Optimal Forwarding in Delay Tolerant Networks with Multiple Destinations
For network engineers designing energy-efficient routing protocols in delay tolerant networks, this work provides a theoretically grounded forwarding policy that balances delay and energy, though the assumption of perfect state knowledge limits practical applicability.
The paper studies the trade-off between delivery delay and energy consumption in delay tolerant networks with multiple destinations, deriving an optimal closed-loop forwarding policy and an asymptotically optimal open-loop policy via fluid approximation, which performs close to optimal in finite networks.
We study the trade-off between delivery delay and energy consumption in a delay tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the packet and the number of destinations that have received the packet. We formulate the problem as a controlled continuous time Markov chain and derive the optimal closed loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ODE (i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed loop policy.