个人信息Personal Information
副教授
博士生导师
硕士生导师
任职 : 档案馆、校史馆副馆长(挂职)
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:软件工程. 计算机应用技术
联系方式:0411-62274417
电子邮箱:c.lin@dlut.edu.cn
Clustering and splitting charging algorithms for large scaled wireless rechargeable sensor networks
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论文类型:期刊论文
发表时间:2016-03-01
发表刊物:JOURNAL OF SYSTEMS AND SOFTWARE
收录刊物:SCIE、EI
卷号:113
页面范围:381-394
ISSN号:0164-1212
关键字:Wireless rechargeable sensor networks; Charging efficiency; Task splitting
摘要:As the interdiscipline of wireless communication and control engineering, the periodical charging issue in Wireless Rechargeable Sensor Networks (WRSNs) is a popular research problem. However, existing techniques for periodical charging neglect to focus on the location relationship and topological feature, leading to large charging times and long traveling time. In this paper, we develop a hybrid clustering charging algorithm (HCCA), which firstly constructs a network backbone based on a minimum connected dominating set built from the given network. Next, a hierarchical clustering algorithm which takes advantage of location relationship, is proposed to group nodes into clusters. Afterward, a K-means clustering algorithm is implemented to calculate the energy core set for realizing energy awareness. To further optimize the performance of HCCA, HCCA-TS is proposed to transform the energy charging process into a task splitting model. Tasks generated from HCCA are split into small tasks, which aim at reducing the charging time to enhance the charging efficiency. At last, simulations are carried out to demonstrate the merit of the schemes. Simulation results indicate that HCCA can enhance the performance in terms of reducing charging times, journey time and average charging time simultaneously. Moreover, HCCA-TS can further improve the performance of HCCA. (C) 2015 Elsevier Inc. All rights reserved.