期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2017
卷号：13
期号：12
页码：1
DOI：10.1177/1550147717749744
出版社：Hindawi Publishing Corporation
摘要：In the Internet of things, a large number of objects can be embedded over a region of interest where almost every device is connected to the Internet. This work scrutinizes the broadcast overhead problem in an Internet of things network, containing a very large number of objects. The work proposes a probabilistic structure (bloom filter)-based technique, which uses a new broadcast structure that attempts to reduce the number of duplicate copies of a packet at every node. This article utilizes a clustering concept to make the broadcast efficient in terms of memory space, broadcast overhead, and energy usage. The unique idea of a bloom-based network uses a filter to incorporate neighbor information when taking a forwarding decision to reduce broadcast overhead. The simulation results show that parallel broadcasting among different clusters and the use of a bloom filter can achieve a reduction in broadcast overhead from hundreds to ones and tens, when compared with a conventional non-bloom-based broadcast algorithm and a bloom-based algorithm. In addition, it helps to reduce energy usage evenly throughout the network, 1/100 times, when compared with conventional broadcast (non-bloom-based) and, 1/10 times, when compared with bloom-based broadcast. This increases the lifetime of a network by having control over network density usage and communications overhead as a result of broadcasting.
关键词：Internet of things; broadcast; bloom filter; cluster
