Bio-inspired and biased random walk routing in dense and lossy wireless sensor networks

This paper proposes a bio-inspired routing algorithm to achieve low mean delay and energy efficiency. Based on the intelligent behavior of bacteria E.Coli on searching nutrition food, we build the gradient field in network with the maximum gradient concentration at the sink. Packets modeled as bacteria move to the sink based on the mechanism: run and tumble which is modeled as biased random walk. When packets are moving on increasing-gradient walks, the routing trajectory is right to reach the sink; otherwise, packets take the chance to change direction (tumble) to find the right direction toward the sink. Simulation results show that the proposed algorithm achieves the low mean delay and energy efficiency with respect to the shortest path algorithm.