A fuzzy-ACO algorithm to enhance reliability optimization through energy harvesting in WSN

A. Banerjee, Samiran Chattopadhyay, A. Mukhopadhyay, G. Gheorghe
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引用次数: 5

Abstract

Reliability optimization in Wireless Sensor Network (WSN) is obviously an important problem. The basic function of a WSN is to provide an adequate and quality data transmission as economically as possible with a reasonable level of reliability with minimum power consumption. To make the system more reliable, solar energy has been considered as energy harvesting strategy. In this paper, an algorithm aiming for reliability optimization in WSN systems is discussed. This algorithm is based on a modified Ant Colony Optimization (ACO) algorithm. The throughput obtained from Sensor Medium Access Control (SMAC) protocol considered as objective function with respect to different environmental constraints. For the input variables, fuzzy models with trapezoidal membership functions are used. The results obtained are compared with other approaches from literature and found satisfactory.
基于能量收集的模糊蚁群算法增强无线传感器网络的可靠性优化
无线传感器网络(WSN)的可靠性优化显然是一个重要问题。无线传感器网络的基本功能是尽可能经济地提供充分和高质量的数据传输,具有合理的可靠性水平和最小的功耗。为了使系统更加可靠,太阳能被认为是一种能量收集策略。本文讨论了一种用于WSN系统可靠性优化的算法。该算法基于改进的蚁群优化算法。将传感器介质访问控制(SMAC)协议获得的吞吐量作为考虑不同环境约束的目标函数。输入变量采用梯形隶属函数模糊模型。将所得结果与文献中其他方法进行了比较,结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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