摘要
无线传感器网络(Wireless sensor networks,简称WSNs)是由大量部署在目标区域的传感器节点构成,作为信息领域的新兴技术,WSN在环境监测、军事侦察、交通管理、医疗监护、智能家居等方面具有广泛的应用前景。传感器节点的存储能力、通信能力和处理能力相对较弱,通过能量有限的电池供电,且节点通常部署在环境条件恶劣或人类很难进入的区域,因此对节点进行更换非常困难。
数据收集作为WSN中极为重要的操作之一,其作用是将节点感知到的数据传送到Sink节点以供用户分析和处理。电能是WSN中非常重要的资源。在数据收集过程中,有效降低节点的能量耗费是节点长时间工作延长网络寿命的关键所在。本文对不同环境下无线传感器网络的数据收集技术进行了深入研究,旨在寻找能有效降低节点能量耗费、延长网络生命周期和提高网络可扩展性的方法,本文的研究工作主要包括以下几个方面：
(1)针对集中式数据收集存在的问题,在无线传感器网络中提出利用分簇技术来进行分布式数据收集。针对典型的分簇协议存在节点能量消耗不均衡,易导致节点过早死亡和网络生命周期缩短的缺点,提出一种能量均衡的分布式方法EBDSC来进行分簇数据收集。在EBDSC中,如果节点发现自己成为簇头后能承担的数据收集轮数比所有邻居都高,则该节点成为候选簇头。对于每个候选簇头,将根据自己邻居被其他候选簇头覆盖的情况,以反比概率成为正式簇头。理论分析表明,在EBDSC算法中,所有节点在O(logn/loge)个时间步内均能加入簇,算法总的消息复杂度是O(nlogn/loge)。仿真实验表明,与目前已有算法相比,EBDSC在分簇阶段有效减小了节点的能量消耗,最终有效延长了网络生命周期。
(2)针对构造连通支配集作为网络虚拟主干来进行数据收集时,已有算法构造的最小连通支配集不能有效均衡节点的能量耗费,导致网络生命周期较短的问题,提出了一种能量有效的基于连通支配集的算法DGA-EBCDS来进行数据收集,通过选择能量水平和度均比较大的节点组成连通支配集,使得支配集中的节点组成一个规模不大但具有较高能量水平的网络骨干。DGA-EBCDS算法使得网络中的所有数据沿虚拟骨干在数量较少的节点中转发,能够节省节点能量,使骨干节点不会因为能量不足而过早死亡。理论分析表明DGA-EBCDS能以O(nlogn)的消息复杂度构造连通支配集。仿真实验表明,与目前已有算法相比,DGA-EBCDS在构造连通支配集时有效减少了节点的能量耗费,从而有效延长了网络生命周期。
(3)针对已有数据收集算法普遍只考虑网络中节点产生的数据量是相同的情况下数据收集算法存在的问题,研究当各节点产生的数据量非均衡情况下适合多跳无线传感器网络环境的数据收集算法。首先,提出了一种基于支配集的分簇数据收集算法DSCAU。在DSCAU中,每个节点对自身剩余能量、节点邻居数量、自身和邻居产生的数据量等情况进行综合考虑来选举候选簇头。为避免正式簇头过多,候选簇头根据自身邻居被其他候选簇头覆盖的数量,以反比概率成为正式簇头。算法为了均衡簇头的能量开销,对簇的规模进行了限制。理论分析和仿真实验表明,DSCAU在多跳情况下能有效延长网络生命周期,并且能保证所有节点均能加入簇。然后,为了提高算法的适用性,本文对DSCAU算法进行了改进,提出了一种在更广范围内适用的通过移动Sink来进行数据收集的DSCP算法。理论分析表明,在DSCP算法中,所有节点在O(n/logn)个时间步内均能加入簇,算法总的消息复杂度是O(n2/logn)。仿真实验表明,DSCP与目前已有算法相比,网络生命周期得到有效延长。
综上所述,本文对无线传感器网络中的数据收集技术及关键问题进行了深入研究,提出了多个性能更好的协议,能够较好地解决WSN数据收集中存在的问题,具有较高的理论意义及应用价值。
Wireless sensor network (WSN) is a new hot-spot in current research, and it has broad application foreground. A wireless sensor network consists of a large number of nodes that collaborate together to monitor various phenomenons. WSN.can be used in various fields, such as military, environment, disaster forecast and relief, business, health, etc. The sensor nodes have only limited communication ability, computational ability, storage space, and energy, etc. Moreover, the nodes are difficult to be replaced because they are often deployed in remote or inaccessible environments.
Wireless sensor networks are data-oriented and are usually densely deployed in a monitor environment to process a great deal of data. Data collection is one of the most important operations in the network, which means that the data sensed by nodes should be transmitted to the sink for further processing. How to conserve the limited energy of nodes and extend the lifetime of the network is an important issue in data collection. This dissertation focuses on the problem that how to find some ways to effectively decrease energy consumption of the nodes and maximize the network lifetime and improve the scalability of the network. The main contributions of this dissertation are showed as follows.
(1) Aiming at the problem of existing clustering protocols usually randomly choose cluster heads or use the node with the highest remaining energy in a cluster as the head, which may lead to unbalanced energy consumption among different nodes and shorten the network lifetime, we propose a distributed energy-balanced dominating set based clustering scheme named EBDSC, which effectively prolongs the network lifetime by balancing energy consumption among nodes. In EBDSC, each node calculates the number of rounds it can afford if it was selected as the cluster head. A node becomes a candidate cluster head if it affords most number of rounds among its neighbors. A candidate cluster head becomes a final cluster head with a probability determined by its uncovered neighbors. The protocol can terminate in O(logn/loge) steps, and its total message complexity is O(nlogn/loge). Simulation results show that EBDSC can balance energy consumption among nodes well. The average energy consumption of EBDSC is reduced in the clustering phase, and the network lifetime is prolonged compared with another clustering algorithm ECDS.
(2) Aiming at the problem of exsiting researches construct virtual backbone of network by using minimum connected dominating sets, and each node in the network can transmit its data to the sink by the virtual backbone. But, the minimum connected dominating sets cannot balance the energy consumptions among nodes. Therefore, the network lifetime is hard to be extended. We propose a novel algorithm named DGA-EBCDS to construct an energy-balanced connected dominating set. In DGA-EBCDS, each node in the connected dominating set has high energy and large degree, and these nodes form a virtual backbone in the network. By transmitting data through the backbone with small numbers of sensor nodes, each node can preserve its energy effectively. Moreover, the nodes in the backbone can live longer. Theoretical analyses show that DGA-EBCDS can construct a connected dominating set with O(nlogn) message complexity, and simulations show that the average energy consumption of DGA-EBCDS is reduced, and the network lifetime is prolonged compared with another algorithm mr-CDS.
(3) Aiming at the problem of existing data collection protocols mainly assume that every node in the network produces the same amount of data, we propose a novel dominating set based algorithm DSCAU to solve the problem. In DSCAU, when electing the tentative cluster head, each node takes its remainder energy, its traffic load, the number of its neighbors, and the traffic loads of its neighbors into consideration. The tentative cluster head will become final cluster head with a probability inversely proportional to the numbers of other tentative cluster heads that cover its neighbors. Furthermore, the size of clusters is restricted to balance the energy consumption among different cluster heads. Theoretical analyses and simulation results show that DSCAU can effectively prolong the network lifetime in multi-hop WSNs, meanwhile guaranteeing that all the nodes in the network can join a cluster.
Moreover, in order to expand the applicability of the algorithm, we futher propose a new algorithm named DSCP to improve DSCAU. In DSCP, a node evaluates the potential lifetime of the network (from its local point of view) assuming that it acts as the cluster head, and claims to be a tentative cluster head if it maximizes the potential lifetime. When evaluating the potential lifetime of the network, a node considers not only its remaining energy, but also other factors including its traffic load, the number of its neighbors, and the traffic loads of its neighbors. The protocol can terminate in O(n/logn) steps, and its total message complexity is O(n2/logn). Simulation results show that DSCP can effectively prolong the lifetime of the network in multi-hop networks with unbalanced traffic load.
In a word, the dissertation performs an in-depth study on the data collection of wireless sensor networks. Moreover, several energy-efficient data collection protocols with higher performance are proposed. Therefore, the research of the dissertation has strong theoretical and practical significances.
引文
[1]Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal. Wireless sensor network survey. Computer Networks,2008,52(12):2292-2330.
[2]李建中,高宏.无线传感器网络的研究进展.计算机研究与发展,2008,45(1)： 1-15.
[3]崔莉,鞠海玲,苗勇,李天璞,刘巍,赵泽.无线传感器网络研究进展.计算机研究与发展,2005,42(1)：163-174.
[4]张倩.基于TinyOS的无线传感器网络路由协议设计与实现：[硕士学位论文].西安：西北工业大学,2006.
[5]李斌.基于WSN的分层路由算法研究：[硕士学位论文].扬州：扬州大学,2009.
[6]田忠.基于IEEE802.15.4的无线传感器网络验证系统的设计与实现：[硕士学位论文].南京：东南大学,2006.
[7]李宜安.基于IEEE802.15.4标准的无线传感器网络研究：[硕士学位论文].南京：东南大学,2006.
[8]曹生岭.基于信号差异的自适应分布式室内定位算法的研究：[硕士学位论文].哈尔滨：哈尔滨工业大学,2008
[9]I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci. A survey on sensor networks. IEEE Communications Magazine,2002,40(8):104-112.
[10]G. Simon, M. Maroti, A. Ledeczi, G. Balogh, B. Kusy, A. Nadas, G. Pap, J. Sallai, K. Frampton. Sensor network-based countersniper system. In Proc.of the Second International Conference on Embedded Networked Sensor Systems (SENSYS 2004),2004:256-260.
[11]Aboelaze M, Aloul F. Current and future trends in sensor networks:A survey. In Proc. of Second IFIP International Conference on Wireless and Optical Communications Networks (WOCN 2005),2005:551-555.
[12]Sang Hyuk Lee, Soobin Lee, Heecheol Song, Hwang Soo Lee. Wireless sensor network design for tactical military applications:Remote large-scale environments. In Proc. of IEEE Military Communications Conference (MILCOM 2009),2009:1-7.
[13]Mahdy A.M. Marine wireless sensor networks:Challenges and applications. In Proc. of Seventh International Conference on Networking (ICN 2008), 2008:530-535.
[14]Heecheol Song, Sang Hyuk Lee, Soobin Lee, Hwang Soo Lee. 6LoWpan-based tactical wireless sensor network architecture for remote large-scale random deployment scenarios. In Proc. of IEEE Military Communications Conference (MILCOM 2009),2009:25-31.
[15]Junyoung Heo, Jiman Hong, Yookun Cho. EARQ:Energy aware routing for real-time and reliable communication in wireless industrial sensor networks. IEEE Transactions on Industrial Informatics,2009,5(1):3-11.
[16]Gungor V.C, Hancke G.P. Industrial wireless sensor networks:Challenges, eesign principles, and technical approaches. IEEE Transactions on Industrial Electronics,2009,56(10):4258-4265.
[17]Flammini A, Ferrari P, Marioli D, Sisinni E, Taroni A. Sensor networks for industrial applications. In Proc. of 2nd International Workshop on Advances in Sensors and Interface (IWASI 2007),2007:1-15.
[18]Anastasi G, Conti M, Di Francesco M. Extending the lifetime of wireless sensor networks through adaptive sleep. IEEE Transactions on Industrial Informatics,2009,5(3):351-365.
[19]Al Agha K, Bertin M.H, Dang T, etc. Which wireless technology for industrial wireless sensor networks? The development of OCARI technology. IEEE Transactions on Industrial Electronics,2009,56(10):4266-4278.
[20]Mo Li, Yunhao Liu, Lei Chen. Nonthreshold-based event detection for 3D environment monitoring in sensor networks. IEEE Transactions on Knowledge and Data Engineering,2008,20(12):1699-1711.
[21]Xia Hong-bo, Jiang Peng, Wu Kai-hua. Design of water environment data monitoring node based on ZigBee technology. In Proc. of International Conference on Computational Intelligence and Software Engineering (CiSE 2009),2009:1-4.
[22]Guang Lu, Wei Xue. Adaptive weighted fusion algorithm for monitoring system of forest fire based on wireless sensor networks. In Proc.of Second International Conference on Computer Modeling and Simulation (ICCMS 2010),2010:414-417.
[23]Dang Thanh, Bulusu Nirupama, Feng Wu-chi, etc. CoTrack:A framework for tracking dynamic features with static and mobile sensors. In Proc.of The 29th IEEE Conference on Computer Communications (INFOCOM 2010),2010:1-5.
[24]Song W, Huang R, Xu M, Shirazi B, LaHusen R. Design and deployment of sensor network for real-time high-fidelity volcano monitoring. IEEE Transactions on Parallel and Distributed Systems,2010,1(1):1-15.
[25]Gao YingMing, Jin RenCheng. A novel wireless sensor networks platform for habitat surveillance. In Proc.of International Conference on Computer Science and Software Engineering (CSSE 2008),2008:1028-1031.
[26]Pendock G.J, Evans L, Coulson G. Wireless sensor module for habitat monitoring. In Proc.of 3rd International Conference on Intelligent Sensors, Sensor Networks and Information (ISSNIP 2007),2007:699-702.
[27]Lindgren A, Mascolo C, Lonergan M, McConnell B. Seal-2-Seal:A delay-tolerant protocol for contact logging in wildlife monitoring sensor networks. In Proc of 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS 2008),2008:321-327.
[28]Wyne S, Singh A.P, Tufvesson F, Molisch A.F. A statistical model for indoor office wireless sensor channels. IEEE Transactions on Wireless Communications,2009,8(8):4154-4164.
[29]Hongwei Huo, Youzhi Xu, Hairong Yan, Mubeen S. An elderly health care system using wireless sensor networks at home. In Proc. of Third International Conference on Sensor Technologies and Applications (SENSORCOMM 2009), 2009:158-163.
[30]Dong-Hwan Park, Tai-Yeon Ku, Jae Gak Hwang. Design and implementation of home sensor service platform. In Proc. of International Conference on Consumer Electronics (ICCE 2010),2010:481-482.
[31]Li F.X, Islam A, Perera G.C, Kolli P.K. Real-time urban bridge health monitoring using a fixed wireless mesh network. In Proc.of 2010 IEEE Radio and Wireless Symposium (RWS 2010),2010:384-387.
[32]Sankaranarayanan S. Intelligent agent based information routing in wireless body sensor Mesh Networks. In Proc. of IFIP International Conference on Wireless and Optical Communications Networks (WOCN 2009),2009:1-5.
[33]Junnila S, Kailanto H, Merilahti J. Wireless, multipurpose in-home health monitoring platform:Two case trials. IEEE Transactions on Information Technology in Biomedicine,2010,14(2):447-455.
[34]Uichin Lee, Magistretti E, Gerla M. Dissemination and harvesting of urban data using vehicular sensing platforms. IEEE Transactions on Vehicular Technology,2009,58(2):882-901.
[35]Xu Li, Wei Shu, Minglu Li. Performance evaluation of vehicle-based mobile sensor networks for traffic monitoring. IEEE Transactions on Vehicular Technology,2009,58(4):1647-1653.
[36]Niyato D, Hossain E.A. Unified framework for optimal wireless access for data streaming over vehicle-to-roadside communications. IEEE Transactions on Vehicular Technology,2010,1(1):1-13.
[37]Reason J. M, Crepaldi R. Ambient intelligence for freight railroads. IBM Journal of Research and Development,2009,53(3):1-14.
[38]Picard R, Burr T. Networked sensors for cargo screening. IEEE Sensors Journal,2008,8(8):1389-1396.
[39]Volos H.I, Buehrer R.M. Design and scaled implementation of a UWB sensor system for cargo transfer. In Proc.of IEEE Global Telecommunications Conference (GLOBECOM 2007),2007:1081-1085.
[40]Del Re E, Pucci R, Ronga L.S. IEEE 802.15.4 wireless sensor network in mars exploration scenario. In Proc.of International Workshop on Satellite and Space Communications (IWSSC 2009),2009:284-288.
[41]Pfarr B, Calabrese M, Kirkpatrick J, Malay J.T. Exploring the possibilities: Earth and space science missions in the context of exploration. In Proc.of IEEE Aerospace Conference (AC 2006),2006:78-83.
[42]杨阳.无线传感器网络中基于最小跳场的可控拓扑及路由研究：[硕士学位论文].重庆：西南大学,2008.
[43]李彦岑.无线传感器网络数据感知节点与接入汇聚技术研究：[硕士学位论文].南京：东南大学,2006.
[44]梁俊斌.无线传感网中低能耗数据收集协议研究：[博士学位论文].长沙：中南大学,2010.
[45]徐建波.无线传感器网络分布式分簇和节能的数据收集协议研究：[博士学位论文].长沙：湖南大学,2007.
[46]Heinzelman W, Chandrakasan A, Balakrishnan H. Energy-efficient communication protocol for wireless microsensor networks. In Proc. of the 33rd Annual Hawaii International Conference on System Sciences, IEEE Computer Society,2000:3005-3014.
[47]Younis O, Fahmy S, HEED:A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 2004,3(4):366-379.
[48]Manjeshwar A, Agrawal D P. TEEN:A protocol for enhanced efficiency in wireless sensor Networks, in Proc. of the 15th Parallel and Distributed Processing International Conference (IPDPS 2001),2001:2009-2015.
[49]刘明,曹建农,陈贵海,陈力军,王晓敏,龚海刚EADEEG:能量感知的无线传感器网络数据收集协议.软件学报,2007,18(5)：1092-1109.
[50]沈洋,齐望东,戴浩.一种能量有效的传感器监测网络成簇协议.软件学报,2008,19(9)：2432-2441.
[51]Chong Liu, Kui Wu, Jian Pei. An energy-efficient data collection framework for wireless sensor networks by exploiting spatiotemporal correlation. IEEE Transactions on Parallel and Distributed Systems,2007,18(7):1010-1023.
[52]Qi Dong, Donggang Liu. Resilient cluster leader election for wireless sensor networks. In Proc.of the 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON 2009),2009:1-9.
[53]Kaur, T, Jinsuk Baek. A strategic deployment and cluster-header selection for wireless sensor networks. IEEE Transactions on Consumer Electronics,2009, 55(4):1890-1897.
[54]Wei D, Navaratnam P, Gluhak A, et al. Energy-efficient clustering for wireless sensor networks with unbalanced traffic load. In:Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2010). 2010.250-256.
[55]李成法,陈贵海,叶懋,吴杰.一种基于非均匀分簇的无线传感器网络路由协议.计算机学报,2007,30(1)：27-36.
[56]Lotfinezhad M, Ben Liang, Sousa E.S. Adaptive cluster-based data collection in sensor networks with direct sink access. IEEE Transactions on Mobile Computing,2008,7(7):884-897.
[57]Chamam A, Pierre S. On the planning of wireless sensor networks: Energy-efficient clustering under the joint routing and coverage constraint. IEEE Transactions on Mobile Computing,2009,8(8):1077-1086.
[58]黄海平,王汝传,蒋颢,孙力娟,李靖.无线传感器网络TBCCA树形分簇算法.计算机研究与发展,2009,46(12).
[59]刘安丰,阳国军,陈志刚.基于不等簇半径轮换工作的传感器网络能量空洞避免研究.通信学报,2010,31(1)：1-8.
[60]Yanyan Zhuang, Jianping Pan, Lin Cai. Minimizing energy consumption with probabilistic distance models in wireless sensor networks. In Proc.of The 29th IEEE Conference on Computer Communications (INFOCOM 2010), 2010:115-124.
[61]Gedik B, Ling Liu, Yu P.S. ASAP:An adaptive sampling approach to data collection in sensor networks. IEEE Transactions on Parallel and Distributed Systems,2007,18(12):1766-1783.
[62]Hongbin Chen, Tse C.K, Jiuchao Feng. Impact of topology on performance and energy efficiency in wireless sensor networks for source extraction. IEEE Transactions on Parallel and Distributed Systems,2009,20(6):886-897.
[63]Hongbin Chen, Tse, C.K, Jiuchao Feng. Minimizing effective energy consumption in multi-cluster sensor networks for source extraction. IEEE Transactions on Wireless Communications,2009,8(3):1480-1489.
[64]Jun Fang, Hongbin Li. Power constrained distributed estimation with cluster-based sensor collaboration. IEEE Transactions on Wireless Communications,2009,8(7):3822-3832.
[65]Guojun Wang, Jiannong Cao, Huan Wang, Minyi Guo. Polynomial Regression for Data Gathering in Environmental Monitoring Applications, in Proc.of IEEE Global Telecommunications Conference (GLOBECOM 2007),2007:1307-1311.
[66]谢磊,陈力军,陈道蓄,谢立.基于分簇的传感器网络数据聚集估算机制.软件学报,2009,20(4)：1023-1037.
[67]Wang Pu, Dai Rui, Akyildiz Ian F. Collaborative data compression using clustered source coding for wireless multimedia sensor networks, in Proc.of The 29th IEEE Conference on Computer Communications (INFOCOM 2010), 2010:327-336.
[68]Tan HO, Korpeoglu I. Power efficient data gathering and aggregation in wireless sensor networks. SIGMOD Record,2003,32(3):66-71.
[69]张卿,谢志鹏,凌波,孙未未,施伯乐.一种传感器网络最大化生命周期数据收集算法.软件学报,2005,16(11)：1946-1957.
[70]Weifa Liang, Yuzhen Liu. Online data gathering for maximizing network lifetime in sensor networks. IEEE Transaction on mobile computing,2007, 6(1):2-11.
[71]Konstantinos Kalpakis, Koustuv Dasgupta, Parag Namjoshi. Maximum lifetime data gathering and aggregation in wireless sensor networks. In Proc. of IEEE International Conference on Networking,2002:75-81.
[72]Yang Yu, Viktor K. Prasanna, Bhaskar Krishnamachari. Energy minimization for real-time data gathering in wireless sensor networks. IEEE Transactions On Wireless Communications,2006,5(11):3087-3096.
[73]李宏,于宏毅,刘阿娜.一种基于树的无线传感器网络数据收集方法.电子与信息学报,2007,29(7)：1633-1637.
[74]Haibo Zhang, Hong Shen. Balancing energy consumption to maximize network lifetime in data-gathering sensor networks. IEEE Transactions on Parallel and Distributed Systems,2009,20(10):1526-1539.
[75]Kalpakis, K, Shilang Tang. A combinatorial algorithm for the maximum lifetime data gathering and aggregation problem in sensor networks. In Proc.of 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2008),2008:1-8.
[76]Cunqing Hua, Tak-shing peter Yum. Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks. IEEE/ACM Transactions on Networking,2008,16(4):892-903.
[77]Yan Wu, Sonia Fahmy, Ness B.shroff. On the construction of a maximum-lifetime data gathering tree in sensor networks:NP-completeness and approximation algorithm, In Proc. of the IEEE 27th Conference on Computer Communications (INFOCOM2008),2008:356-360.
[78]Chiranjeeb Buragohain, Divyakant Agrawal, Subhash Suri. Power Aware Routing for Sensor Databases. In Proc. of the IEEE 24th Conference on Computer Communications (INFOCOM 2005),2005:1747-1757.
[79]Soonmok Kwon, Jeong-gyu Kim, Cheeha Kim. An efficient tree structure for delay sensitive data gathering in wireless sensor networks. In Proc. of the 22nd IEEE International Conference on Advanced Information Networking and Applications (AINA 2008),2008:738-743.
[80]Maleq Khan, Gopal Pandurangan, Anil Vullikanti. Distributed algorithms for constructing approximate minimum spanning trees in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems,2009,20(1):124-139.
[81]Lindsey S, Raghavendra CS. PEGASIS:Power efficient gathering in sensor information systems. In Proc. of the IEEE Aerospace Conference. San Francisco:IEEE Computer Society,2002:1-6.
[82]余勇昌,韦岗.无线传感器网络中基于PEGASIS协议的改进算法.电子学报,2008,36(7)：1309-1313.
[83]Hyunduk Kim, Boseon Yu, Wonik Choi, Moonju Park, Jinseok Chae. Distance based pre-cluster head selection scheme for a chain-based protocol. In Proc. of Ninth IEEE International Conference on Computer and Information Technology (CIT 2009),2009:110-115.
[84]Jisoo Shin, Changjin Suh. Energy-efficient chain topology in ubiquitous sensor network. In Proc.of the 10th International Conference on Advanced Communication Technology (ICACT 2008),2008:1688-1693.
[85]Chakraborty A, Chakraborty K., Mitra S.K, Naskar M.K. An optimized lifetime enhancement scheme for data gathering in wireless sensor networks. In Proc.of Fifth IEEE Conference on Wireless Communication and Sensor Networks (WCSN 2009),2009:1-6.
[86]Guo Wenjing, Zhang Wei, Lu Gang. PEGASIS protocol in wireless sensor network based on an improved ant colony algorithm. In Proc. of 2010 Second International Workshop on Education Technology and Computer Science (ETCS 2010),2010:64-67.
[87]Jae Duck Yu, Kyung Tae Kim, Bo Yle Jung, Hee Yong Youn. An energy efficient chain-based clustering routing protocol for wireless sensor networks. In Proc.of the International Conference on Advanced Information Networking and Applications Workshops (WAINA 2009),2009:383-388.
[88]Deosarkar B.P, Yadav N.S, Yadav R.P. Chain based conical clustering (CCC) framework for data gathering in WSNs. In Proc. of the 16th IEEE International Conference on Networks (ICON 2008),2008:1-6.
[89]Hao Wu, Yi-ming Ding, Zhangdui Zhong. A chain-based fast data aggregation algorithm based on suppositional cells for wireless sensor networks. In Proc. of 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS 2009),2009:106-109.
[90]Kuong-Ho Chen, Jyh-Ming Huang, Chieh-Chuan Hsiao. CHIRON:An energy-efficient chain-based hierarchical routing protocol in wireless sensor networks. In Proc.of Wireless Telecommunications Symposium (WTS 2009), 2009:1-5.
[91]Zheng Gengsheng, Hu Zhengbing. Chain routing based on coordinates-oriented clustering strategy in WSNs. In Proc. of the International Symposium on Computer Network and Multimedia Technology (CNMT 2009),2009:1-4.
[92]Sung-Min Jung, Young-Ju Han, Tai-Myoung Chung. The concentric clustering scheme for efficient energy consumption in the PEGASIS. In Proc. of the 9th International Conference on Advanced Communication Technology (ICACT 2007),2007:260-265.
[93]Jung-Eun Lee, Keecheon Kim. Diamond-Shaped Routing Method for Reliable Data Transmission in Wireless Sensor Networks. In Proc.of International Symposium on Parallel and Distributed Processing with Applications (ISPA 2008),2008:799-801.
[94]Jin-Young Choi, Sung-Min Jung, Young-Ju Han, Tai-Myoung Chung. Advanced concentric-clustering routing scheme adapted to large-scale sensor networks. In Proc.of Second International Conference on Sensor Technologies and Applications (SENSORCOMM 2008),2008:366-371.
[95]Julia Albath, Mayur Thakur, Sanjay Madria. Energy Constrained Dominating Set for Clustering in Wireless Sensor Networks. In Proc.of 24th IEEE International Conference on Advanced Information Networking and Applications (AINA 2010).2010:812-819.
[96]Ling Ding, Xiaofeng Gao, Weili Wu, Wonjun Lee, Xu Zhu, Ding-Zhu Du. Distributed Construction of Connected Dominating Sets with Minimum Routing Cost in Wireless Networks [A].2010 IEEE 30th International Conference on Distributed Computing Systems (ICDCS 2010)[C]. 2010:448-457.
[97]Donghyun Kim, Yiwei Wu, Yingshu Li, et al. Constructing Minimum Connected Dominating Sets with Bounded Diameters in Wireless Networks. IEEE Transactions on Parallel Ransactions on Parallel and Distributed Systems, 2009,20(2):147-157.
[98]Hongwei Du, Qiang Ye, Weili Wu, et al. Constant Approximation for Virtual Backbone Construction with Guaranteed Routing Cost in Wireless Sensor Networks[A]. In Proc.of the 30th IEEE International Conference on Computer Communications (INFOCOM 2011)[C].2011:577-586.
[99]Khalid Ateyia M. Almahorg, Sagar Naik, Xuemin Shen. Efficient Localized Protocols to Compute Connected Dominating Sets for Ad Hoc Networks. In Proc.of the IEEE Global Communications Conference (Globecom 2010).2010: 157-163.
[100]Sajid Hussain, Mubashsharul I. Shafique, Laurence T. Yang. Constructing a CDS-Based Network Backbone for Energy Efficiency in Industrial Wireless Sensor Network. In Proc.of the 12th IEEE International Conference on High Performance Computing and Communications (HPCC 2010).2010:322-328.
[101]Yiwei Wu, Yingshu Li. Construction Algorithms for k-Connected m-Dominating Sets in Wireless Sensor Networks. In Proc.of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2008).2008:256-264.
[102]Donghyun Kim, Wei Wang, Xianyue Li, Zhao Zhang, Weili Wu. A New Constant Factor Approximation for Computing 3-Connected m-Dominating Sets in Homogeneous Wireless Networks. In Proc.of the 29th IEEE International Conference on Computer Communications (INFOCOM 2010). 2010:789-797.
[103]M.T. Thai, N. Zhang, R. Tiwari, X. Xu. On Approximation Algorithms of k-Connected m-Dominating Sets in Disk Graphs. Theoretical Computer Science,2007,358(3):49-59.
[104]Andreas Larsson, Philippas Tsigas. A Self-stabilizing (k,r)-clustering Algorithm with Multiple Paths for Wireless Ad-hoc Networks. In Proc.of the 31st International Conference on Distributed Computing Systems (ICDCS 2011).2011:353-362.
[105]Rivero-Angeles M.E., Bouabdallah N. Event reporting on continuous monitoring wireless sensor networks. In Proc.of the IEEE Global Telecommunications Conference (GLOBECOM 2009),2009:1-6.
[106]曹冬磊,曹建农,金蓓弘.一种无线传感器网络中事件区域检测的容错算法.计算机学报,2007,30(10)：1770-1776.
[107]Bouabdallah N, Rivero-Angeles M.E, Sericola B. Continuous monitoring using event-driven reporting for cluster-based wireless sensor networks. IEEE Transactions on Vehicular Technology,2009,58 (7):3460-3479.
[108]Mo Li, Yunhao Liu, Lei Chen. Nonthreshold-based event detection for 3D environment monitoring in sensor networks. IEEE Transactions on Knowledge and Data Engineering,2008,20(12):1699-1711.
[109]Jie Tong, Zhigao Du, Yi Liu, Depei Qian. Intra-flow network coding based multipath routing protocol for event-driven wireless sensor networks. In Proc.of the 5th International Conference on Mobile Ad-hoc and Sensor Networks (MSN 2009),2009:62-69.
[110]Tan Hwee-Xian, Chan Mun-Choon, Xiao Wendong, Kong Peng-Yong, Tham Chen-Khong. Information quality aware routing in event-driven sensor networks. In Proc.of the 29th IEEE Conference on Computer Communications (INFOCOM 2010),2010:101-109.
[111]胡湘华,杨学军.面向事件监测的无线传感网感知调度.软件学报,2008,19(9)：2413-2421.
[112]Bin Wang, Dongliang Xie, Canfeng Chen, Jian Ma, Shiduan Cheng. Deploying multiple mobile sinks in event-driven WSNs. In Proc.of the IEEE International Conference on Communications (ICC 2008),2008:2293-2297.
[113]Geyik S.C., Szymanski B.K. Event recognition in sensor networks by means of grammatical inference. In Proc.of the 28th IEEE Conference on Computer Communications (INFOCOM 2009),2009:900-908.
[114]Guang Jin, Nittel S. Towards Spatial Window Queries Over Continuous Phenomena in Sensor Networks. IEEE Transactions on Parallel and Distributed Systems,2008,19(4):559-571.
[115]Dengpan Zhou, Jie Gao. Opportunistic processing and query of motion trajectories in wireless sensor networks. In Proc.of the 28th IEEE Conference on Computer Communications (INFOCOM 2009),2009:1197-1205.
[116]Meliou A, Guestrin C, Hellerstein J.M. Approximating sensor network queries using in-network summaries. In Proc.of the 8th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2009),2009:229-240.
[117]余建平,林亚平.传感器网络中基于蚁群算法的实时查询处理.软件学报,2010,21(3)：473-489.
[118]崔艳荣,李克清.传感器网络中基于蚁群优化的数据查询协议.软件学报,2010,21(4)：793-801.
[119]You-Chiun Wang, Yao-Yu Hsieh, Yu-Chee Tseng. Multiresolution spatial and temporal coding in a wireless sensor network for long-term monitoring applications. IEEE Transactions on Computers,2009,58(6):827-838.
[120]郭龙江,李建中,李贵林.无线传感器网络环境下时-空查询处理方法.软件学报,2006,17(4)：794-805.
[121]Tao-Yang Fu, Wen-Chih Peng, Wang-Chien Lee. Parallelizing itinerary-based KNN query processing in wireless sensor networks. IEEE Transactions on Knowledge and Data Engineering,2010,22(5):711-729.
[122]Cheng R, Ben Kao, Kwan A, Prabhakar S, Yicheng Tu. Filtering data streams for entity-based continuous queries. IEEE Transactions on Knowledge and Data Engineering,2010,22(2):234-248.
[123]李贵林,高宏.传感器网络中基于环的负载平衡数据存储方法.软件学报,2007,18(5)：1173-1185.
[124]Lei Xie, Lijun Chen, Daoxu Chen, Li Xie. EEBASS:Energy-efficient balanced storage scheme for sensor networks. In Proc.of the IEEE Global Telecommunications Conference (GLOBECOM 2008),2008:1-6.
[125]谢磊,陈力军,陈道蓄,谢立.基于环结构的传感器网络多分辨率数据存储机制.软件学报,2009,20(12)：3163-3178.
[126]Sarkar R., Xianjin Zhu, Jie Gao. Double rulings for information brokerage in sensor networks. IEEE/ACM Transactions on Networking,2009, 17(6):1902-1915.
[127]Lin Chia-Hung, Kuo Jian-Jhih, Tsai Ming-Jer. Reliable GPS-free double-ruling-based information brokerage in wireless sensor networks. In Proc.of the 29th IEEE Conference on Computer Communications (INFOCOM 2010), 2010:1-5.
[128]Lei Ying, Zhen Liu, Towsley D., Xia C.H. Distributed operator placement and data caching in large-scale sensor networks. In Proc.of the 27th IEEE Conference on Computer Communications (INFOCOM 2008),2008:977-985.
[129]Andreou P, Zeinalipour-Yazti D, Andreou M, Chrysanthis P.K, Samaras G. Perimeter-based data replication in mobile sensor networks. In Proc.of the 10th International Conference on Mobile Data Management:Systems, Services and Middleware (MDM 2009),2009:244-251.
[130]Ishihara S., Suda T. Replica arrangement scheme for location dependent information on sensor networks with unpredictable query frequency. In Proc.of the IEEE International Conference on Communications (ICC 2009),2009:1-6.
[131]H Chan, A Perrig. ACE:An emergent algorithm for highly uniform cluster formation. In:Proc.of the 1st European Workshop on Wireless Sensor Networks. LNCS 2920, Berlin:Springer-Verlag,2004.154-171. http://citeseer.ist.psu.edu/672023.html
[132]Manjeshwar A, Agrawal D P. APTEEN:A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. in:Proceedings of the 2nd International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile computing, Ft. Lauderdale, FL, April 2002:195-202.
[133]Fei Hu, Xiaojun Cao, and Carter May. Optimized scheduling for data aggregation in wireless sensor networks. IEEE Int'l Conf. on ITCC,2005, (2):557-566.
[134]王建新,赵湘宁,刘辉宇.一种基于两跳邻居信息的贪婪地理路由算法.电子学报,2008,36(10)：1903-1909.
[135]Akyildiz L, Su W, Sankarasubramaniam Y et al. A survey on sensor networks. IEEE Communications, August 2002,40(8):102-114.
[136]Mhatre V, Rosenberg C, Kofman D, et al. A minimum cost heterogeneous sensor network with a lifetime constraint. IEEE Transactions on Mobile Computing,2005,4(1):4-15
[137]Mhatre V, Rosenberg K. Design guidelines for wireless sensor networks: Communication, clustering and aggregation. Ad Hoc Network Journal,2004, 2(l):45-63.
[138]R. Malhotra. IP Routing, First Edition. O'REILLY, January 2002.
[139]Naresh K, Pradeep KP, Sathish KS. An active en-route filtering scheme for information reporting in wireless sensor networks. International Journal of Computer Science and Informatin Technologies (IJCSIT 2011), 2011:1812-1819.
[140]Bashir AK, Lim SJ, Hussain CS, et al.. Energy efficient in-network RFID data filtering scheme in wireless sensor networks. IEEE Sensors Journal, 2011:7004-7021.