Topology maintenance of Ad Hoc wireless sensor networks with an optimum distributed power saving scheduling learning automata based algorithm

The scheduling of nodes in a wireless Ad Hoc Sensor network is getting them to alternate between the sleeping and active mode. If this process of adjusting the wake/sleep schedule of all nodes that is, a topology management mechanism, is maintained in an optimal manner, further energy can be saved, which will have a direct impact on prolonging the lifetime of the network. So, in this paper a distributed power saving coordination algorithm for multi-hop ad hoc wireless networks based on learning automata without significantly diminishing the quality of services of the network such as capacity or connectivity of the network is proposed such that all nodes in the network that are equipped with learning automata don't need to be synchronized with each other. Learning automata abilities such as low computational load, usability in distributed environments with ambiguous information, and adaptability to changes via low environmental feedbacks are all, factors that can provide the mentioned optimal manner for nodes; and cause better fitness with local techniques in ad hoc wireless networks. The proposed protocol, SpanLAQ, consists of two phases: coordinator announcement and coordinator withdrawal which are based on learning automata to ensure fairness, and to make local decisions on whether a node is going to sleep or joining to a forwarding backbone as a coordinator. So, using learning automata with passing of time causes a decrease in energy consumption and an improvement of the network lifetime in SpanLAQ protocol with an 802.11 network in power saving mode, in comparison to other similar protocols such as Span and without any topology management protocols. Simulation results with a practical energy model also show that the above result is being achieved with some improvements in capacity, connectivity and communication latency.