Antnet Pheromone-Based Stochastic Multipath Routing Protocols using Hidden Markov Models for Energy Enhancement in Wireless Sensor Networks

Abstract

Evolving of Wireless Sensor Network (WSNs) a type of infrastructure-less networks by tens, hundreds, thousandths, or billions of devices that provide indispensable services for the phenomenon study become more used in many industries with many applications. Forest fire tracking, environmental monitor, healthcare, seismic and volcano surveillance, Internet of Devices and everything, and now internet of vehicles is the new trend of network of devices. These devices and things mostly exchange data between many sources and destinations using a special computer mechanism, the routing protocols to optimized the using of network and devices resource to retrieve their path.Additionally, constraints like network capabilities, storage, computational, energy consumption, and so on, many researches were conducted to proposed routing protocols that limited the network effort and the all of things’ interaction to extend the lifetime. In the present paper Antnet routing protocol which is classed in the Ant Colony Optimization heuristic is inspired on the ants behavior to define a stochastic based model permitting to predict the ants path to reach final destination using biological substance deposit on all visited paths to establish a new form of routing table that can be exploit for the purpose of the optimization objective. Conducted experimentation and obtained results show that the using of the pheromone in multiple paths by ants during trips permit to conserve effectively the available resources, reduce control overhead, residual overall, and optimize the energy consumption. Our new routing mechanism based on stochastic models performs well that compared existing routing.