Abstract:

Compared to traditional random mobility models, a social-based mobility model was proposed, aiming to generate synthetic traces to capture the statistical properties detected from real traces. the driving force of complicated social behaviors from an evolutionary point of view was explored. A genetic algorithm-based mobility model(GAMM) was presented. Using Gain/Cost Ratio as the metric of trace's fitness, complicated movement patterns were emerged from generations of evolutions. Explorer's model and transportation model were presented to show the expandability of GAMM. The influence of social-based mobility model on MANETs network protocols are also investigated by simulation.

Key words: mobility model, genetic algorithm, social network