Comparative Evaluation of Genetic Algorithms for Force-Based Self-Deployment of Mobile Agents in MANETs

This paper compares two self-deployment algorithms for mobile agents in wireless mobile ad-hoc networks based on genetic algorithms using potential field techniques. The algorithms are designed for real-time deployment of mobile agents over an unknown terrain. Each mobile agent exchanges its genetic information of speed and direction encoded in its chromosomes with the neighboring nodes. The fields are constructed such that each mobile agent is repelled both by obstacles and other nodes, thereby forcing the neighbor agents to spread throughout the geographical area. Comparative evaluation of the two approaches is based on the metrics such as area coverage, deployment time and the distance traveled by the mobile agents.