摘要
无线传感器网络的应用前景广阔,能够广泛应用于军事、环境、智能家居等领域。国内外相关研究多数局限于所有传感器节点都是静止的情况,不满足某些需要移动节点的应用,比如检测野生动物的生活,追踪病人的心跳情况等,在这些应用中节点总是在不断地慢速运动,它们需要无线传感器网络中存在可移动的节点。移动节点的引入不但可以拓宽类似于上述的网络应用范围,而且可以动态调整网络结构,优化网络的性能——能耗、延迟、生命周期等。因此移动节点的引入对无线传感器网络具有重要意义,作为该引入的前提——无线传感器网络中移动节点的路径规划,将成为亟待解决的问题。
由于无线传感器网络的应用环境特殊、资源受限等特点,GPS等高端导航设备难以适用于该网络中移动节点路径规划问题,例如在太空探索或者地下煤矿应用中,GPS信号无法覆盖。无线传感器网络本身是一种密集感知型网络,其自身具备了进行路径规划的条件,然而由于该网络资源受限,路径规划不再纯粹是搜索算法问题,而是一个需要兼顾路径规划优度与网络性能的问题。
本文将无线传感器网络中的路径规划问题划分为四个主要环节：无线传感器网络布局、定位参考点选择、定位算法与路径搜索算法,这四个主要环节首先是路径规划问题的必要组成部分,缺少任何一项均无法解决实际应用中的路径规划问题；其次,这四个主要环节之间存在着相互促进的内联关系,这些关系从整体上进一步提升了路径规划算法的性能。
本文主要工作与贡献集中于以下几点：
1.在网络布局环节中,针对应用环境分别提出了布局指导策略LG(Layout Guide)、布局优化策略LO(Layout Optimization)。在对LG的研究中发现,传感半径与通信半径的比值λ能够影响一种布局的有效覆盖率,它可以指导用户根据给定的λ值,选择最优的布局方法；LO策略可以对网络功率级进行调整,从而在不影响网络度值的前提下,减少网络能耗。
2.在定位参考点选择环节中,本文提出了一种参考点选择算法CRS,采用“多轮分配”机制在最终搜索解的优度与计算复杂度之间较好地做了一次权衡。实验结果表明,CRS算法得出的定位覆盖度要较随机选择与SHARP算法分别高41.7%、38.3%左右。
3.在定位算法环节中,本文提出了一种基于模糊识别的定位算法FTLM,该算法用若干样本点将未知点“约束”于某一个小区域内,进而估算未知点的坐标,FTLM执行过程简单,无需大量参考点参与计算,节约了能量与带宽。此外FTLM可以通过设置样本点的个数,灵活地调节定位精度与计算复杂度以满足应用需求,该算法尤其适用于本文研究的路径规划问题。实验结果表明计算复杂度为O(n)的FTLM算法对应的定位精度要比计算复杂度为O(nm)的SBL算法约高7.3%,其中m为参考点个数。
4.在路径搜索算法环节中,本文提出了一种基于无线传感器网络的路径搜索算法PS。该算法将传感器节点作为“路标”,通过数据包的传递建立候选路径,在路径选择时,兼顾了路径长度与无线传感器网络的生命周期,该算法执行简单、计算复杂度低,适用于无线传感器网络的路径规划中。实验结果表明PS算法的一次执行延迟较栅格法低4.2s,PS算法对应的生命周期较高于栅格法。
5.将上述各个环节有机地结合起来,形成了基于无线传感器网络的路径规划算法WPP,并通过大量实验,测试了该算法内部各环节的关联性及算法整体性能。测试结果表明通过调节算法的四个参数,可以改变WPP算法的各项性能,以达到用户需求。
本文工作有效地解决了路径规划优度与无线传感器网络资源受限的矛盾。虽然最终的路径规划结果不是最短距离路径,但是相比于某些特定应用中所收获的更长的生存周期、较低的计算复杂度仍然是值得的。本文的研究特别适合于无大规模障碍物群的环境以及对网络生命周期要求高的相关应用,本文的研究成果为无线传感器网络中移动节点的路径规划提供了新的思路。
Wireless sensor networks has a wide application fields, it can be used in military affairs, environment supervision, samrt home and so on. Most of correlation researches are limited to immobile network, and they are uncomfortable for some mobile applications such as inspecting of wild animal's living and tracing of patients'heartbeat, in these applications, the nodes always mobile at a low speed, and they need mobile nodes in WSNs. The introduced mobile nodes can not only advance the ability of service but also can adjust the structure of WSNs to optimize its performance----energy consumption, latency and lifetime. So, the mobile nodes have an important signification to WSNs, and the path planning of mobile nodes based on WSNs has to be solved firstly.
WSN has its characters such as special application environment, restricted resource and so on, so, some well worked navigation devices such as GPS can hardly be used. For example, while in outer space or underground colliery applications, the GPS signal can't work. WSNs is a kind of denseness and sensor network, it has the terms of path planning. However, due to WSNs'restricted resource, the path planning is not a simple search problem anymore, but a problem which needs to be given attention to the result of planning and network's performance.
The algorithm of path planning is divided into four parts in this paper:network's layout, reference nodes' selection, localization model and path searching. The four parts are the necessaries of path planning firstly; there are inner relations among them secondly, the relations can advance the performance of path planning ulteriorly.
The main works and contributions of the paper are focused on the following aspects:
1. In the research of network's layout, two strategies are promoted:LG (Layout Guide) and LO (Layout Optimization). In LG, the ratioλbetween sensor radius and communication radius can change the efficiency cover ratio, it can guide people to layout the network according to the givenλ; In LO, the power levels are adjusted to decrease the energy consumption in condition of unchanging the degree of network.
2. In the research of reference nodes'selection, CRS is advanced, it takes "multi-turns" mechanism to balance the advantage of planning result and complexity. The result of experiments shows that, the coverage ratio of CRS is 41.7% and 38.3% higher than random selection and SHARP selection.
3. In the research of localization model, an algorithm called FTLM is advanced based fuzzy recognition. In FTLM, the unknown node is limited into a small area by setting several swatch nodes, the procedure is simple and doesn't need larger number of reference nodes, it can save energy and bandwidth. Moreover, the precision and complexity can be adjusted by the set of swatch nodes to satisfy applications' requirements. It is very suitable for the path planning research in this paper. This result of experiments show that, the complex degree of FTLM is O(n) and its localization precision is 7.3% more than SBL whose degree is O(nm), in which, m is the number of reference nodes.
4. In the research of path search, we promote a algorithm based wireless sensor networks which is called PS. In this algorithm, the sensors are considered as the guides, and the paths are constructed by packets'communication. While in path selection, we give attentions to the lifetime of WSNs and the length of the path, the PS algorithm is simple and it has a low computing complex. The result of experiments shows that, the latency of PS algorithm is 4.2s lower than gridding algorithm, and PS can cause a longer lifetime than gridding.
5. Finally, a path planning algorithm called WPP based WSN is advanced by banding the above researches together. A lot of experiments are performed to test the inner relations and the algorithm's performance. The result shows that, the performance of WPP can be adjusted to satisfy the requirements of users by changing the four parameters in WPP.
This paper solves the conflicts between the path planning result and the restricted resource in WSNs. Although, the finally planning result maybe not the shortest path, but, we think it is more valuable to get a more lifetime and low planning complexity. The result of this paper is more suitable for the applications which have no block clusters or requires high lifetime. The researches of this paper provide a novel way for the path planning based WSNs.
引文
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