Identifying Nearest Neighbor Nodes and Connectivity in Three-Dimensional Wireless Sensor Networks Using Poisson Point Field

Abstract : Some problems about the connectivity of wireless sensor networks (WSNs) are always important and difficult topics in research, especially the trade-off between connectivity and energy control. In this paper, we present a novel and effective method to calculate nearest neighbor nodes in three-dimensional WSNs using Poisson point field theory, which enables each node to find the kth nearest neighbor node and adjust transmitting range according to local requirement. Moreover, we derive the probability expression of the k-connected network. Finally, we give corresponding simulation results and discussions about the practical value for node energy control and design of WSNs.
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Chen Ding; Zhiyuan Shao; Ran Zheng. IFIP International Conference on Network and Parallel Computing (NPC), Sep 2010, Zhengzhou, China. Springer, Lecture Notes in Computer Science, LNCS-6289, pp.200-209, 2010, Network and Parallel Computing. 〈10.1007/978-3-642-15672-4_18〉
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Yanhuai Qu, Jianan Fang, Shuai Zhang. Identifying Nearest Neighbor Nodes and Connectivity in Three-Dimensional Wireless Sensor Networks Using Poisson Point Field. Chen Ding; Zhiyuan Shao; Ran Zheng. IFIP International Conference on Network and Parallel Computing (NPC), Sep 2010, Zhengzhou, China. Springer, Lecture Notes in Computer Science, LNCS-6289, pp.200-209, 2010, Network and Parallel Computing. 〈10.1007/978-3-642-15672-4_18〉. 〈hal-01054990〉

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