Reliable Multicast Clouds

Multicast group communications are essential for armed forces to effectively coordinate and execute missions in live theater, and given all the dynamics that a network can be subjected to in mission-critical situations (i.e., any combination of fast fading, slow fading, frequency jamming, network congestion, mobility), ensuring an appropriate level of network fidelity for supporting reliable communications becomes a difficult wireless networking problem. We argue for designing tunable reliability more explicitly into the act of topology construction based on the severity of forecasted dynamics in the network. This paper studies the number of nodes in the network supporting multicast traffic for a group of nodes, with more nodes supporting multicast traffic, the number of available redundant paths increases, enhancing reliability. We investigate the fundamental tradeoff of the amount of nodes supporting multicast communications and the gains in the number of node-disjoint paths among nodes in the multicast group. Traditionally, wired and wireless approaches to multicast focus on constructing some sort of tree-based topology with the benefit of having the minimum amount of resources allocated and a simplified routing protocol without redundant paths. Others have argued for ring-based topologies, augmented trees or rings allowing for alternate paths, and others have explored the mesh-based routing problem for multicast. We formulate a set of mixed integer linear programs (MILPs) for determining the nodes participating in the multicast group, we denote the set of nodes supporting multicast traffic as the multicast cloud. We investigate the fundamental tradeoffs of the fidelity of the cloud over a wide-range of parameters, accounting for various types of multicast topology allocation strategies (e.g. tree- and meshed-based approaches). We find that many nodes are needed to construct a single path among all nodes in a multicast group, but the cost for an additional node-- isjoint path requires a fraction of additional nodes. We characterize this sublinear cost growth in terms of the number of nodes needed to provide connectivity to the cloud, and we characterize how the diameter of the cloud (i.e., hop across) decreases as more nodes participate in group communications.