Iterative search with emulating nodes' local movement on range-free sensor network localization

摘要

This paper proposes an iterative evolutionary algorithm with emulating nodes' local movement for searching the best localization accuracy in range-free scenario. All localization methods face a trade-off between the solution quality and computation cost. When sensor network localization in range-free scenario is considered as a constraint satisfaction problem, localization will reach the highest accuracy but with huge computation complexity. To solve the constraint satisfaction, some characteristics that only exist in range-free localization problem are utilized as heuristics in the search of nodes' positions. They are summarized as simple and complex movement to emulate nodes' local movement, and proved to be effective to find a suitable searching direction and jump out of local-minimums existing in the localization. Those emulations are then included in each iteration of a two-objective evolutionary algorithm minimizing the number of node-pairs with violated connectivity, as well as the value quantitating how worse of the violations. Simulation results show that the proposed algorithm can greatly decrease the reach high-accurate positions within limited iterations.