A Swarm Intelligence Technique for Link Monitoring Problems in Wireless Ad Hoc Networks

A swarm intelligence-based optimization approach, called JPWCV, is developed to solve the link monitoring problems in wireless ad hoc networks (WANETs). The minimum weighted connected vertex cover problem (MWCVCP) in graph theory plays a virtual backbone for the link monitoring problems in WANETs. The proposed JPWCV approach incorporates the jumping particle swarm optimization approach and a local search method based on weight and cost ratio metrics to get the best solution for the MWCVCP. This technique also uses a greedy procedure to make the weighted vertex cover into a connected one. Simulation results on extensive datasets suggest the notable improvement of JPWCV over existing algorithms in the context of less computational cost and execution time. The statistical analysis, grounded in the ranking of algorithms, further substantiates the superior performance of JPWCV over the compared algorithms.