Fast triangle flip bat algorithm based on curve strategy and rank transformation to improve DV-Hop performance

Abstract

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

A modified error-oriented weight positioning model based on DV-Hop

“…Sharma [39] presented the concept of co-planarity to reduce location errors caused by the anchor nodes which are coplanar, and used the GA solved the weight model. Similarly, Cai [40] presented the fast triangle flip bat algorithm with curve and rank transformation strategy to optimize DV-Hop positioning model. For the problem of uneven distribution of nodes due to the battery life of the nodes, Kanwar [41] presented to localize the newly deployed nodes and use GA to solve the model.…”