Optimal Online Data Dissemination for Resource Constrained Mobile Opportunistic Networks
Abstract: Delivery delay and communication costs are two conflicting design issues for mobile opportunistic networks with nonreplenishable energy resources. In this paper, we study the optimal data dissemination for resource constrained mobile opportunistic networks, i.e., the delay delay-constrained least-cost cost multicasting in mobile opportunistic networks. We formally formulate the problem and introduce in a centralized heuristic algorithm which aims to discover a tree for multicasting, in order to meet the delay constraint and achieve low communication cost. While the above algorithm can be implemented by each individual node, it is intrinsically centralized ntralized (requiring global information) and, thus, impractical for real-world real implementation. However, it offers useful insights for the development of a distributed scheme. The essence of the centralized approach is to first learn the probabilities to deliver liver the data along different paths to different nodes and then decide the optimal multicast tree by striking the balance between cost and delivery probability. In mobile opportunistic networks, even if the optimal routing tree can be computed by the cent centralized ralized solution, it is the “best� only on a statistic basis for a large number of data packets. It is not necessarily the best solution for every individual transmission. Based on the above observation, we develop a distributed online algorithm using opti optimal mal stopping theory, in which in each meeting event, nodes make adaptive online decisions on whether this