A Novel Path Planning Model Based on Nested Regular Hexagons for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

Abstract

In many wireless sensor networks (WSNs) applications, the relevant sensor node's location information is crucial in determining where the event or situation occurs. Therefore, localization is one of the critical challenges in WSNs. Mobile Anchor Node-Assisted Localization (MANAL) is one of the promising solutions for the localization of statically deployed sensors. The main problem in MANAL is that the path planning of the Mobile Anchor (MA) node should be done so that the network's localization error will be minimal and that all unknown nodes in the network are covered. This paper proposes a new path planning approach called Nested Hexagons Curves (NHexCurves) for MANAL. NHexCurves guarantees that it will receive messages from at least three non-collinear anchors to locate all unknown nodes in the network. The proposed model has been compared to six different path planning schemes in the literature using Accuracy Priority Trilateration (APT) under different evaluation criteria. In these comparisons, first of all, localization errors of the models are compared using some statistical concepts. Secondly, the variation of the localization error according to parameters such as resolution (R) and the standard deviation of noise (sigma) is observed. Then, with similar approaches, the standard deviation of errors, localization ratio, scalability performances, and path lengths of the models are examined. The simulation results present the advantages of the proposed NHexCurves algorithm over other similar algorithms.