Stochastic Time Evolving Routing Protocol based on Energy and Delay Metrics

In this article, we introduce a Quality of Service (QoS) routing algorithm based on dynamic state-dependent policies. The proposed algorithm uses a bio-inspired approach based on trial/error paradigm to optimize two QoS different criteria: Energy and end-to-end delay. Our proposal, called EDEAR "Energy and Delay Efficient Adaptive Routing", uses a paradigm based on routesʹ exploration. In this phase, we collect information in terms of energy and delay by using continuous learning parameters on the network and update routing table maintained at each node of the network. This phase of exploration has been optimized by proposing a new algorithm based on multipoint relay for energy consumption, thus reducing the overhead generated by the packets exploration. Numerical results obtained with NS simulator for different levels of trafficʹs load and mobility show that EDE