High Impact Factor : 4.396 icon | Submit Manuscript Online icon |

Information Maximization in Multihop Wireless Sensor Network Using TDOA within Resource Constraints


Shahid Mohi Ud Din , Al-Falah School of Engineering & Technology, Dhauj Faridabad, Haryana; Mohd Sadim, Al-Falah School of Engineering & Technology, Dhauj Faridabad, Haryana


Sensor pairing, source localization, TDOA, energy and delay efficiency, wireless sensor network.


We study the problem of information maximizing in a wireless sensor network (WSN) within resource constraints. We consider a sensor network with a tree topology, where the root corresponds to the sink, and the rest of the network detects an event and transmits data to the sink. This paper is concerned with source localization based on time-difference-of-arrival (TDOA) measurements from spatially separated sensors in a wireless sensor network (WSN). Most of the existing works adopt a centralized sensor pairing strategy, where one sensor node is chosen as the common reference. However, due to the bandwidth and power constraints of multihop WSNs, it is well known that this kind of centralized methods is energy consuming due to the need of single and multihop transmissions of raw measurement data. In this letter, we propose a decentralized in-network sensor pairing method to acquire TDOA measurements for source localization. It is proved that the proposed decentralized in-network sensor pairing method can result in the same Cramer–Rao-Bound (CRB) as the centralized one at a far less communication cost. We show that this optimization problem is NP-hard in the strong sense when the input is the maximum node degree of the tree. We then propose a dynamic programming framework for solving the problem exactly, which involves solving a special case of the job interval selection problem at each node. Our solution has a polynomial time complexity when the maximum node degree is O (log N) in a tree with N nodes. For trees with higher node degrees, we further develop a suboptimal solution, which has low complexity and allows distributed implementation. We investigate tree structures for which this solution is optimal to the original problem. The efficiency of the suboptimal solution is further demonstrated through numerical results on general trees.

Other Details

Paper ID: IJSRDV2I5431
Published in: Volume : 2, Issue : 5
Publication Date: 01/08/2014
Page(s): 822-826

Article Preview

Download Article