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Performance analysis of artificial bee colony optimization based clustering protocol in various scenarios of WSN

机译:WSN各种场景下基于人工蜂群优化的聚类协议性能分析

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Most primaryconcern in wireless sensor networks (WSN) is management of energy of the small nodes deployed for sensing physical or environmental conditions of an area. However appropriate use of routing protocols can increase the network life. Protocols based on clustering such as LEACH is a competent approach, in which cluster has been planned; each cluster has plentiful nodes and lone cluster head (CH). Node transmits their sensed information to CH; CH cumulates that information and forwards that to sink. Soft-computing (SC) technique such as nature inspired algorithms are use to deal with the complex constraints in WSNs. One of such technique is Artificial Bee Colony Optimization (ABCO) that is based on swarm intelligence. In this paper, ABCO based LEACH algorithm is tested broadly on diverse scenarios of WSNs, changing maximum number of rounds (rmax) as well as number of sensor nodes (n). Multiple numbers of parameters such as dead nodes per round, alive nodes per round and packet to base station (BS) per round, are taken into concern for performance evaluation. Comparison of each parameter from conventional LEACH is also presented. The simulation has been done in MATLAB.
机译:无线传感器网络(WSN)中最主要的关注点是管理用于感知某个区域的物理或环境状况的小型节点的能量管理。但是,正确使用路由协议可以延长网络寿命。基于集群的协议(例如LEACH)是一种行之有效的方法,其中已经计划了集群;每个集群都有很多节点和孤簇头(CH)。节点将其感测到的信息发送给CH; CH累积该信息并将其转发到接收器。软计算(SC)技术(例如自然启发算法)用于处理WSN中的复杂约束。其中一种技术是基于群体智能的人工蜂群优化(ABCO)。在本文中,基于ABCO的LEACH算法在WSN的各种情况下进行了广泛测试,更改了最大回合数(rmax)以及传感器节点数(n)。为了进行性能评估,需要考虑多个参数,例如每轮死节点,每轮活动节点以及每轮到基站(BS)的数据包。还介绍了来自传统LEACH的每个参数的比较。仿真已经在MATLAB中完成。

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