【作者】 蔡艳丽；

【导师】 李明禄；

【作者基本信息】 上海交通大学 ， 计算机应用技术， 2009， 博士

【摘要】 传感器网络在许多领域得到了广泛应用,例如环境监测、战场监测、健康护理等。一个传感器网络有大量的小的传感器节点组成,这些传感器节点由感知、处理和通信模块等组成。一方面,由于传感器节点可能是随机分布的,所以覆盖问题是传感器网络中一个十分重要的课题。传感器网络的覆盖反映了感兴趣的区域或目标的监测效果的好坏。另一方面,节能也是无线传感器网络中一个重要的问题。首先,大部分传感器节点只有有限的电量并且不可充电。其次,由于在很多情况下,环境恶劣或者是人力不可达到的,很难去更换传感器节点的电池。在本论文中,我们主要考虑以下问题。首先,我们定义并研究了基于目标的有向传感器网络中的寻找一个覆盖集的问题,即有向覆盖集问题(directional cover set problem (DCS))。与传统的具有全向感知能力的全向传感器相比,由于技术的限制以及价格因素的考虑,有向传感器只有有限角度的感知范围。一个有向传感器网络由大量有向传感器节点组成,此类有向传感器可以切换到不同的方向,从而扩展其感知能力以覆盖给定区域内的所有目标。与全向传感器相比,有向传感器的感知角度较小,甚至在布置后不能覆盖任何目标,因此我们需要对网络中的传感器进行调度使之朝向某些方向,从而覆盖所有的目标。DCS问题寻找一个覆盖集,该覆盖集为可以覆盖所有目标的有向传感器的方向的一个子集。我们证明了DCS问题为NP完全问题,提出了两个算法并证明了其正确性。仿真结果表明了这些算法的性能。其次,我们定义并研究了基于目标的有向传感器网络中的寻找多个可相交覆盖集、且为每个覆盖集分配一段工作时间,从而最大化网络寿命的问题,即多重有向覆盖集问题(multiple directional cover sets problem (MDCS))。在MDCS问题中,我们把网络中传感器的方向组织到可相交的子集中,其中每个子集都是一个覆盖集,并且给每个覆盖集分配一段工作时间。我们轮流在每个时刻只使用一个覆盖集。当我们使用一个覆盖集时,有方向在该覆盖集中的传感器处于活跃状态且工作在该方向上,其他所有的传感器都处于睡眠状态。我们证明了MDCS问题为NP完全问题,并提出了多个算法。通过仿真,我们详尽地比较了这些算法的性能。最后,我们为基于面积的全向传感器网络提出了一个精确的节能的覆盖控制算法,即基于面积的协作睡眠算法(area-based collaborative sleeping algo-rithm(ACOS))。该算法基于传感器的净覆盖面积,通过精确控制传感器节点的状态,最大化传感器网络的面积覆盖的同时也最小化能量消耗。传感器网络的面积覆盖用被覆盖区域的大小来衡量。一个传感器的净覆盖面积是指只被该传感器覆盖的区域的面积。同时,传感器节点间的协作也被引入该算法中,以平衡节点间的能量消耗。仿真结果表明在唤醒更少节点的情况下,ACOS算法可以提供比其他睡眠算法更好的覆盖。更多还原

【Abstract】 Sensor networks have emerged as promising platforms for many applications, such asenvironmental monitoring, battlefield surveillance, and health care. A sensor network mayconsist of a large number of small sensor nodes that are composed of sensing, processing andcommunicating components. On one hand, as sensors may be distributed arbitrarily, one ofthe fundamental issues in wireless sensor networks is the coverage problem. The coverageof a sensor network, represents how well the interested region or targets are monitored. Onthe other hand, power conservation is another important issue in wireless sensor networksdue to the following reasons. First, most sensor nodes have limited power sources and arenon-rechargeable. Also, the batteries of the sensor nodes are hard to replace due to hostileor inaccessible environments in many scenarios. In this dissertation, we mainly consider thefollowing problems.Firstly, we define and solve the problem of finding a cover set, called directional coverset problem (DCS), in target-oriented directional sensor networks. Unlike convectionalomni-directional sensors that always have an omni-angle of sensing range, directional sen-sors may have a limited angle of sensing range due to technical constraints or cost consid-erations. A directional sensor network consists of a number of directional sensors, whichcan switch to several directions to extend their sensing ability to cover all the targets in agiven area. Because a directional sensor has a smaller angle of sensing range than an omni-directional sensor or even does not cover any target when it is deployed, we need to schedulesensors in the network to face to certain directions to cover all the targets. The DCS is tofind a cover set that is a subset of directions of the sensors, in which the directions cover allthe targets. We prove the DCS to be NP-complete and propose two algorithms for the DCS.We also prove the correctness of the proposed algorithms. Simulation results are presentedto demonstrate the performance of these algorithms. Secondly, we define and solve the problem of finding non-disjoint cover sets and al-locating the work time for each of them to maximize the network lifetime, called multipledirectional cover sets problem (MDCS), in target-oriented directional sensor networks. InMDCS, we organize the directions of sensors into non-disjoint subsets, each of which is acover set, and allocate the work time for each cover set. We alternately activate only onecover set at any time. When one cover set is activated, each sensor that has a direction in thiscover set is in the active state and works in this direction, while all the other sensors are inthe sleep state. We prove the MDCS to be NP-complete and propose several algorithms forthe MDCS. We compare the performance of these algorithms by simulations exhaustively.Thirdly, we propose a precise and energy-aware coverage control algorithm, namedarea-based collaborative sleeping (ACOS) algorithm, for area-oriented omni-directional sen-sor networks. This algorithm precisely controls the mode of sensors to maximize the areacoverage and minimize the energy consumption based on the net sensing area of a sensor.The area coverage of a sensor network is measured by the fraction of the region covered.The net sensing area of a sensor is the area of the region exclusively covered by the sensoritself. If the net sensing area of a sensor is less than a given threshold, the sensor will goto sleep. Collaboration is introduced to the algorithm to balance the energy consumptionamong sensors. Performance study shows that ACOS has better coverage of the surveillancearea while waking fewer sensors than other state-of-the-art sleeping algorithms.更多还原