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The mobility pattern of users is one of the distinct features of vehicular ad hoc networks (VANETs) compared with other types of mobile ad hoc networks (MANETs). This is due to the higher speed and the roadmap-restricted movement of vehicles. In this paper, we propose a new analytical mobility model for VANETs based on product-form queueing networks. In this model, we map the topology of the streets and the behavior of vehicles at both intersections and different parts of the streets onto different parameters of a BCMP¹ open queueing network comprising M/G/∞ nodes. This model represents a sparse situation for VANETs. To include the effect of dense situation on the mobility model, we modify the proposed queueing network as a new one comprising nodes with state-dependent service rates, i.e., M/G(n)/∞ nodes. With respect to the product-form solution property of the proposed queueing networks, we are able to find the spatial traffic distribution for vehicles at both sparse and dense situations. Furthermore, we are able to modify the proposed queueing network to find the lower and upper bounds for the probability of connectivity. In the last part of this paper, we show the flexibility of the proposed model by several numerical examples and confirm our modeling approach by simulation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a general mobility model suitable for wireless multimedia networks. Our model is based on splitting a region into subregions. Furthermore, we make an analogy between subregions as well as their inter-connections with a multi-class Jackson queueing network comprising of infinite-server nodes. The main attribute of such a network is due to its product-form stationary distribution. Using this model, we are able to obtain a closed analytical form for the spatial traffic distribution corresponding to a specific number of network-connected users with different classes of service and mobility in a typical region. Also, we show the flexibility obtained by the proposed mobility model in representing some general distributions such as sum-of-hyper-exponentials (SOHYP), hyper-Erlang and Cox which were previously suggested to model mobility-related statistical parameters, e.g., cell dwell time and channel holding time. Finally, we apply the proposed model to a few mobility scenarios and obtain the resultant active user's location density. [ABSTRACT FROM AUTHOR]