Node distribution-based localization for large-scale wireless sensor networks

Authors:
Sangjin Han;Sungjin Lee;Sanghoon Lee;Jongjun Park;Sangjoon Park
Affiliations:
Wireless Network Lab, Center for IT of Yonsei University, Seoul, Korea 120-749;Wireless Network Lab, Center for IT of Yonsei University, Seoul, Korea 120-749;Wireless Network Lab, Center for IT of Yonsei University, Seoul, Korea 120-749;Electronics and Telecommunications Research Institute, Daejeon, Korea 305-350;Electronics and Telecommunications Research Institute, Daejeon, Korea 305-350
Venue:
Wireless Networks
Year:
2010

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Abstract

Distributed localization algorithms are required for large-scale wireless sensor network applications. In this paper, we introduce an efficient algorithm, termed node distribution-based localization (NDBL), which emphasizes simple refinement and low system-load for low-cost and low-rate wireless sensors. Each node adaptively chooses neighboring nodes, updates its position estimate by minimizing a local cost-function, and then passes this updated position to neighboring nodes. This update process uses a node distribution that has the same density per unit area as large-scale networks. Neighbor nodes are selected from the range in which the strength of received signals is greater than an experimentally based threshold. Based on results of a MATLAB simulation, the proposed algorithm was more accurate than trilateration and less complex than multi-dimensional scaling. Numerically, the mean distance error of the NDBL algorithm is 1.08---5.51 less than that of distributed weighted multi-dimensional scaling (dwMDS). Implementation of the algorithm using MicaZ with TinyOS-2.x confirmed the practicality of the proposed algorithm.