Research On The Sociality Of Nodes Based Mobility Model In Mobile Ad Hoc Network

Mobile Ad Hoc Network (MANET) is a collection of wireless mobile nodes forming a multihop and self-organized wireless network. MANET has high dynamic topology and has no fixed network infrastructure. Therefore, the network has the merits of flexibility, fast networking and so on. It is applied to military affairs and disaster-saving fields broadly.Mobility models which are used to describe the movement patterns of nodes are an important compotent of the network simulator in MANET. The choice of mobility models and the parameters of models have an important impact on the performace of network protocols. Simulation results obtained with unrealistic movement models may do not correctly reflect the true performance of the protocols. Therefore, realistic mobility models which describe nodes movement correctly are essential in simulating mobile ad hoc network.In real scenarios, mobile devices are usually carried by humans, so the movement of such devices is necessarily based on human decisions and socialization behaviour. Sociality is one of the most important characteristics of nodes movement in real scenarios. Mobility models which consider the sociality of nodes are better to map reality than the random mobility models. However, there are few parameters which measure the sociality of nodes, and the majority of existing mobility models does not provide realistic movement in MANET. In this paper, we propose two parameters which can be used to measure the sociality of the mobile nodes, and the Sociality of Nodes based Mobility Model (SNMM) is designed and evaluated. The main contributions of this paper are as follows:(1) Analyzing the movement traces from real scenarios, we demonstrate that the complementary cumulative distribution function of contact duration, which follows an approximation power law, familiarity-regularity distribution is consistent with the characteristics of the relationships in real scenarios. Furthermore, from the view point of sociology, the reasons that caused the characteristics of these two distributions were analyzed. The results show that these two distributions can be used to measure the sociality of real traces effectively.(2) SNMM is proposed to describe the socialization behaviour in real scenarios. In the model, we consider the relationship between nodes while considering the choice probability and the pause time in the different geographical space. In addition, we aso consider geographical distance affects the relationship between nodes.(3) Building a network platform for mobility models, we use the complementary cumulative distribution function of contact duration and familiarity-regularity distribution to measure the sociality of nodes in SNMM. Simulation results demonstrate that SNMM is a proper choice of providing realistic mobile scenerios of network simulations.