Practical Routing in a Cyclic MobiSpace

A key challenge of routing in delay-tolerant networks (DTNs) is finding routes that have high delivery rates and low end-to-end delays. When future connectivity information is not available, opportunistic routing is preferred in DTNs, in which messages are forwarded to nodes with higher delivery probabilities. We observe that real objects have repetitive motions, whereas no prior research work has investigated the time-varying delivery probabilities of messages between nodes at different times during a repetition of motion of the nodes. We propose to use the expected minimum delay (EMD) as a new delivery probability metric in DTNs with repetitive but nondeterministic mobility. First, we model the network as a probabilistic time-space graph with historical contact information or prior knowledge about the network. We then translate it into a probabilistic state-space graph, in which the time dimension is removed. With the state-space graph, we apply the Markov decision process to derive the EMDs of the messages. We propose an EMD-based probabilistic routing protocol, called routing in cyclic MobiSpace (RCM). To make RCM more practical, we show a simple extension that reduces routing information exchanged among nodes. We perform simulations with real and synthetic traces. Simulation results show that RCM outperforms several existing opportunistic routing protocols.