A Novel Multi-Hop Algorithm for Wireless Network with Unevenly Distributed Nodes

作     者：Yu Liu Zhong Yang Xiaoyong Yan Guangchi Liu Bo Hu 

作者机构：School of Computer EngineeringJinling Institute of TechnologyNanjing211169China School of Intelligence Science and Control EngineeringJinling Institute of TechnologyNanjing211169China School of Modern Post&Institute of Modern PostsNanjing University of Posts and TelecommunicationsNanjing210003China Stratifyd Inc.CharlotteNC 28208USA Center of Information Construction and ManagementNanjing Normal University of Special EducationNanjing210038China 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2019年第58卷第1期

页      面：79-100页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：The paper is sponsored by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(15KJB520009,16KJD520004) China Postdoctoral Science Foundation(2016M601861) Jiangsu Postdoctoral Science Foundation(1701049A) the Open Project Program of Jiangsu Key Laboratory of Remote Measurement and Control(YCCK201603) 

主　　题：Multi-hop localization Elastic Net regularization sparse 

摘      要：Node location estimation is not only the promise of the wireless network for target recognition,monitoring,tracking and many other applications,but also one of the hot topics in wireless network *** this paper,the localization algorithm for wireless network with unevenly distributed nodes is discussed,and a novel multi-hop localization algorithm based on Elastic Net is *** proposed approach is formulated as a regression problem,which is solved by Elastic *** other previous localization approaches,the proposed approach overcomes the shortcomings of traditional approaches assume that nodes are distributed in regular areas without holes or obstacles,therefore has a strong adaptability to the complex deployment *** proposed approach consists of three steps:the data collection step,mapping model building step,and location estimation *** the data collection step,training information among anchor nodes of the given network is *** mapping model building step,the mapping model among the hop-counts and the Euclidean distances between anchor nodes is constructed using Elastic *** location estimation step,each normal node finds its exact location in a distributed *** scenario experiments and simulation experiments do exhibit the excellent and robust location estimation performance.