Approximation Designs for Energy Harvesting Relay Deployment in Wireless Sensor Networks
作者机构：School of Modern PostsNanjing University of Posts and TelecommunicationsNanjing 210003China State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjing 210023China ByteDance Inc.Shanghai 201100China Key Laboratory of Artificial Intelligence of Ministry of EducationDepartment of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China
出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)
年 卷 期：2022年第37卷第4期
页 面：779-796页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：This work was supported by the Key-Area Research and Development Program of Guangdong Province of China under Grant No.2020B0101390001 the Shanghai Municipal Science and Technology Major Project of China under Grant No.2021SHZDZX0102 the National Natural Science Foundation of China under Grant No.62072228 the Fundamental Research Funds for the Central Universities of China,the Collaborative Innovation Center of Novel Software Technology and Industrialization of Jiangsu Province of China,and the Jiangsu Innovation and Entrepreneurship(Shuangchuang)Program of China
主 题：approximation algorithm constraint relay deployment energy harvesting wireless sensor network
摘 要：Energy harvesting technologies allow wireless devices to be recharged by the surrounding environment, providing wireless sensor networks (WSNs) with higher performance and longer lifetime. However, directly building a wireless sensor network with energy harvesting nodes is very costly. A compromise is upgrading existing networks with energy harvesting technologies. In this paper, we focus on prolonging the lifetime of WSNs with the help of energy harvesting relays (EHRs). EHRs are responsible for forwarding data for sensor nodes, allowing them to become terminals and thus extending their lifetime. We aim to deploy a minimum number of relays covering the whole network. As EHRs have several special properties such as the energy harvesting and depletion rate, it brings great research challenges to seek an optimal deployment strategy. To this end, we propose an approximation algorithm named Effective Relay Deployment Algorithm, which can be divided into two phases: disk covering and connector insertion using the partitioning technique and the Steinerization technique, respectively. Based on probabilistic analysis, we further optimize the performance ratio of our algorithm to (5 + 6/K) where K is an integer denoting the side length of a cell after partitioning. Our extensive simulation results show that our algorithm can reduce the number of EHRs to be deployed by up to 45% compared with previous work and thus validate the efficiency and effectiveness of our solution.
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