的模拟研究证实。

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