Energy effficient cache node placement using genetic algorithm & cooperative caching algorithm

M. Parvez, H. Divya
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引用次数: 1

Abstract

Optimization of communication among sensors to serve data in short latency and minimal energy is necessitated for some of the wireless sensor network applications. For a self-organizing wireless sensor network Genetic Algorithm based multi-objective methodology is developed and is used as a technique in the selection of sensor nodes which play special roles in running caching and request forwarding decisions. For developing the fitness function design parameters such as network density, connectivity and energy consumption are considered. The algorithm is implemented in MATLAB using Genetic Algorithm toolbox. The optimized network obtained using Genetic Algorithm is deployed in the same manner using network simulator and the cooperative caching algorithm is run on it. The algorithm is checked for short latency and minimum energy consumption and compared with the previous cooperative caching scheme and Scaled power community index cooperative caching scheme.
基于遗传算法和协同缓存算法的高效缓存节点布局
在一些无线传感器网络应用中,需要优化传感器之间的通信,以短延迟和最小能量提供数据。针对自组织无线传感器网络,提出了一种基于遗传算法的多目标方法,并将其作为一种选择传感器节点的技术,这些节点在运行缓存和请求转发决策中起着特殊的作用。为了建立适应度函数,考虑了网络密度、连通性和能耗等设计参数。该算法在MATLAB中利用遗传算法工具箱实现。利用网络模拟器对遗传算法得到的优化网络进行相同方式的部署,并在其上运行协同缓存算法。对该算法进行了时延短、能耗小的检验,并与已有的协同缓存方案和缩放功率社区索引协同缓存方案进行了比较。
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