可充电传感网中移动式能量补给及数据收集策略研究  

Mobile Energy Replenishment and Data Collection Strategies in Rechargeable Sensor Networks

作　　者：刘俊辰[1] 梁俊斌[1] 王田[2] 蒋婵[1] 李陶深[1] LIU Jun-chen LIANG Jun-bin WANG Tian JIANG Chan LI Tao-shen(School of Computer and Electronic Information, Guangxi University, Nanning 530004, China College of Computer Science Technology, Huaqiao University, Xiamen 362021, China)

机构地区：[1]广西大学计算机与电子信息学院,南宁530004 [2]华侨大学计算机科学与技术学院,厦门362021

出　　处：《计算机科学》2016年第10期107-113,共7页Computer Science

基　　金：国家自然科学基金(61562005;61572206;61363067;61202468);广西自然科学基金(2015GXNSFAA139286);香江学者计划项目(XJ2013028);2015年广西高校科技研究项目(KY2015YB486);2013年广西高等学校中青年优秀骨干教师培养工程项目资助

摘　　要：可充电无线传感器网络是一种新型的无线传感网,它利用移动充电车在收集数据的同时给能量低的节点充电,可广泛应用于需要长期监测环境的应用中。但是,移动充电车如何在给定的延迟内完成数据收集,降低网络能耗并尽可能多地给低能量节点补充能量是一个具有挑战性的问题。因此提出一个新的算法RSEP(Root Selection with Energy Prediction)。首先,限定充电车的路径长度以保证延迟。然后,将路径上的低能量节点作为根节点,构造多棵数据收集树。若根节点能量可以保证其短期内不会死亡,则从树中寻找一条等于树的直径的路径。在该路径上选取网络中邻居最多的节点作为新的根节点,以改变树的结构来降低树高。树上的节点将它们的数据及能量信息沿着树传送到根节点。最后,移动充电车沿着充电路径为各个根节点充电时,就可以收集各个树上节点的数据及能量信息。此外,充电车收集到的能量信息会随着时间推移而"过时",而能量信息是根节点选择时的重要参考因素。因此,充电车利用马尔科夫模型预测节点在下一轮数据收集开始时的能量,从而优化根节点的选择。仿真实验结果表明,与目前已有的算法相比,RSEP算法可以以较少的网络总能耗完成充电,并且每轮充电时间均较短。Rechargeable wireless sensor network is a new type of wireless sensor network, which uses mobile wireless charging vehicle （MWCV） to charge the nodes with low energy in the network, as well as collect data from the net- work. The network can be used for applications that need to perform long time monitoring. However, it is a challenge to control the MWCV to finish data collection within given deadline in an energy efficient fashion, and achieve the target of charging as many low energy nodes as possible. In this paper, a novel algorithm named RSEP （Root Selection with Energy Prediction） was proposed. Firstly, the length of MWCV＇s walking path is constrained to guarantee the latency. Then,all the low energy nodes in the walking path are selected to be roots, by which multiple data collection trees are constructed. If a root＇s energy is enough for the root to maintain for more than a round, a path equaling to the diameter of the tree should be found. In the path,a node with the largest number of neighbors in the network is selected to be a new root. A new tree is formed by adjusting the old tree＇s structure through the new root. All the nodes in the tree transmit their data and energy information to the root. Finally,when MWCV walks along its path to charge the low ener- gy nodes, it can collect all data and energy information from the trees rooted at these nodes. On the other hand, the ener- gy information will become out-of-date with the time elapses. MWCV uses the Markov model to predict the nodes energy level at the time when next round of data collection starts, so as to optimize the roots selection. Theoretical analysis and simulation results show that compared with existing works, RSEP algorithm can accomplish a round^s charging with lower total energy consumption and shorter time duration.

关 键 词：可充电无线传感器网络 移动式能量补给 能耗 能量预测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]