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A Self-Optimizing Scheme for Energy Balanced Routing in Wireless Sensor Networks Using SensorAnt

机译:使用SensorAnt的无线传感器网络中能量平衡路由的自优化方案

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摘要

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.
机译:由于传感器节点的能量受到限制,节能协议的规划对于无线传感器网络(WSN)至关重要。路由协议应该能够在传输到宿节点的过程中提供均匀的功耗。在本文中,我们提出了一种无线传感器网络的自优化方案,该方案能够利用和优化传感器节点的资源,尤其是电池,以实现所有传感器节点之间的均衡能耗。该方法基于蚁群优化(ACO)元启发式算法,该算法用于增强具有最佳质量功能的路径。此功能的评估取决于多种标准的度量标准,例如最小剩余电池电量,跳数以及路由和网络的平均能量。此方法还可以在整个WSN中分配传感器节点的流量负载,从而减少能耗,延长网络寿命并减少数据包丢失。仿真结果表明,该方案在能耗,平衡和效率方面都比基于节能蚂蚁路由(EEABR)更好。

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