Corona based deployment strategies in wireless sensor network: A survey

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• 作者：Atiq Ur Rahman^a ; ^{atiq621@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Abdulrahman Alharby^a ; ^{ar.alharby@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Halabi Hasbullah^b ; ^{halabi@petronas.com.my" class="auth_mail" title="E-mail the corresponding author} ; Khalid Almuzaini^c ; ^{kmuzaini@kacst.edu.sa" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Energy hole ; Coverage hole ; Corona based deployment ; Arithmetic and geometric proportion
• 刊名：Journal of Network and Computer Applications
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：64
• 期：Complete
• 页码：176-193
• 全文大小：2544 K

文摘

A wireless sensor network (WSN) is composed of a large number of sensor nodes, relay nodes, and a base station, that are deployed in an environment to collect information. WSNs are getting more widespread use and have been adapted to a vast array of applications, such as habitat monitoring, precision agriculture, smart homes and military surveillance. It is necessary for various applications to deploy sensor nodes in an efficient way as much as possible and to monitor the event precisely. Irregular deployment of sensor node creates coverage-holes and energy holes in a network. Due to coverage hole not every point in the target area is being covered and the formation of energy-holes means that data can no longer be delivered to the sink on certain path. This particular time instance has been defined as “the total network lifetime”. As balanced energy consumption among the sensor nodes of the WSN is the most challenging problem due to many-to-one traffic pattern. The goal of our survey is to present a comprehensive review of the recent literature of sensor node deployment. In this paper, we classify the sensor node deployment strategies into two types: (1) Non-corona and (2) Corona-based sensor node deployment strategies. We review the major development in the two deployment strategies and outline the new challenges. Their simulation results showed that each deployment strategy significantly utilized the energy of the nodes and prolongs the network lifetime.