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使用 SensorAnt 的无线传感器网络中能量平衡路由的自优化方案。

A self-optimizing scheme for energy balanced routing in Wireless Sensor Networks using SensorAnt.

机构信息

Department of Computer and Communication Systems Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, Malaysia.

出版信息

Sensors (Basel). 2012;12(8):11307-33. doi: 10.3390/s120811307. Epub 2012 Aug 15.

Abstract

Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.

摘要

节能协议的规划对于无线传感器网络(WSNs)至关重要,因为传感器节点的能量受到限制。路由协议应该能够在向汇聚节点传输时提供均匀的功耗。在本文中,我们提出了一种用于 WSN 的自优化方案,该方案能够利用和优化传感器节点的资源,特别是电池,以实现所有传感器节点的能耗平衡。该方法基于蚁群优化(ACO)元启发式算法,采用该算法来增强具有最佳质量函数的路径。该函数的评估取决于多准则指标,如最小剩余电池电量、跳数以及路由和网络的平均能量。该方法还通过在整个 WSN 中分配传感器节点的业务负载来减少能量消耗、延长网络寿命并减少分组丢失。仿真结果表明,我们的方案在能耗、平衡和效率方面均优于基于能量的高效蚁群路由(EEABR)。

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