Recent advances in wireless and micro-electronics technologies have made these technologies functionally accessible and available to a wide range of different applications. One of the fast growing field?s is wireless sensor networks technologies, whose applications from military, such as monitoring enemy and military consignments, to traffic surveillance, environment and building structures monitoring. An important characteristic of sensor networks is the limited power supply of the sensor nodes. These nodes are usually powered by batteries, and therefore it may not be possible to recharge or replace the batteries after their deployment.
This proposed research aims at addressing the maximal lifetime scheduling problem for sensor surveillance networks in a dynamic environment in which the positions of the targets are dynamic and each sensor has different surveillance range. Specifically, the research involves an exploratory investigation of finding a novel family of efficient scheduling algorithms (that offer a wide range of tradeoffs among cost, scalability and energy consumption) for a sensor surveillance network. Its purpose is to monitor a set of moving targets, such that all the targets are being monitored by the sensors in the network at any point in time and at the same time the lifetime of the sensor surveillance network is maximized. In this scheduling algorithm, a sensor can switch off to save energy when it is not its turn to monitor a target. The proposed project also develops distributed monitoring mechanisms and scanning methods to obtain a sensor?s locations information. An analytical framework to theoretically evaluate the scheduling solution from the point of view of tradeoffs between cost, scalability and energy consumption is also proposed. The analytical results will be evaluated by extensive simulations and experimental measurements.
