Abstract

In this paper, we investigate the self-similarity characteristic of MANET(Mobile Ad-hoc NETworks) traffics through simulations and then construct a fuzzy logic controlled mobility model according to the traffic feature to optimize the network performance. First, based on the generated traffics using OPNET, the self-similarity of MANET traffics has been verified with a qualitative analysis. Then, by exploring the relation between the self-similarity indicator, i.e., Hurst and some network performance metrics, such as Packets Delivery Ratio(PDR), Average Transmission Delay(ATD) and nodal Average Moving Speed(AMS), a fuzzy logic controller is designed to make the mobility model adaptively work in order to output satisfied performance. By online estimating the self-similarity of incoming traffics using R/S analysis, the Packet Size(PS) and AMS of each vehicle could be intelligently adjusted to maximize the PDR and minimize the experienced ATD. Numerical results indicate that our proposed mobility model, compared to the classic mobility model RWP(Random WayPoint), has a better performance in terms of PDR and ATD.

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