SGER: A Novel Optimization Scheduling Technique for Sensor Surveillance Networks

无线和微电子技术的最新进展使得这些技术在功能上可访问并可用于广泛的不同应用。快速增长的领域之一？无线传感器网络技术是无线传感器网络的核心技术，其应用范围从军事领域，如敌情监测、军事演习，到交通监控、环境监测、建筑结构监测等。传感器网络的一个重要特点是传感器节点的能量有限。这些节点通常由电池供电，因此，它可能无法充电或更换电池部署后，提出的研究旨在解决的最大生命周期调度问题的传感器监视网络中的动态环境中的目标的位置是动态的，每个传感器有不同的监视范围。具体而言，该研究涉及到一个探索性的调查，发现一个新的家庭的高效调度算法（提供了广泛的权衡成本，可扩展性和能源消耗）的传感器监控网络。它的目的是监视一组移动目标，使得网络中的传感器在任何时间点监视所有目标，同时最大化传感器监视网络的寿命。在这种调度算法中，传感器可以关闭，以节省能源时，它不是轮到监测目标。拟议的项目还开发分布式监测机制和扫描方法，以获得一个传感器？的位置信息。一个分析框架，从理论上评估调度解决方案的角度之间的权衡成本，可扩展性和能源消耗。分析结果将通过广泛的模拟和实验测量进行评估。

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.