CWDV-Hop: A Hybrid Localization Algorithm With Distance-Weight DV-Hop and CSO for Wireless Sensor Networks

摘要

Localization problem is a hot topic in the field of wireless sensor networks. The distance vector-hop (DV-Hop) is a typical range-free localization algorithm which is widely used in many applications owing to its advantages such as simplicity, feasibility, low cost, and less hardware requirements. However, its localization error is relatively large. In this article, a novel approach designated as CWDV-Hop was presented to improve the localization accuracy. In the first step of CWDV-Hop, the distance-weighted hop distance was calculated by introducing the new defined distance-weighted factor and single-node hop distance, which can effectively reduce the impact of curved path on the estimation of average hop distance. Furthermore, the locations of unknown nodes are obtained by utilizing two-dimensional hyperbolic scheme. At last, Chicken Swarm Optimization (CSO), which is a kind of nature inspired algorithm, is introduced to optimize the locations of unknown nodes. In comparison with the traditional DV-Hop approach, the localization accuracy of CWDV-Hop can be raised by 53.6%, 39.5% and 53.1% for the square, $X$ -shaped and $O$ -shaped random distribution environment respectively, with the time complexity slightly gained. It demonstrates the effectiveness of CWDV-Hop not only in the isotropy network, but also in the anisotropy network with holes or other uneven distributions.