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, the authors 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.