ICP: Instantaneous clustering protocol for wireless sensor networks

详细信息    查看全文

• 作者：Linghe Kong^a ; ^{linghe.kong@sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Qiao Xiang^b ; ^c ; ^{xiangq27@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Xue Liu^d ; ^{xueliu@cs.mcgill.ca" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Xiao-Yang Liu ; ^a ; ^{yanglet@sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Xiaofeng Gao^a ; ^{gao-xf@cs.sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Guihai Chen^a ; ^{gchen@cs.sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Min-You Wu^a ; ^{mwu@sjtu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Instantaneous clustering protocol ; Parallel clustering ; Wireless sensor networks
• 刊名：Computer Networks
• 出版年：2016
• 出版时间：4 June 2016
• 年：2016
• 卷：101
• 期：Complete
• 页码：144-157
• 全文大小：1720 K

文摘

Wireless sensor network (WSN) is one of the mainstay technologies in Internet of Things. In WSNs, clustering is to organize scattered sensor nodes into a cluster-topology network for communications. Existing efforts on clustering intensively focus on the energy-efficiency issue. However, in mission-critical applications, a fast clustering scheme, which can not only gather sensory data immediately after deployment but also reduce the energy consumption, is more desired. In this paper, we study the clustering problem considering both time- and energy-efficiency. We propose a novel instantaneous clustering protocol (ICP) that groups sensor nodes into single-hop clusters in a parallel manner. ICP can instantaneously complete the clustering due to two key designs. First, to determine the cluster heads locally. Existing methods require a long duration on cluster head voting. To waive the voting consumption, a cluster head in ICP is locally determined by the pre-assigned probability and its present status. Second, to minimize the amount of transmissions. Parallel transmissions from different cluster heads and acknowledgments (ACKs) from multiple cluster members lead to severe time and energy consumption. On the contrary, ICP gets rid of the ACK mechanism, instead, only cluster heads contend to broadcast during a given period. This period is elaborately derived to guarantee the connectivity. Experiments on a 64-node testbed and simulations on large-scale WSNs are extensively conducted to evaluate ICP. Performance results demonstrate that ICP significantly outperforms existing clustering methods by reducing up to 55% time consumption and 89% amount of transmissions for energy-saving.