A dynamic flocking algorithm with a restrictive partnership model to support mobile ad hoc networks

This paper presents an improved flocking algorithm to increase the connectivity of a mobile ad hoc network using autonomous and intelligent agents. Flocking algorithms usually aim to simulate realistic movements of a group of agents. In this paper, however, agents use a flocking algorithm to find a solution to a computationally very difficult optimization problem in real-time as the topology of the network changes due to the mobility of users. In the improved flocking algorithm, agents select their interaction partners based on the Gabriel Graph and adjust their flocking behavior parameters dynamically. A simulation study is conducted to compare the performance of the improved flocking algorithm with a previous algorithm. Computational studies show that the recommended strategies are quite effective.