Maximising lifetime of wireless sensor networks using distributed scheduling algorithms with adjustable sensing range.
Optimizing the energy consumption in wireless sensor networks has recently become the most important performance objective. In this project we define the lifetime of a wireless sensor network as the amount of time that the network can effectively cover the targets of interest. Having all the sensors active at all times would ensure coverage but would also significantly reduce the network lifetime as the nodes would discharge quickly. A viable approach taken to maximize the network lifetime is to make good use of the overlap in the sensing regions of individual sensors caused by the high density of deployment. We design a scheduling mechanism in which only a subset of the sensors can be active at anyone time, while all other sensors are put to sleep. The members of this active set (cover set) are periodically updated to keep the network alive for a longer duration of time. Also, for each of the cover sets, the goal is to smoothly adjust the sensing range such that a minimum sensing range can be maintained while meeting the target coverage objective. We propose a reliable distributed scheduling algorithm which can smoothly adjust the nodes' sensing range while providing optimal target coverage with the minimal set of active sensors. From the simulation results, the improvement in network lifetime of the Distributed Scheduling Algorithm with adjustable sensing range over the Load Balancing Protocol for sensing with fixed sensing range is about 26% on average in the linear energy model and about 50% on average in the quadratic energy model.