Probability-based adaptive forwarding strategy in named data networking

Forwarding strategy is an important research problem in named data networking (NDN). A probability-based adaptive forwarding (PAF) strategy is introduced in this paper. Ant colony optimization is customized to a dynamic NDN environment to compute the selection probabilities. In addition, we use a statistical model in PAF to compute timeout for the retransmission mechanism at the NDN layer. PAF also provides network operators a number of parameters to tune for different network scenarios. Simulation results show PAF can achieve load balance and is adaptive to network condition changes.