Adaptive scheduling in wireless sensor networks based on Potts model

Recent advances in wireless sensor network´s technology have developed using this technology in various fields. For the importance and intense application of these networks, many efforts and researchers have been done to confront challenges. In this paper, to conquer one of the most important challenges of these networks, that is the limitation in energy resources, an adaptive scheduling algorithm based in Potts model was applied. According to this model, for every element of a system, q different states are considered. Each element converts its state to a new state or remains in that state due to its current state and its adjacent neighbours and with the effect of environment. In this project, this model was used in wireless sensor networks such that each sensor node is considered as an element of sensor network system and three active, inactive and standby states are defined for that node, which it selects one of these three states according to its current state and neighbours and environment effect and adapts its activity with the environment in a way that the least energy to be consumed. By comparing this algorithm and similar algorithm (with two states), it is observed that in identical conditions, Potts model with three states represents better results and more lifetimes for network.