Dynamic simulation based localization for mobile sensor networks

In mobile wireless sensor networks, sensors can move randomly or keep static temporarily. Mobility makes the sensor networks better acquire information, but also makes accurate localization more difficult since the network environment changes continually. In this paper, an energy-efficient dynamic simulation based localization (DSL) algorithm is introduced that uses range measurement information to restrict sample region and establishes a dynamic filtering mechanism to improve the localization performance and efficiency. Analytical and simulation results are provided to study the localization cost and location accuracy in different mobility models and various environmental settings. The results indicate that our algorithm outperforms the best known simulation based localization schemes under a wide range of conditions, with localization accuracy improved by an average of 24% and computation cost reduced significantly for a similar high localization accuracy.

[1]  David Evans,et al.  Localization for mobile sensor networks , 2004, MobiCom '04.

[2]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[3]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..

[4]  Ian F. Akyildiz,et al.  Wireless sensor networks , 2007 .

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

[6]  Yugeng Xi,et al.  Energy-Efficient Aggregation Control for Mobile Sensor Networks , 2006 .

[7]  Jun Wang,et al.  Mobility-Pattern Based Localization Update Algorithms for Mobile Wireless Sensor Networks , 2005, MSN.

[8]  Paul J. M. Havinga,et al.  Range-Based Localization in Mobile Sensor Networks , 2006, EWSN.

[9]  Vinay Kolar,et al.  Dynamic localization control for mobile sensor networks , 2005, PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, 2005..

[10]  Liang Yua,et al.  A Review of Control and Localization for Mobile Sensor Networks , 2006, WCICA 2006.

[11]  Gerald E. Sobelman,et al.  Gradient-Driven Target Acquisition in Mobile Wireless Sensor Networks , 2006, MSN.

[12]  Koen Langendoen,et al.  Monte-Carlo Localization for Mobile Wireless Sensor Networks , 2006, MSN.

[13]  Mingyan Liu,et al.  Sound mobility models , 2003, MobiCom '03.

[14]  Koen Langendoen,et al.  Distributed localization in wireless sensor networks: a quantitative compariso , 2003, Comput. Networks.