Analytical model for probabilistic network coding with delay fairness in multihop wireless network

Abstract

In this work, we present an analytical study of the average delay and network throughput for packet dissemination using network coding in multihop wireless network scenario, where the generation of the packets is a stochastic process. The main challenge for the relay when it receives a packet is whether to wait for a coding opportunity and therefore reduce the network congestion or to send the packet directly without coding and reduce the packet delay. So, we propose a probabilistic approach for the relay when it receives a packet, and then we develop an analytical framework to address the trade-off between the throughput and the delay, we investigate the condition to maintain the stability of the system. We also provide the optimum transmission probability that achieves the minimum fair delay between the two sources and results in an optimum throughput. In the symmetric case (e.g. two flows with the same rate), we show that the optimum fair delay can be achieved with probability of transmission 0.5. We also show that despite of the flow data rate, using this probability in symmetric flows will result in an almost 33 per cent improvement in the bandwidth consumption and in an equal hop delay for both flows that is 0.5/λ where λ is the average flow data rate. Moreover, for asymmetric rate flows, we provide the optimum transmission probability and its corresponding fair delay and throughput improvement. We carry out simulation to verify our analytical model.