Cluster based localization algorithm in wireless networks

Given the locations of a small number of reference anchor nodes and the distances between neighbour nodes, various localization algorithms for wireless networks have been proposed. In this paper, we carry out a comparative evaluation of three different cluster based localization algorithms. The three different algorithms are based on the use of extended Kalman filter (EKF), semi-definite programming (SDP) and multi-dimensional scaling (MDS). Their cluster based variants are the decentralized EKF (DEKF), cluster based SDP (CSDP) and cluster based MDS (CMDS), respectively. The algorithms are evaluated in both static and low mobility environments. Simulation results show that DEKF performs as well as EKF in both static and low mobility environments, and they outperform CSDP and CMDS. DEKF requires less anchor nodes, smaller cluster, while achieving more accurate location estimation.

[1]  Wheeler Ruml,et al.  Improved MDS-based localization , 2004, IEEE INFOCOM 2004.

[2]  Hans Scholten,et al.  An Iterative Quality-Based Localization Algorithm for Ad Hoc Networks , 2002 .

[3]  L. El Ghaoui,et al.  Convex position estimation in wireless sensor networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[4]  B. R. Badrinath,et al.  Ad hoc positioning system (APS) , 2001, GLOBECOM'01. IEEE Global Telecommunications Conference (Cat. No.01CH37270).

[5]  Mani B. Srivastava,et al.  The bits and flops of the n-hop multilateration primitive for node localization problems , 2002, WSNA '02.

[6]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[7]  Yinyu Ye,et al.  Semidefinite programming for ad hoc wireless sensor network localization , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[8]  Jian Shu,et al.  Cluster-based Three-dimensional Localization Algorithm for Large Scale Wireless Sensor Networks , 2009, J. Comput..

[9]  Nitin H. Vaidya,et al.  Location-aided routing (LAR) in mobile ad hoc networks , 1998, MobiCom '98.

[10]  S. Grime,et al.  Data fusion in decentralized sensor networks , 1994 .

[11]  Gwo-Jong Yu,et al.  A Hierarchical MDS-based Localization Algorithm for Wireless Sensor Networks , 2007 .

[12]  Nitin H. Vaidya,et al.  Location‐Aided Routing (LAR) in mobile ad hoc networks , 2000, Wirel. Networks.

[13]  Y. Ye,et al.  A Distributed Method for Solving Semidefinite Programs Arising from Ad Hoc Wireless Sensor Network Localization , 2006 .

[14]  Kim-Chuan Toh,et al.  SDPT3 -- A Matlab Software Package for Semidefinite Programming , 1996 .

[15]  Mario Gerla,et al.  Adaptive Clustering for Mobile Wireless Networks , 1997, IEEE J. Sel. Areas Commun..

[16]  Heikki N. Koivo,et al.  Decentralized Kalman Filter in Wireless Sensor Networks – Case Studies , 2007 .

[17]  Yinyu Ye,et al.  Semidefinite programming based algorithms for sensor network localization , 2006, TOSN.

[18]  Mani B. Srivastava,et al.  On the Error Characteristics of Multihop Node Localization in Ad-Hoc Sensor Networks , 2003, IPSN.

[19]  Zhanyang Zhang,et al.  A CLUSTER BASED APPROACH TOWARD SENSOR LOCALIZATION AND K-COVERAGE PROBLEMS , 2011 .

[20]  Jan M. Rabaey,et al.  Location in distributed ad-hoc wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).