文章基本信息

标题：WIRELESS SENSOR NETWORK DEPLOYMENT BASED ON MACHINE LEARNING FOR PROLONGING NETWORK LIFETIME AND PDR
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作者：ALI NOORI ; ONG BI LYNN ; HASNA AHMAD 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2019
卷号：97
期号：14
页码：3958-3968
出版社：Journal of Theoretical and Applied
摘要：Sensor Deployment (SN) is one of the major challenges in wireless sensor network architecture. One of the most fundamental issues in wireless sensor deployment is to balance the objective to resolve network conflicts. This paper aims to find the Pareto front that maximizes the packet delivery ratio and minimizes sensor energy consumption for prolonging network lifetime. For this proposal, a hyper-heuristic framework for improving the performance of the metaheuristic (LMOJPSO) search optimization process by combining two different searching techniques was designed. The first optimization technique carried out its searches with the help of an extreme learning machine (ELM), whereas the second used a wireless sensor network simulator. In this paper, the proposed method is examined in given wireless sensor network test instances, and the evaluation of its performance is carried out using a WSN performance metric. The results indicate that the proposed model is superior to the non-dominated sorting genetic algorithm (NSGA-II).
关键词：Wireless Sensor Network Deployment; NSGA-II; Hyper-heuristic; PSO; Optimization