A Topographic-Awareness and Situational-Perception Based Mobility Model with Artificial Bee Colony Algorithm for Tactical MANET

Jinhai Huo, Bowen Deng, Shuhang Wu, Jian Yuan, Ilsun You

A topographic-awareness and situational-perception based mobility model with path optimization for tactical MANET is proposed in this paper. Firstly, a formalized process is constructed to generate a random acceleration on nodes as the disturbance caused by small-scale topographic factors in the battlefield. Secondly, a path optimization method with the artificial bee colony algorithm is introduced to mimic the trace planning when the nodes possess the terrain information of battlefield. Thirdly, a topographic-awareness based bypass strategy is proposed to simulate the action of nodes facing large-scale terrain factors in the case when the terrain information is lacking. Finally, a situational-perception based avoidance strategy is built to simulate the process of cognition and decision when there is an encounter with the enemies on the march. The mobility model consists of the four parts above and imitates the dynamic characteristics of tactical nodes in military environment.