A low complexity and high speed gradient descent based secure localization in Wireless Sensor Networks

Abstract

In many applications of Wireless Sensor Networks (WSNs) such as monitoring applications or routing, localization is one of the important issues that affect directly the network quality of operation. Secure localization in WSNs needs to detect malicious nodes and exclude them in order to avoid deception by attackers. Accurate and appropriate methods that are usually iterative algorithms such as gradient descent, least median square (LMdS) and voting based secure localization have been introduced in the recent literature. Gradient descent based secure localization has better performance in terms of convergence speed and accuracy while have the minimum complexity compared to the other methods, however, still more convergence speed is needed for real-time applications. In this paper, a new gradient based method has been introduced which has higher convergence speed among all existing algorithms and the probability of fault for this algorithm is less than other algorithms. The other advantage of the proposed method is its low complexity in comparison to the other methods and its capability to be implemented in hardware. Simulation results show that the introduced algorithm's convergence speed is about 10 times more than the gradient descent algorithm with same localization error.