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      Passive-Event-Assisted Approach for the Localizability of Large-Scale Randomly Deployed Wireless Sensor Network

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          Abstract

          Localizability in large-scale, randomly deployed Wireless Sensor Networks (WSNs) is a classic but challenging issue. To become localizable, WSNs normally require extensive adjustments or additional mobile nodes. To address this issue, we utilize occasional passive events to ease the burden of localization-oriented network adjustment. We prove the sufficient condition for node and network localizability and design corresponding algorithms to minimize the number of nodes for adjustment. The upper bound of the number of adjusted nodes is limited to the number of articulation nodes in a connected graph. The results of extensive simulations show that our approach greatly reduces the cost required for network adjustment and can thus provide better support for the localization of large-scale sparse networks than other approaches.

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          Author and article information

          Journal
          TST
          Tsinghua Science and Technology
          Tsinghua University Press (Xueyan Building, Tsinghua University, Beijing 100084, China )
          1007-0214
          05 April 2019
          : 24
          : 2
          : 134-146
          Affiliations
          ∙ Zhiguo Chen and Guifa Teng are with the College of Information Science and Technology, Agricultural University of Hebei, Baoding 071000, China. E-mail: chenzhiguo2006@ 123456sina.com .
          ∙ Xiaolei Zhou is with Nanjing Telecommunication Technology Research Institute, National University of Defense Technology, Nanjing 210089, China. E-mail: zhouxiaolei@ 123456nudt.edu.cn .
          ∙ Tao Chen is with Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China. E-mail: chentao@ 123456nudt.edu.cn .
          Author notes
          * To whom correspondence should be addressed. E-mail: tguifa@ 123456hebau.edu.cn .

          Zhiguo Chen received the BS degree from Fourth Military Medical University in 2009, and MS degree from Agricultural University of Hebei in 2013. He is currently a PhD candidate in School of Information Science and Technology, Agricultural University of Hebei, China. His research interests include wireless sensor networks, intelligent agriculture, and Internet of Things.

          Guifa Teng received the BS and MS degrees from Agricultural University of Hebei in 1979 and 1988, respectively. He received the PhD degree from Peking University in 2005. He is currently a professor in School of Information Science and Technology, as well as the director of graduate school, in Agricultural University of Hebei, China. His research interests include artificial intelligence, big data, and intelligent agriculture.

          Xiaolei Zhou received the BS degree from Nanjing University in 2009, MS and PhD degrees from National University of Defense Technology, in 2011 and 2016, respectively. He is an assistant professor with the Nanjing Telecommunication Technology Research Institute, National University of Defense Technology. His research interests include mobile computing, wireless indoor positioning, and location based services.

          Tao Chen received the BS, MS, and PhD degrees from National University of Defense Technology in 2004, 2006, and 2011, respectively. He is an assistant professor with the College of System Engineering, National University of Defense Technology. His research interests include wireless sensor networks, peer-to-peer computing, and data center networking.

          Article
          1007-0214-24-2-134
          10.26599/TST.2018.9010070

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