PPMA, a probabilistic predictive multicast algorithm for ad hoc networks

Ad hoc networks are collections of mobile nodes communicating using wireless media without any fixed infrastructure. Existing multicast protocols fall short in a harsh ad hoc mobile environment, since node mobility causes conventional multicast trees to rapidly become outdated. The amount of bandwidth resource required for building up a multicast tree is less than that required for other delivery structures, since a tree avoids unnecessary duplication of data. However, a tree structure is more subject to disruption due to link/node failure and node mobility than more meshed structures. This paper explores these contrasting issues and proposes PPMA, a Probabilistic Predictive Multicast Algorithm for ad hoc networks, that leverages the tree delivery structure for multicasting, solving its drawbacks in terms of lack of robustness and reliability in highly mobile environments. PPMA overcomes the existing trade-off between the bandwidth efficiency to set up a multicast tree, and the tree robustness to node energy consumption and mobility, by decoupling tree efficiency from mobility robustness. By exploiting the non-deterministic nature of ad hoc networks, the proposed algorithm takes into account the estimated network state evolution in terms of node residual energy, link availability and node mobility forecast, in order to maximize the multicast tree lifetime, and consequently reduce the number of costly tree reconfigurations. The algorithm statistically tracks the relative movements among nodes to capture the dynamics in the ad hoc network. This way, PPMA estimates the node future relative positions in order to calculate a long-lasting multicast tree. To do so, it exploits the most stable links in the network, while minimizing the total network energy consumption. We propose PPMA in both its centralized and distributed version, providing performance evaluation through extensive simulation experiments.