面向事件监测无线传感器网络可靠传输技术研究
|
摘要
无线传感器网络大规模、低成本、自组织的特性使其在事件监测领域有着广泛的应用前景。然而由于环境恶劣、节点资源受限等原因,信息传输的可靠性成为无线传感器网络应用系统设计面临的重大挑战。特别是在事件监测应用领域,对信息的可靠传输提出了更高的要求。不仅要求事件的准确感知,在此基础上还需实现事件信息的及时、可靠通告。因此,面向事件监测的可靠传输技术是无线传感器网络研究的重要内容之一。
论文针对面向事件监测无线传感器网络可靠传输的关键技术问题进行了深入研究,主要包括以下几个方面的内容：首先对无线传感器网络事件监测相关技术的研究现状进行了综述和梳理,通过分析指出其中的不足。之后,分别开展了复合事件检测与可靠通告、紧急信息可靠传输、突发感知的拥塞控制和休眠状态下信息的及时传输等问题的研究。在此研究基础上,提出了解决相应问题的协议和算法。论文的主要工作和创新点如下：
(1)针对现有事件检测属性单一的问题,提出一种多属性复合事件检测方法。在此基础上,对判决机制进行了改进,任何参与转发初始判决数据包的中间节点均可作为最终判决节点,不再固定为汇聚节点。中间节点在转发过程中一旦信息充分则立即作出最终判决。最终判决结果不仅需要发送至汇聚节点以通告用户,还需发给事件源节点使其停止发送初始判决信息以节省能量。针对最终判决结果的可靠传输问题,本论文提出一种κ-copy的可靠传输机制,数据包在传输过程中可按需进行冗余备份,以降低单个数据包传输失败的风险。
(2)传统的拥塞检测大都没有考虑节点负载的动态变化特征,并以控制源节点发送速率牺牲事件逼真度的方法减缓拥塞。针对此问题,本文首次提出队列变化率的概念,将队列长度和队列变化率同时纳入拥塞评估的范畴。根据拥塞评估结果将节点分为多个不同状态,并提出一种多级速率调节机制,各节点根据不同状态采取不同速率调节策略。此外,采用优先级队列设计思想,为紧急事件信息分配较高优先级,进一步保证了紧急信息的可靠传输。
(3)针对突发事件发生时易造成网络短时间拥塞的问题,本文提出一种突发感知的拥塞控制协议。在低负载网络环境中,传感器节点运行基于竞争冲突避免的CSMA/A MAC协议以节省能量。当突发事件发生时,短时间之内向传感器网络注入大量的信息流,网络负载较高。传统基于竞争的信道接入方式无法适应这种高负载网络下数据流传输,造成较为严重的区域拥塞。本论文利用TDMA适用于高负载的优点,在拥塞区域嵌入TDMA调度算法,当拥塞减轻或消除后,则恢复CSMA/CA机制。
(4)针对异步休眠方式中存在较为严重的转发等待时延问题,本文提出一种基于scout的休眠窗口自适应调节MAC协议。发送节点通过发送一系列的scout数据包唤醒接收节点,接收节点根据接收到的数据包动态调整其休眠时间,减少了下个数据包的等待时延。基于scout包,非转发路径上的节点可根据邻居节点转发任务动态调整其休眠时间,进一步减小非转发节点的空闲侦听时间,节省了宝贵的能量资源,延长了网络生存时间。
Wireless sensor networks (WSNs) have broad market prospects of applications in event monitoring due to its characteristics of large scale, low cost and self-organization. However, for the severe condition and limited resources, the reliable transmission is a major challenge in developing system of WSNs. Besides, the features of event monitor-ing applications bring out an even higher demand for the protocol design, requiring not only the accurate detection of event, but also the reliable and timely transmission of event notification. Therefore, the information reliable transmission is one of the most important subjects in WSNs.
In this dissertation, the key problem about the reliable transmission for event monitoring in WSNs is studied and the contents arc organized as follows:Firstly, we summarize the present resource literatures of relevant technologies and point out their shortcomings. And then, we carry out the research on four aspects:composite event detection and reliable notification, reliability of transmission for urgent information, burstiness-aware congestion control, and timeliness of transmission with sleep-wake scheduling. Meanwhile, relevant protocols and algorithms are presented and analyzed. The main contributions of this dissertation can be summarized as follows:
(1) In this dissertation, a novel method for detecting composite event using multiple properties is proposed. The final decision node is not only the sink node, but any other nodes participating in forwarding primary decision packets. They could make final decision as soon as obtaining enough information. And then, the final decision node sends the alarm information to the sink to inform users, as well as the event source nodes to stop sending primary decision packets to save energy. As for the reliable notification of the alarm information, a k-copy reliable transmission scheme is designed to improve the reliability by copying the alarm packet on demand to reduce the risk of transmission failure of single packet.
(2) Most of traditional congestion detection schemes do not take the dynamic change of load into consideration. Besides, they reduce the source rate of nodes to alleviate congestion at the cost of fidelity of event. To address this problem, a new concept of queue fluctuation is used to evaluate congestion by combining queue length. Based on the congestion evaluation results, nodes can be divided into different states and then a multistage rate adjustment scheme is proposed. Each node could adjust its rate depending on the different states. Furthermore, we use the idea of priority queue and assign a higher priority for the urgent information to further guarantee the reliability of transmission.
(3) To deal with the temporary congestion due to the occurrence of event, a burstiness aware congestion control protocol is proposed. When the network load is low, sensor nodes use CSMA/CA-based MAC protocol to save energy. However, the event occurring might generate a large amount of traffic in network, resulting in the increasing load and congestion. The previous CSMA/CA-based media access scheme is not suitable under the heavy network due to the serious collision. In this dissertation, a TDMA-based media access scheme is used around the congestion area to avoid disorder contention when congestion occurs. As soon as the congestion is alleviated, the previous CSMA/CA-bascd scheme is active again.
(4) For the severe cumulative latency in the asynchronous sleep-wake scheduling, a scout-based low latency MAC protocol is proposed. Initially, the sender transmits a serial of scout packets to wake up the receiver and then the receiver adjusts its sleep time to shorten the waiting time of next packet according to the scout packets. Besides, the other nodes not on the routing path overhearing the scout packets will adjust their sleep-wake scheduling to reduce the idle listening.
论文针对面向事件监测无线传感器网络可靠传输的关键技术问题进行了深入研究,主要包括以下几个方面的内容：首先对无线传感器网络事件监测相关技术的研究现状进行了综述和梳理,通过分析指出其中的不足。之后,分别开展了复合事件检测与可靠通告、紧急信息可靠传输、突发感知的拥塞控制和休眠状态下信息的及时传输等问题的研究。在此研究基础上,提出了解决相应问题的协议和算法。论文的主要工作和创新点如下：
(1)针对现有事件检测属性单一的问题,提出一种多属性复合事件检测方法。在此基础上,对判决机制进行了改进,任何参与转发初始判决数据包的中间节点均可作为最终判决节点,不再固定为汇聚节点。中间节点在转发过程中一旦信息充分则立即作出最终判决。最终判决结果不仅需要发送至汇聚节点以通告用户,还需发给事件源节点使其停止发送初始判决信息以节省能量。针对最终判决结果的可靠传输问题,本论文提出一种κ-copy的可靠传输机制,数据包在传输过程中可按需进行冗余备份,以降低单个数据包传输失败的风险。
(2)传统的拥塞检测大都没有考虑节点负载的动态变化特征,并以控制源节点发送速率牺牲事件逼真度的方法减缓拥塞。针对此问题,本文首次提出队列变化率的概念,将队列长度和队列变化率同时纳入拥塞评估的范畴。根据拥塞评估结果将节点分为多个不同状态,并提出一种多级速率调节机制,各节点根据不同状态采取不同速率调节策略。此外,采用优先级队列设计思想,为紧急事件信息分配较高优先级,进一步保证了紧急信息的可靠传输。
(3)针对突发事件发生时易造成网络短时间拥塞的问题,本文提出一种突发感知的拥塞控制协议。在低负载网络环境中,传感器节点运行基于竞争冲突避免的CSMA/A MAC协议以节省能量。当突发事件发生时,短时间之内向传感器网络注入大量的信息流,网络负载较高。传统基于竞争的信道接入方式无法适应这种高负载网络下数据流传输,造成较为严重的区域拥塞。本论文利用TDMA适用于高负载的优点,在拥塞区域嵌入TDMA调度算法,当拥塞减轻或消除后,则恢复CSMA/CA机制。
(4)针对异步休眠方式中存在较为严重的转发等待时延问题,本文提出一种基于scout的休眠窗口自适应调节MAC协议。发送节点通过发送一系列的scout数据包唤醒接收节点,接收节点根据接收到的数据包动态调整其休眠时间,减少了下个数据包的等待时延。基于scout包,非转发路径上的节点可根据邻居节点转发任务动态调整其休眠时间,进一步减小非转发节点的空闲侦听时间,节省了宝贵的能量资源,延长了网络生存时间。
Wireless sensor networks (WSNs) have broad market prospects of applications in event monitoring due to its characteristics of large scale, low cost and self-organization. However, for the severe condition and limited resources, the reliable transmission is a major challenge in developing system of WSNs. Besides, the features of event monitor-ing applications bring out an even higher demand for the protocol design, requiring not only the accurate detection of event, but also the reliable and timely transmission of event notification. Therefore, the information reliable transmission is one of the most important subjects in WSNs.
In this dissertation, the key problem about the reliable transmission for event monitoring in WSNs is studied and the contents arc organized as follows:Firstly, we summarize the present resource literatures of relevant technologies and point out their shortcomings. And then, we carry out the research on four aspects:composite event detection and reliable notification, reliability of transmission for urgent information, burstiness-aware congestion control, and timeliness of transmission with sleep-wake scheduling. Meanwhile, relevant protocols and algorithms are presented and analyzed. The main contributions of this dissertation can be summarized as follows:
(1) In this dissertation, a novel method for detecting composite event using multiple properties is proposed. The final decision node is not only the sink node, but any other nodes participating in forwarding primary decision packets. They could make final decision as soon as obtaining enough information. And then, the final decision node sends the alarm information to the sink to inform users, as well as the event source nodes to stop sending primary decision packets to save energy. As for the reliable notification of the alarm information, a k-copy reliable transmission scheme is designed to improve the reliability by copying the alarm packet on demand to reduce the risk of transmission failure of single packet.
(2) Most of traditional congestion detection schemes do not take the dynamic change of load into consideration. Besides, they reduce the source rate of nodes to alleviate congestion at the cost of fidelity of event. To address this problem, a new concept of queue fluctuation is used to evaluate congestion by combining queue length. Based on the congestion evaluation results, nodes can be divided into different states and then a multistage rate adjustment scheme is proposed. Each node could adjust its rate depending on the different states. Furthermore, we use the idea of priority queue and assign a higher priority for the urgent information to further guarantee the reliability of transmission.
(3) To deal with the temporary congestion due to the occurrence of event, a burstiness aware congestion control protocol is proposed. When the network load is low, sensor nodes use CSMA/CA-based MAC protocol to save energy. However, the event occurring might generate a large amount of traffic in network, resulting in the increasing load and congestion. The previous CSMA/CA-based media access scheme is not suitable under the heavy network due to the serious collision. In this dissertation, a TDMA-based media access scheme is used around the congestion area to avoid disorder contention when congestion occurs. As soon as the congestion is alleviated, the previous CSMA/CA-bascd scheme is active again.
(4) For the severe cumulative latency in the asynchronous sleep-wake scheduling, a scout-based low latency MAC protocol is proposed. Initially, the sender transmits a serial of scout packets to wake up the receiver and then the receiver adjusts its sleep time to shorten the waiting time of next packet according to the scout packets. Besides, the other nodes not on the routing path overhearing the scout packets will adjust their sleep-wake scheduling to reduce the idle listening.
引文
[1]I. Akyildiz, W. Su, Y. Sankarasubramaniam. et al. A survey on sensor networks. Commu-nications Magazine, IEEE,40(8):102-114, Aug.2002. ISSN 0163-6804.
[2]任丰原.黄海宁,林闯.无线传感器网络.软件学报.14(7):1282-1291：2003.
[3]E. H. Callaway. Wireless Sensor Networks: Architectures and Protocols. CRC Press.2004. ISBN:0849318238.
[4]J. Yick, B. Mukherjcc, D. Ghosal. Wireless sensor network survey. Computer Networks, 52(12):2292-2330,2008. ISSN 1389-1286.
[5]J A, Bymc.21 ideas for the 21th century. Business Week,8:78-167,1999.
[6]MIT Technology Review.10 emerging technologies that will change the world. http://www.technologyreview.com/article/13060/page2.February 2003.
[7]L.Atzori,A. Iera, G.Morabito. The internet of things:A survey.Computer Networks, 54(15):2787-2805,2010.ISSN 1389-1286.
[8]IBM.智慧地球赢在中国http://www.ibm.com/smartcrplanet/cn/zh/?re=masthcad
[9]工业和信息化部.物联网“十二五”发展规划.http://kjs.miit.gov.cn/n11293472/n11295040/n11478867/14344522.html
[10]M. Bhushan, R. Rengaswamy. Comprehensive design of a sensor network for chemical plants based on various diagnosability and reliability criteria.1. Framework. Industrial and engineering chemistry research,41(7):1826-1839.2002.
[11]Y. Wang, X. Wang, B. Xie, et al. Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks IEEE Transactions on Mobile Computing,7(6):698-711. June 2008.
[12]Y. Li, Z. Wang, Y. Song. Wireless Sensor Network Design for Wildfire Monitoring. In Proc. of The Sixth World Congress on Intelligent Control and Automation, volume 1.2006, 109-113.
[13]A. Mainwaring, J. Polastre, R. Szewczyk, et al. Wireless sensor networks for habitat. monitoring. In Proc. of ACM WSNA'02, Atlanta. GA. USA. September 2002.88-97.
[14]R.Szewczyk, E. Ostcrweil, J. Polastre, et al. Application driven systems research:habitat monitoring with sensor networks. In Communications of the ACM Special Issue on Sensor Networks,47(6):34-40.June 2004.
[15]V. Dyo, S.A. Ellwood, D.W. Macdonald, et al. Evolution and sustainability of a wildlife monitoring sensor network. In Proc. of the 8th ACM SenSys. ACM, New York, NY, USA.2010,127-140.
[16]Y. Kim, T. Schmid, Z. M. Charbiwala, et al. NAWMS:Nonintrusive Autonomous Water Monitoring System. In Proceedings of ACM SenSys'08. Raleigh. NC. USA, Nov.2008, 309-322.
[17]R. Siuli, S. Bandyopadhyay, Z. M. Charbiwala, ct al. Agro-sense:Precision agriculture using sensor-based wireless mesh networks. In Proceedings of First ITU-T Kaleidoscope Academic Conference on Innovations in NGN:Future Network and Services,2008,383-388.
[18]P. Juang, H. Oki, Y. Wang, et al. Energy-efficient computing for wildlife tracking:design tradeoffs and early experiences with zebranet. SIGARCH Comput. Archit. News,30(5):96-107,2002.
[19]Turtlenet. http://prisms.cs.umass.edu/dome/turtlenet.2007.
[20]L. Riquclmc, J.A. Soto, J. Polastre, et al.Wireless sensor networks for precision horticulture in southern Spain. Comput. Electron. Agric.,68(1):25-35,2009.
[21]Artificial Retina project. http://artificialretina.energy.gov
[22]D.Malan, T. Fulford-Jones, M. Welsh, et al. CodeBlue:an Ad Hoc sensor network in-frastructure for emergency medical care. In Proceedings of Workshop on Applications of Mobile Embedded Systems(WAMES'04), Boston, MA.USA.June 2004.
[23]R. Herlien, T. O'Reilly, K. Headley, et al. An ocean observatory sensor network application. IEEE Sensors,1837-1842,2010.
[24]T.Y. Wang, Q. Cheng. Collaborative event-region and boundary-region detection in wireless sensor networks. IEEE Transactions on Signal Processing,56(6):2547-2560,2008.
[25]K. Ren, K. Zeng, W. Lou. Secure and fault-tolerant event boundary detection in wireless sensor networks. IEEE Transactions on Wireless Communications,7(1):354-363.2008.
[26]N. Hubbell, Han Qi. Detection and tracking of dynamic amorphous events in wireless sensor networks. IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON'11). June 2011.170-178.
[27]M. M. Chen, C. Majidi, D. M. Doolin, et al.. Design and construction of a wildfire instru-mentation system using networked sensors (Poster). Network Embedded Systems Technology (NEST) Retreat Oakland California, USA, June 17-18.2003.
[28]A. Arora, P. Dutta, S. Bapat, et al. A line in the sand: a wireless sensor network for target detection, classification, and tracking. Comput. Netw.,46(5):605-634.2004.
[29]Boomerang shooter detection system.http://bbn.com/boomerang
[30]N. Xu,S. Rangwala, K. K. Chintalapudi, et al. A wireless sensor network for structural monitoring. In SenSys '04:Proceedings of the 2nd international conference on Embedded networked sensor systems. ACM, New York, NY, USA,2004,13-24.
[31]S. Kim, S. Pakzad, D. Culler, et al. Health monitoring of civil infrastructures using wire-less sensor networks. In Proceedings of the 6th international conference on Information processing in sensor networks(IPSN'07). ACM, New York, NY, USA,2007,254-263.
[32]T. He, S. Krishnamurthy, L. luo, ct al. VigilNct:An integrated sensor network system for energy-efficient surveillance. ACM Transactions on Sensor Networks (TOSN). 1(2):1-38, 2006.
[33]F. Lau, E. Oto, H. Aghajan. Color-based multiple agent tracking for wireless image sensor networks. In Proceedings of the Advanced Concepts for Intelligent Vision Systems (ACIVS '06), Springer, Antwerp, Belgium, September 2006.299-310.
[34]FireFly Sensor Networks, http://www.ecc.cmu.edu/firefly/projects.html.
[35]J.Solobera. Detecting Forest Fires using Wireless Sensor Networks with Waspmote. http://www.libelium.com/wireless_sensor_networks_to_detec_forest_fires/
[36]Ian F. Akyildiz, M.C. Vuran. Wireless Sensor Networks. John Wiley & Sons Ltd.2010.
[37]LAN/MAN Standards Committee. IEEE Std 802.15.4-2011 (Revision of IEEE Std 802.15.4-2006). IEEE Standard for Local and metropolitan area networks-Part 15.4:Low-Rate Wireless Personal Area Networks (LR-WPANs). May,2011.
[38]Crossbow technology, http://www.xbow.com.
[39]A. Dunkcls, B. Gronvall, T. Voigt. Contiki- a lightweight and flexible operating system for tiny networked sensors. In Proc. of the 29th Annual IEEE International Conference on Local Computer Networks. Tampa, Florida, USA. Nov.2004,455-462.
[40]Waspmote. Libelium opens access to bluctooth wireless sensor networks. http://www.libelium.com/libcliumworld/articles/101321320500,2009.
[41]The Stargate platform. http://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/Stargate_Datashect.pdf.
[42]CrossBow. Wireless Sensor Networks Product Reference Guide,2007.
[43]Sun Microsystems. Inc. Sun spot world, http://sunspotworld.com/.
[44]A. Rowe, R. Mangharam, R. Rajkumar. FireFly:A Time Synchronized Rcal-Time Sensor Networking Platform. Wireless Ad Hoc Networking:Personal-Area, Local-Area, and the Sensory-Area Networks. CRC Press Book Chapter,November 2006.
[45]SOWNet Technologies. G-Node G301. http://www.sownet.nl/index.php/products/gnode.
[46]National Instruments.Inc. NIWSN-3202. http://sinw.ni.com/nips/cds/view/p/lang/en/nid/206921.
[47]MicroStrain, Inc. Sensors, http://www.microstrain.com/wirclcss/sensors
[48]H. Karl, A. Willig. Protocols and Arhitectures for Wireless Sensor Networks. John Wiley & Sons Ltd,2005.
[49]J.-F. Chambcrland and V. V. Veeravalli. Decentralized Detection in Sensor Networks. IEEE Trans, on Signal Processing,51(2):407-416, February 2003.
[50]杨露菁,余华.多源信息融合理论及应用,第一版.北京.北京邮电大学出版社.2006.
[51]R. Viswanathan and P. Varshney. Distributed detection with multiple sensors:Part I-fundamentals. Proc. of the IEEE,85(1):54-63, Jan.1997.
[52]C. Scott. The Neyman-Pearson Criterion. http://cnx.Org/contcnt/m11548/1.2/
[53]Wikipedia. Q-function. http://en.wikipedia.org/wiki/Q-function
[54]A.Wald. Sequential Test of Statistical Hypothesis. Annals of Mathematical Statistics,1945, 25(5),New York:Wiley and Sons.
[55]Don Johnson. Sequential Hypothesis Testing,http://cnx.org/content/m11242/latest/
[56]L. Yu and A. Ephremides. Detection performance and energy efficiency trade-off in a sensor network, in Proc. of Allerton Conference. Allerton, IL. October 2003.
[57]L. Yu and A. Ephremides. Detection performance and energy efficiency of sequential de-tection in a sensor network, in Proc. of HICSS'06. Hawai, USA.
[58]L. Yu, L. Yuan, G. Qu, and A. Ephremides. Energy-driven detection scheme with guaran-teed accuracy, in Proc. of IPSN'06, Nashville, TN. USA. April 2006. pp.284-291.
[59]T. Q. Quek. D. Dardari, and M. Z. Win. Energy efficiency of dense wireless sensor networks: to cooperate or not to cooperate. IEEE Journal on Selected Areas in Communications. 25(2):459-470,2007.
[60]H.-X. Tan, M.-C. Chan, W. Xiao. P.-Y. Kong, and C.-K. Tham. Information quality aware routing in event-driven sensor networks.in Proc. IEEE INFOCOM,2010,1-9.
[61]J. Zheng, A. Jamalipour. Wireless Sensor Networks-A Networking Perspective. John Wiley & Sons Ltd,2009,351-356.
[62]方维维,钱德沛,刘轶.无线传感器网络传输控制协议.软件学报.19(6)：1439-1451,2008.
[63]B. Hull, K. Jamieson, H. Balakrishnan. Mitigating congestion in wireless sensor network. in Proc. The Second International Conference on Embedded Networked Sensor Systems (SenSys'04), Baltimore, MD, USA,2004,134-147.
[64]C.-Y. Wan, S. B. Eisenman, A. T. Campbell. CODA:congestion detection and avoidance in sensor networks, in Proc. First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003), Los Angeles, California, USA, Nov.2003.266-279.
[65]C. Wang, B. Li, K. Sohraby. Upstream congestion control in wireless sensor networks through cross-layer optimization. IEEE Journal on Selected Areas in Communications. 25(5):786-795,2007.
[66]L. Liang, D. Gao, H. Zhang. A Novel Reliable Transmission Protocol for Urgent Information in Wireless Sensor Networks, in Proc. IEEE GLOBECOM'10, Miami. FL. USA. Dec.2010. 1-6.
[67]O. B. Akan and I. Akyildiz, Event-to-sink reliable transport in wireless sensor networks. IEEE/ACM Transactions on Networking,13(5):1003-1016,2005.
[68]C.-T. Ee, R. Bajcsy. Congestion control and fairness for many-to-one routing in sen-sor networks, in Proc. of 2004 ACM Conference on Embedded Networked Sensor Sys-tems(Sensys'04), Baltimore, MD, Nov.2004.148-161.
[69]S.-J. Park, R. Vedantham, R.. Sivakumar, et al. A scalable approach for reliable downstream data delivery in wireless sensor networks. in Proceedings of 2004 ACM International Sym-posium on Mobile Ad Hoc Networking and Computing (MobiIIoc'04). Roppongi, Japan, May 2004,78-89.
[70]S. Rangwala, R. Gummadi, R. Govindan, et al. Interference-aware fair rate control in wireless sensor networks. In Proceedings of the ACM SIGCOMM.2006,63-74.
[71]C. Wang, K. Sohraby, V. Lawrence, et al. Priority-based congestion control in wireless sensor networks, in Proc. IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06), Taichung. Taiwan. June 2006,22-31.
[72]V. C. Gungor, O. B. Akan, and I. F. Akyildiz. A real-time and reliable transport pro-tocol for wireless sensor and actor networks. IEEE/ACM Transactions on Networking. 16(2):359-370, April 2008.
[73]J. Kang, Y. Zhang, B. Nath, S. Yu. Adaptive Resource Control Scheme to Alleviate Con-gestion in Sensor Networks. In Proceedings of the First Workshop on Broadband Advanced Sensor Networks (BASENETS'04). San Jose, CA. October 2004.
[74]R. Kumar, H. Rowaihy, G.H. Cao, et al. Congestion aware routing in sensor networks. Technical report,2006. htpp://nsrc.cse.psu.edu/tech_report/NAS-TR-0036-2006.pdf
[75]F. Ren, T. He, S. Das, and C. Lin. Traffic-aware dynamic routing to alleviate congestion in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems.2011.
[76]L. Gulluccio, A.T. Campbell, S. Palazzo. Poster Abstract:CONCERT:aggregation-based CONgcstion Control for sEnsoR neTworks. In Proc. of ACM SenSys'05, San Diego,USA, 2005,274-275.
[77]Edith C. H. Ngai, Y. Zhou, Michael R. Lyu, et al. Reliable reporting of delay-sensitive events in wireless sensor-actuator networks. In Proc. of the 3rd IEEE MASS,2006,101-118.
[78]C. Wan, A. T. Campbell. Siphon:Overload traffic management using multi-radio virtual sinks in sensor networks. In Proc. of ACM SenSys'05, San Diego, USA,2005,116-129.
[79]G.-S. Ahn, S.G. Hong, E. Miluzzo, et al. Funneling-MAC:a localized, sink-oriented MAC for boosting fidelity in sensor networks. In Proceedings of the 4th international conference on Embedded networked sensor systems(SenSys'06). Boulder, Colorado, USA.2006,293-306.
[80]A. Woo, D. C. Culler. A transmission control scheme for media acess in sensor networks In Proceedings of ACM Mobicom' 01. Rome, Italy. Jul.2004.16-21.
[81]C. Wang, M. Daneshmand, B. Li, K. Sohraby. A survey of transport protocols for wireless sensor networks. IEEE Network,20(3):34-40,2006.
[82]F. Stann,J. Hcidcmann. RMST:Reliable data transport in senor networks. In Proceedings of IEEE International Workshop on Sensor Network Protocols and Applications(SNPA'03), Anchorage, AK, May 2003.
[83]C. Intanagonwiwat, R.. Govindan, D. Estrin, et al. Directed Diffusion for Wireless Sensor Networks. IEEE/ACM Transactions on Networking,11(1):2-16.2003.
[84]H.Zhang,A. Arora. Y. Choi, et al. Reliable bursty convergecast in wireless sensor networks. In Proc. of The ACM Mobihoc'05, Urbana-Champaign. IL. May 2005,266-276.
[85]I.S. Reed, G. Solomon. ReedSolomon error correction. http://en.wikipedia.org/wiki/Reed-Solomon_error_correction
[86]M. Luby. LT codes. In Proceedings of The 43rd Annual IEEE Symposium on Foundations of Computer Science.271-280,2002.
[87]A. Shokrollahi. Raptor codes. IEEE Transactions on Information Theonry,52(6):2551-2567, 2006.
[88]S. Kim, R. Fonseca, D. Culler. Reliable transfer on wireless sensor networks. In Proc. of The IEEE SECON'04,2004,449-459.
[89]R. Fonseca, S. Ratnasamy, J. Zhao, et al. Beacon vector routing:scalable point-to-point routing in wireless sensornets. In Proceedings of the 2nd conference on Symposium on Net-worked Systems Design & Implementation- Volume 2(NSDI'05), Berkeley. CA, USA,2005. 329-342.
[90]B. Deb, S. Bhatnagar, and B. Nath. ReInForM:Reliable Information Forwarding using Multiple Paths in Sensor Networks. In Proceedings of the 28th Annual IEEE Conference on Local Computer Networks(LCN 2003), Bonn, Germany. October 2003.
[91]E. Felemban, C.G. Lee, E. Ekici. MMSPEED:Multipath Multi-SPEED Protocol for QoS Guarantee of Reliability and Timeliness in Wireless Sensor Networks. IEEE Transactions on Mobile Computing,5(6):738-754,2006.
[92]T. He, J.A. Stankovic. C. Lu, ct al. SPEED:a stateless protocol for real-time communica-tion in sensor networks. In Proc. of 23rd International Conference on Distributed Computing Systems, May 2003,46-55.
[93]W. Ye, J. Hcidemann,and D. Estrin. An energy-efficient mac protocol for wireless sensor networks. In Proc. IEEE INFOCOM,New York. NY. USA. Jun.2002,1567-1576.
[94]R. Mishra, S. Nayak, K. Verma, and D. Singh. Survey on techniques to resolve problems associated with rts/cts mechanism. In Proc. ACM ICCCS. New York. NY. USA:ACM, 2011,86-91.
[95]W. Ye, J. Heidemann, and D. Estrin. Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/Acm Transactions on Networking,12(3):493-506,2004.
[96]T. Van Dam and K. Langendoen. An adaptive energy-efficient mac protocol for wireless sensor networks. In Proc. ACM Sensys.ACM,2003.171-180.
[97]G. Lu, B. Krishnamachari, C.S. Raghavendra. An adaptive energy-efficient and low-latency MAC for tree-based data gathering in sensor networks. Wiley Wireless Communications and Mobille Computing.7:863-875,2007.
[98]W. Ye, F. Silva, and J. Heidemann. Ultra-low duty cycle MAC with scheduled channel polling. In Proc. ACM Sensys. Boulder, Colorado. USA. ACM.2006.321-334.
[99]S. Du, A. Saha, and D. Johnson. RMAC:A routing-enhanced duty-cycle mac protocol for wireless sensor networks. In Proc. IEEE INFOCOM. Anchorage. Alaska, USA:IEEE, May 2007,1478-1486.
[100]J. Elson, L. Girod, and D. Estrin. Fine-grained network time synchronization using refer-ence broadcasts. In Proc. Fifth Symposium on Operating Systems Design and Implementa-tion (OSDI 2002). Dec.2002.
[101]S. Ganeriwal, R. Kumar, and M. B. Srivastava. Timing-sync protocol for sensor networks. In Proc. ACM Sensys. ACM, Nov.2003,138-149.
[102]Y. Sun, S. Du, O. Gurewitz, and D. Johnson. DW-MAC:a low latency, energy effi-cient demand-wakeup mac protocol for wireless sensor networks. In Proc. ACM Mobi-Hoc.HongKong, China:ACM, May 2008,53-62.
[103]T. Canli, A. Khokhar. PRMAC:Pipelined Routing Enhanced MAC Protocol for Wireless Sensor Networks. In Proc. IEEE International Conference on Communications(ICC'09). June 2009,1-5.
[104]J. Polastre, J. Hill, and D. Culler. Versatile low power media access for wireless sensor networks. In Proc. ACM Sensys.Baltimore, Maryland:ACM. Nov.2004,95-107.
[105]A. El-Hoiydi and J. Decotignie. WiseMAC:An ultra low power mac protocol for multi-hop wireless sensor networks. Algorithmic Aspects of Wireless Sensor Networks.18-31.2004.
[106]J. Polastrc, J. Hui, P. Levis, ct al. A unifying link abstraction for wireless sensor networks. In Proc. ACM SenSys.2005,76-89.
[107]M. Buettner, G. Yee, E. Anderson, and R. Han. X-MAC:a short preamble mac protocol for duty-cycled wireless sensor networks. In Proc. ACM Sensys. Boulder, Colorado, USA,ACM, 2006,307-320.
[108]J. J. Garcia-Luna-Aceves and A. Tzamaloukas. Reversing the Collision-Avoidance Hand-shake in Wireless Networks. In Proc. ACM/IEEE Mobicom,1999.120-131.
[109]Amre El-Hoiydi and Jean-Dominique Decotignie. Low Power Downlink MAC Proto-cols for Infrastructure Wireless Sensor Networks. Mobile Networks and Applications, 10(5):675-690,2005.
[110]R.. Musaloiu-E., C. M. Liang, and A. Terzis. Koala: Ultra-Low Power Data Retrieval in Wireless Sensor Networks. In Proc. ACM IPSN. April 2008,421-432.
[111]Y. Sun, O. Gurewitz, and D. Johnson. RI-MAC:a receiver-initiated asynchronous duty cycle mac protocol for dynamic traffic loads in wireless sensor networks. In Proc. ACM Sensys. Raleigh, NC, USA, ACM,2008,1-14.
[112]Y. Peng, Z. Li, D. Qiao, and W. Zhang. Delay-bounded mac with minimal idle listening for sensor networks. In Proc. IEEE LNFOCOM.Shanghai. China. Apr.2011.1314-1322.
[113]R. Krashinsky and H. Balakrishnan。 Minimizing energy for wireless web access with bounded slowdown, in Proc.IEEE Mobicom.2002.
[114]L. Tang, Y. Sun, O. Gurewitz, D.B. Johnson. PW-MAC:An energy-efficient predictive-wakeup MAC protocol for wireless sensor networks. In Proc. IEEE INFOCOM Shanghai, China, Apr.2011,1305-1313.
[115]R.R. Choudhury, N.H. Vaiya. MAC-Layer Anycasting in Ad Hoc Networks. Sigcomm Corn-put. Commmun. Rev.34:75-80, Jan.2004.
[116]M. Zorzi and R. R. Rao. Geographic Random Forwarding (GcRaF) for Ad Hoc and Sensor Networks:Energy and Latency Performance. IEEE transactions on Mobile Computing. 2(4):349-365, October 2003.
[117]M. Zorzi and R. R. Rao. Geographic Random Forwarding (GcRaF) for Ad hoc and Sensor Networks:Multihop Performance. IEEE transactions on Mobile Computing.2(4):337-348. October 2003.
[118]F.A. Tobagi and L. Kleinrock. Packet Switching in Radio Channels. Ⅱ:The Hidden Ter-minal Problem in Carrier Sense Multiple-Access and the Busy-Tone Solution. IEEE trans-actions on Communication,23:1417-1433, Dec.1975.
[119]S. Liu, K. Fan, and P. Sinha. CMAC:An energy-efficient mac layer protocol using convergent packet forwarding for wireless sensor networks. ACM Trans. Sen. Netw.,5:1-34. Nov.2009.
[120]J. Kim. X. Lin, N. B. Shroff, and P. Sinha. Minimizing delay and maximizing lifetime for wireless sensor networks with anycast. IEEE/ACM Transactions on Networking,18(2):515-528, April 2010.
[121]J. Kim, X. Lin, and N. B. Shroff. Optimal anycast technique for delay-sensitive energy-constrained asynchronous sensor networks. IEEE/ACM Trans. Netw.19(2):484-497,2011.
[122]F. Ashraf, N.H. Vaidya, R.H. Kravets. Any-MAC: Extending any asynchronous MAC with anycast to improve delay in WSN. In Proc. IEEE SECON, Salt Lake City, Utah, USA, June 2011,19-27.
[123]M. Lucchi, M. Chiani. Distributed Detection of Local Phenomena with Wireless Sensor Networks. In Proc. of IEEE ICC, Cape Town, South Africa, May 2010,1-6.
[124]H. Shu, Q. Liang. Fundamental performance analysis of event detection in wireless sensor networks. In Proc. of IEEE WCNC,3-6 April 2006.2187-2192.
[125]Y. Zou, K. Chakrabarty. A distributed coverage- and connectivity-centric technique for selecting active nodes in wireless sensor networks. IEEE Transactions on Computers. 54(8):978-991,2005.
[126]Y. S. Li, C. Y. Ai, C. T. Vu, et al. Delay-bounded and energy-efficient composite event monitoring in heterogeneous wireless sensor networks. IEEE Transaction on Parallel, and Distributed Systems,21(9):1373-1385,2010.
[127]T. Spyropoulos, K. Psounis, C.S. Raghavendra. Efficient Routing in Intermittently Con-nected Mobile Networks:The Multiple-Copy Case. IEEE Transaction on Networks, 16(1):77-90,2008.
[128]M. Uddin, H. Ahmadi, T. Abdelzaher, R. Kravets. A Low-energy, Multi-copy Inter-contact Routing Protocol for Disaster Response Networks. In Proc. of IEEE SECON. Rome. Italy June 2009,1-9.
[129]U. Acer, P. Giaccon, D. Hay, et al. Timely data delivery in a realistic bus network. In Proc. of IEEE INFOCOM, Shanghai, China,2011,446-450.
[130]A. Elwhishi,P. Ho. K. Naik. B. Shihada. Self Adaptive Contention Aware Routing Pro-tocol for Intermittently Connected Mobile Networks. IEEE Transactions on Parallel and Distributed Systems,accepted,2012.
[131]K. Fall and K. Varadhan。The ns manual.http://www.isi.edu/nsnam/ns.May 2010.
[132]H. Higaki. NeBuST:Low-latency congested sensor data transmission protocol. In Proc. IEEE International Conference on Communications and Information Technology. Aqaba. Jordan,March 2011,36-42.
[133]M.M.Bhuiyan, I. Gondal, J. Kamruzzaman. CODAR: Congestion and Delay Aware Rout-ing to detect time critical events in WSNs. In Proc. IEEE International Conference on Information Networking, Jan.26-28,2011,357-362.
[134]Tao L. Q.. Yu F. Q. ECODA:enhanced congestion detection and avoidance for multiple class of traffic in sensor networks. IEEE Transactions on Consumer Electronics,2010. 56(3):1387-1394.
[135]Yaghmaee M. H., Adjeroh D. Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks. Computer Networks, July 2009, 53(11):1798-1811.
[136]L.B. Le, E. Hossain, A.S. Alfa. Service differentiation in multirate wireless networks with weighted round-robin scheduling and ARQ-based error control. IEEE Transactions on Com-munications, Feb.2006,54(2):208-215.
[137]O. Durmaz Incel, A. Ghosh, B. Krishnamachari, K. Chintalapudi Fast Data Collection in Tree-Based Wireless Sensor Networks. IEEE Transactions on Mobile Computing. Feb. 2011.1536-1233.
[138]T. Peerapol, J. La Richard. Characterization of Queue Fluctuations in Probabilistic AQM Mechanisms. In Proc. ACM SIGMETRICS.200A.283-294.
[139]H. W. Huo, H. K. Zhang. Y. C. Niu, ct al. MSRLab6:An IPv6 wireless sensor networks testbed. In Proc. International Conference on Signal Processing(ICSP),2006.2950-2956.
[140]V. Raghunathan. C. Schurgcrs, Sung Park. M.B. Srivastava. Energy-aware wireless mi-crosensor networks. IEEE Signal Processing Magazine,19(2):40-50.Mar.2002.
[141]Y. Xu, J. Heidemann, and D. Estrin. Geography-informed energy conservation for ad hoc routing. In Proc. Mobicom,2001,70-84.
[142]M.J. Miller. N.H. Vaidya. Minimizing energy consumption in sensor networks using a wakeup radio. IEEE Wireless Communications and Networking Conference(WCNC'04). March 2004,2335-2340.
[143]E. Shih, P. Bahl, and M. Sinclair. Wake on wireless:an event driven energy saving strategy for battery operated devices. In Proc. IEEE MobiCom.Atlanta, Georgia. USA. Sept.2002. 160-171.
[144]B. Karp, H. T. Kung. GPSR: greedy perimeter stateless routing for wireless networks. in Proc. MobiCom'00, Boston, Massachusetts,United States.2000.243-254.
[145]C. Perkins, E. Rover. Ad-hoc on-demand distance vector routing. in Proc. WMCSA'99, New Orleans, Louisiana, USA,1999,90-100.
[146]V. Shnayder, M. Hempstead, B. Chen, et al. Simulating the power consumption of large-scale sensor network applications, in Proc. ACM Sensys. ACM.2004.188-200.
[147]V. Jacobson. Congestion avoidance and control, in Proc. ACM SIGCOMM Computer Com-munication Review,18(4):314-329,1988.
[2]任丰原.黄海宁,林闯.无线传感器网络.软件学报.14(7):1282-1291：2003.
[3]E. H. Callaway. Wireless Sensor Networks: Architectures and Protocols. CRC Press.2004. ISBN:0849318238.
[4]J. Yick, B. Mukherjcc, D. Ghosal. Wireless sensor network survey. Computer Networks, 52(12):2292-2330,2008. ISSN 1389-1286.
[5]J A, Bymc.21 ideas for the 21th century. Business Week,8:78-167,1999.
[6]MIT Technology Review.10 emerging technologies that will change the world. http://www.technologyreview.com/article/13060/page2.February 2003.
[7]L.Atzori,A. Iera, G.Morabito. The internet of things:A survey.Computer Networks, 54(15):2787-2805,2010.ISSN 1389-1286.
[8]IBM.智慧地球赢在中国http://www.ibm.com/smartcrplanet/cn/zh/?re=masthcad
[9]工业和信息化部.物联网“十二五”发展规划.http://kjs.miit.gov.cn/n11293472/n11295040/n11478867/14344522.html
[10]M. Bhushan, R. Rengaswamy. Comprehensive design of a sensor network for chemical plants based on various diagnosability and reliability criteria.1. Framework. Industrial and engineering chemistry research,41(7):1826-1839.2002.
[11]Y. Wang, X. Wang, B. Xie, et al. Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks IEEE Transactions on Mobile Computing,7(6):698-711. June 2008.
[12]Y. Li, Z. Wang, Y. Song. Wireless Sensor Network Design for Wildfire Monitoring. In Proc. of The Sixth World Congress on Intelligent Control and Automation, volume 1.2006, 109-113.
[13]A. Mainwaring, J. Polastre, R. Szewczyk, et al. Wireless sensor networks for habitat. monitoring. In Proc. of ACM WSNA'02, Atlanta. GA. USA. September 2002.88-97.
[14]R.Szewczyk, E. Ostcrweil, J. Polastre, et al. Application driven systems research:habitat monitoring with sensor networks. In Communications of the ACM Special Issue on Sensor Networks,47(6):34-40.June 2004.
[15]V. Dyo, S.A. Ellwood, D.W. Macdonald, et al. Evolution and sustainability of a wildlife monitoring sensor network. In Proc. of the 8th ACM SenSys. ACM, New York, NY, USA.2010,127-140.
[16]Y. Kim, T. Schmid, Z. M. Charbiwala, et al. NAWMS:Nonintrusive Autonomous Water Monitoring System. In Proceedings of ACM SenSys'08. Raleigh. NC. USA, Nov.2008, 309-322.
[17]R. Siuli, S. Bandyopadhyay, Z. M. Charbiwala, ct al. Agro-sense:Precision agriculture using sensor-based wireless mesh networks. In Proceedings of First ITU-T Kaleidoscope Academic Conference on Innovations in NGN:Future Network and Services,2008,383-388.
[18]P. Juang, H. Oki, Y. Wang, et al. Energy-efficient computing for wildlife tracking:design tradeoffs and early experiences with zebranet. SIGARCH Comput. Archit. News,30(5):96-107,2002.
[19]Turtlenet. http://prisms.cs.umass.edu/dome/turtlenet.2007.
[20]L. Riquclmc, J.A. Soto, J. Polastre, et al.Wireless sensor networks for precision horticulture in southern Spain. Comput. Electron. Agric.,68(1):25-35,2009.
[21]Artificial Retina project. http://artificialretina.energy.gov
[22]D.Malan, T. Fulford-Jones, M. Welsh, et al. CodeBlue:an Ad Hoc sensor network in-frastructure for emergency medical care. In Proceedings of Workshop on Applications of Mobile Embedded Systems(WAMES'04), Boston, MA.USA.June 2004.
[23]R. Herlien, T. O'Reilly, K. Headley, et al. An ocean observatory sensor network application. IEEE Sensors,1837-1842,2010.
[24]T.Y. Wang, Q. Cheng. Collaborative event-region and boundary-region detection in wireless sensor networks. IEEE Transactions on Signal Processing,56(6):2547-2560,2008.
[25]K. Ren, K. Zeng, W. Lou. Secure and fault-tolerant event boundary detection in wireless sensor networks. IEEE Transactions on Wireless Communications,7(1):354-363.2008.
[26]N. Hubbell, Han Qi. Detection and tracking of dynamic amorphous events in wireless sensor networks. IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON'11). June 2011.170-178.
[27]M. M. Chen, C. Majidi, D. M. Doolin, et al.. Design and construction of a wildfire instru-mentation system using networked sensors (Poster). Network Embedded Systems Technology (NEST) Retreat Oakland California, USA, June 17-18.2003.
[28]A. Arora, P. Dutta, S. Bapat, et al. A line in the sand: a wireless sensor network for target detection, classification, and tracking. Comput. Netw.,46(5):605-634.2004.
[29]Boomerang shooter detection system.http://bbn.com/boomerang
[30]N. Xu,S. Rangwala, K. K. Chintalapudi, et al. A wireless sensor network for structural monitoring. In SenSys '04:Proceedings of the 2nd international conference on Embedded networked sensor systems. ACM, New York, NY, USA,2004,13-24.
[31]S. Kim, S. Pakzad, D. Culler, et al. Health monitoring of civil infrastructures using wire-less sensor networks. In Proceedings of the 6th international conference on Information processing in sensor networks(IPSN'07). ACM, New York, NY, USA,2007,254-263.
[32]T. He, S. Krishnamurthy, L. luo, ct al. VigilNct:An integrated sensor network system for energy-efficient surveillance. ACM Transactions on Sensor Networks (TOSN). 1(2):1-38, 2006.
[33]F. Lau, E. Oto, H. Aghajan. Color-based multiple agent tracking for wireless image sensor networks. In Proceedings of the Advanced Concepts for Intelligent Vision Systems (ACIVS '06), Springer, Antwerp, Belgium, September 2006.299-310.
[34]FireFly Sensor Networks, http://www.ecc.cmu.edu/firefly/projects.html.
[35]J.Solobera. Detecting Forest Fires using Wireless Sensor Networks with Waspmote. http://www.libelium.com/wireless_sensor_networks_to_detec_forest_fires/
[36]Ian F. Akyildiz, M.C. Vuran. Wireless Sensor Networks. John Wiley & Sons Ltd.2010.
[37]LAN/MAN Standards Committee. IEEE Std 802.15.4-2011 (Revision of IEEE Std 802.15.4-2006). IEEE Standard for Local and metropolitan area networks-Part 15.4:Low-Rate Wireless Personal Area Networks (LR-WPANs). May,2011.
[38]Crossbow technology, http://www.xbow.com.
[39]A. Dunkcls, B. Gronvall, T. Voigt. Contiki- a lightweight and flexible operating system for tiny networked sensors. In Proc. of the 29th Annual IEEE International Conference on Local Computer Networks. Tampa, Florida, USA. Nov.2004,455-462.
[40]Waspmote. Libelium opens access to bluctooth wireless sensor networks. http://www.libelium.com/libcliumworld/articles/101321320500,2009.
[41]The Stargate platform. http://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/Stargate_Datashect.pdf.
[42]CrossBow. Wireless Sensor Networks Product Reference Guide,2007.
[43]Sun Microsystems. Inc. Sun spot world, http://sunspotworld.com/.
[44]A. Rowe, R. Mangharam, R. Rajkumar. FireFly:A Time Synchronized Rcal-Time Sensor Networking Platform. Wireless Ad Hoc Networking:Personal-Area, Local-Area, and the Sensory-Area Networks. CRC Press Book Chapter,November 2006.
[45]SOWNet Technologies. G-Node G301. http://www.sownet.nl/index.php/products/gnode.
[46]National Instruments.Inc. NIWSN-3202. http://sinw.ni.com/nips/cds/view/p/lang/en/nid/206921.
[47]MicroStrain, Inc. Sensors, http://www.microstrain.com/wirclcss/sensors
[48]H. Karl, A. Willig. Protocols and Arhitectures for Wireless Sensor Networks. John Wiley & Sons Ltd,2005.
[49]J.-F. Chambcrland and V. V. Veeravalli. Decentralized Detection in Sensor Networks. IEEE Trans, on Signal Processing,51(2):407-416, February 2003.
[50]杨露菁,余华.多源信息融合理论及应用,第一版.北京.北京邮电大学出版社.2006.
[51]R. Viswanathan and P. Varshney. Distributed detection with multiple sensors:Part I-fundamentals. Proc. of the IEEE,85(1):54-63, Jan.1997.
[52]C. Scott. The Neyman-Pearson Criterion. http://cnx.Org/contcnt/m11548/1.2/
[53]Wikipedia. Q-function. http://en.wikipedia.org/wiki/Q-function
[54]A.Wald. Sequential Test of Statistical Hypothesis. Annals of Mathematical Statistics,1945, 25(5),New York:Wiley and Sons.
[55]Don Johnson. Sequential Hypothesis Testing,http://cnx.org/content/m11242/latest/
[56]L. Yu and A. Ephremides. Detection performance and energy efficiency trade-off in a sensor network, in Proc. of Allerton Conference. Allerton, IL. October 2003.
[57]L. Yu and A. Ephremides. Detection performance and energy efficiency of sequential de-tection in a sensor network, in Proc. of HICSS'06. Hawai, USA.
[58]L. Yu, L. Yuan, G. Qu, and A. Ephremides. Energy-driven detection scheme with guaran-teed accuracy, in Proc. of IPSN'06, Nashville, TN. USA. April 2006. pp.284-291.
[59]T. Q. Quek. D. Dardari, and M. Z. Win. Energy efficiency of dense wireless sensor networks: to cooperate or not to cooperate. IEEE Journal on Selected Areas in Communications. 25(2):459-470,2007.
[60]H.-X. Tan, M.-C. Chan, W. Xiao. P.-Y. Kong, and C.-K. Tham. Information quality aware routing in event-driven sensor networks.in Proc. IEEE INFOCOM,2010,1-9.
[61]J. Zheng, A. Jamalipour. Wireless Sensor Networks-A Networking Perspective. John Wiley & Sons Ltd,2009,351-356.
[62]方维维,钱德沛,刘轶.无线传感器网络传输控制协议.软件学报.19(6)：1439-1451,2008.
[63]B. Hull, K. Jamieson, H. Balakrishnan. Mitigating congestion in wireless sensor network. in Proc. The Second International Conference on Embedded Networked Sensor Systems (SenSys'04), Baltimore, MD, USA,2004,134-147.
[64]C.-Y. Wan, S. B. Eisenman, A. T. Campbell. CODA:congestion detection and avoidance in sensor networks, in Proc. First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003), Los Angeles, California, USA, Nov.2003.266-279.
[65]C. Wang, B. Li, K. Sohraby. Upstream congestion control in wireless sensor networks through cross-layer optimization. IEEE Journal on Selected Areas in Communications. 25(5):786-795,2007.
[66]L. Liang, D. Gao, H. Zhang. A Novel Reliable Transmission Protocol for Urgent Information in Wireless Sensor Networks, in Proc. IEEE GLOBECOM'10, Miami. FL. USA. Dec.2010. 1-6.
[67]O. B. Akan and I. Akyildiz, Event-to-sink reliable transport in wireless sensor networks. IEEE/ACM Transactions on Networking,13(5):1003-1016,2005.
[68]C.-T. Ee, R. Bajcsy. Congestion control and fairness for many-to-one routing in sen-sor networks, in Proc. of 2004 ACM Conference on Embedded Networked Sensor Sys-tems(Sensys'04), Baltimore, MD, Nov.2004.148-161.
[69]S.-J. Park, R. Vedantham, R.. Sivakumar, et al. A scalable approach for reliable downstream data delivery in wireless sensor networks. in Proceedings of 2004 ACM International Sym-posium on Mobile Ad Hoc Networking and Computing (MobiIIoc'04). Roppongi, Japan, May 2004,78-89.
[70]S. Rangwala, R. Gummadi, R. Govindan, et al. Interference-aware fair rate control in wireless sensor networks. In Proceedings of the ACM SIGCOMM.2006,63-74.
[71]C. Wang, K. Sohraby, V. Lawrence, et al. Priority-based congestion control in wireless sensor networks, in Proc. IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06), Taichung. Taiwan. June 2006,22-31.
[72]V. C. Gungor, O. B. Akan, and I. F. Akyildiz. A real-time and reliable transport pro-tocol for wireless sensor and actor networks. IEEE/ACM Transactions on Networking. 16(2):359-370, April 2008.
[73]J. Kang, Y. Zhang, B. Nath, S. Yu. Adaptive Resource Control Scheme to Alleviate Con-gestion in Sensor Networks. In Proceedings of the First Workshop on Broadband Advanced Sensor Networks (BASENETS'04). San Jose, CA. October 2004.
[74]R. Kumar, H. Rowaihy, G.H. Cao, et al. Congestion aware routing in sensor networks. Technical report,2006. htpp://nsrc.cse.psu.edu/tech_report/NAS-TR-0036-2006.pdf
[75]F. Ren, T. He, S. Das, and C. Lin. Traffic-aware dynamic routing to alleviate congestion in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems.2011.
[76]L. Gulluccio, A.T. Campbell, S. Palazzo. Poster Abstract:CONCERT:aggregation-based CONgcstion Control for sEnsoR neTworks. In Proc. of ACM SenSys'05, San Diego,USA, 2005,274-275.
[77]Edith C. H. Ngai, Y. Zhou, Michael R. Lyu, et al. Reliable reporting of delay-sensitive events in wireless sensor-actuator networks. In Proc. of the 3rd IEEE MASS,2006,101-118.
[78]C. Wan, A. T. Campbell. Siphon:Overload traffic management using multi-radio virtual sinks in sensor networks. In Proc. of ACM SenSys'05, San Diego, USA,2005,116-129.
[79]G.-S. Ahn, S.G. Hong, E. Miluzzo, et al. Funneling-MAC:a localized, sink-oriented MAC for boosting fidelity in sensor networks. In Proceedings of the 4th international conference on Embedded networked sensor systems(SenSys'06). Boulder, Colorado, USA.2006,293-306.
[80]A. Woo, D. C. Culler. A transmission control scheme for media acess in sensor networks In Proceedings of ACM Mobicom' 01. Rome, Italy. Jul.2004.16-21.
[81]C. Wang, M. Daneshmand, B. Li, K. Sohraby. A survey of transport protocols for wireless sensor networks. IEEE Network,20(3):34-40,2006.
[82]F. Stann,J. Hcidcmann. RMST:Reliable data transport in senor networks. In Proceedings of IEEE International Workshop on Sensor Network Protocols and Applications(SNPA'03), Anchorage, AK, May 2003.
[83]C. Intanagonwiwat, R.. Govindan, D. Estrin, et al. Directed Diffusion for Wireless Sensor Networks. IEEE/ACM Transactions on Networking,11(1):2-16.2003.
[84]H.Zhang,A. Arora. Y. Choi, et al. Reliable bursty convergecast in wireless sensor networks. In Proc. of The ACM Mobihoc'05, Urbana-Champaign. IL. May 2005,266-276.
[85]I.S. Reed, G. Solomon. ReedSolomon error correction. http://en.wikipedia.org/wiki/Reed-Solomon_error_correction
[86]M. Luby. LT codes. In Proceedings of The 43rd Annual IEEE Symposium on Foundations of Computer Science.271-280,2002.
[87]A. Shokrollahi. Raptor codes. IEEE Transactions on Information Theonry,52(6):2551-2567, 2006.
[88]S. Kim, R. Fonseca, D. Culler. Reliable transfer on wireless sensor networks. In Proc. of The IEEE SECON'04,2004,449-459.
[89]R. Fonseca, S. Ratnasamy, J. Zhao, et al. Beacon vector routing:scalable point-to-point routing in wireless sensornets. In Proceedings of the 2nd conference on Symposium on Net-worked Systems Design & Implementation- Volume 2(NSDI'05), Berkeley. CA, USA,2005. 329-342.
[90]B. Deb, S. Bhatnagar, and B. Nath. ReInForM:Reliable Information Forwarding using Multiple Paths in Sensor Networks. In Proceedings of the 28th Annual IEEE Conference on Local Computer Networks(LCN 2003), Bonn, Germany. October 2003.
[91]E. Felemban, C.G. Lee, E. Ekici. MMSPEED:Multipath Multi-SPEED Protocol for QoS Guarantee of Reliability and Timeliness in Wireless Sensor Networks. IEEE Transactions on Mobile Computing,5(6):738-754,2006.
[92]T. He, J.A. Stankovic. C. Lu, ct al. SPEED:a stateless protocol for real-time communica-tion in sensor networks. In Proc. of 23rd International Conference on Distributed Computing Systems, May 2003,46-55.
[93]W. Ye, J. Hcidemann,and D. Estrin. An energy-efficient mac protocol for wireless sensor networks. In Proc. IEEE INFOCOM,New York. NY. USA. Jun.2002,1567-1576.
[94]R. Mishra, S. Nayak, K. Verma, and D. Singh. Survey on techniques to resolve problems associated with rts/cts mechanism. In Proc. ACM ICCCS. New York. NY. USA:ACM, 2011,86-91.
[95]W. Ye, J. Heidemann, and D. Estrin. Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/Acm Transactions on Networking,12(3):493-506,2004.
[96]T. Van Dam and K. Langendoen. An adaptive energy-efficient mac protocol for wireless sensor networks. In Proc. ACM Sensys.ACM,2003.171-180.
[97]G. Lu, B. Krishnamachari, C.S. Raghavendra. An adaptive energy-efficient and low-latency MAC for tree-based data gathering in sensor networks. Wiley Wireless Communications and Mobille Computing.7:863-875,2007.
[98]W. Ye, F. Silva, and J. Heidemann. Ultra-low duty cycle MAC with scheduled channel polling. In Proc. ACM Sensys. Boulder, Colorado. USA. ACM.2006.321-334.
[99]S. Du, A. Saha, and D. Johnson. RMAC:A routing-enhanced duty-cycle mac protocol for wireless sensor networks. In Proc. IEEE INFOCOM. Anchorage. Alaska, USA:IEEE, May 2007,1478-1486.
[100]J. Elson, L. Girod, and D. Estrin. Fine-grained network time synchronization using refer-ence broadcasts. In Proc. Fifth Symposium on Operating Systems Design and Implementa-tion (OSDI 2002). Dec.2002.
[101]S. Ganeriwal, R. Kumar, and M. B. Srivastava. Timing-sync protocol for sensor networks. In Proc. ACM Sensys. ACM, Nov.2003,138-149.
[102]Y. Sun, S. Du, O. Gurewitz, and D. Johnson. DW-MAC:a low latency, energy effi-cient demand-wakeup mac protocol for wireless sensor networks. In Proc. ACM Mobi-Hoc.HongKong, China:ACM, May 2008,53-62.
[103]T. Canli, A. Khokhar. PRMAC:Pipelined Routing Enhanced MAC Protocol for Wireless Sensor Networks. In Proc. IEEE International Conference on Communications(ICC'09). June 2009,1-5.
[104]J. Polastre, J. Hill, and D. Culler. Versatile low power media access for wireless sensor networks. In Proc. ACM Sensys.Baltimore, Maryland:ACM. Nov.2004,95-107.
[105]A. El-Hoiydi and J. Decotignie. WiseMAC:An ultra low power mac protocol for multi-hop wireless sensor networks. Algorithmic Aspects of Wireless Sensor Networks.18-31.2004.
[106]J. Polastrc, J. Hui, P. Levis, ct al. A unifying link abstraction for wireless sensor networks. In Proc. ACM SenSys.2005,76-89.
[107]M. Buettner, G. Yee, E. Anderson, and R. Han. X-MAC:a short preamble mac protocol for duty-cycled wireless sensor networks. In Proc. ACM Sensys. Boulder, Colorado, USA,ACM, 2006,307-320.
[108]J. J. Garcia-Luna-Aceves and A. Tzamaloukas. Reversing the Collision-Avoidance Hand-shake in Wireless Networks. In Proc. ACM/IEEE Mobicom,1999.120-131.
[109]Amre El-Hoiydi and Jean-Dominique Decotignie. Low Power Downlink MAC Proto-cols for Infrastructure Wireless Sensor Networks. Mobile Networks and Applications, 10(5):675-690,2005.
[110]R.. Musaloiu-E., C. M. Liang, and A. Terzis. Koala: Ultra-Low Power Data Retrieval in Wireless Sensor Networks. In Proc. ACM IPSN. April 2008,421-432.
[111]Y. Sun, O. Gurewitz, and D. Johnson. RI-MAC:a receiver-initiated asynchronous duty cycle mac protocol for dynamic traffic loads in wireless sensor networks. In Proc. ACM Sensys. Raleigh, NC, USA, ACM,2008,1-14.
[112]Y. Peng, Z. Li, D. Qiao, and W. Zhang. Delay-bounded mac with minimal idle listening for sensor networks. In Proc. IEEE LNFOCOM.Shanghai. China. Apr.2011.1314-1322.
[113]R. Krashinsky and H. Balakrishnan。 Minimizing energy for wireless web access with bounded slowdown, in Proc.IEEE Mobicom.2002.
[114]L. Tang, Y. Sun, O. Gurewitz, D.B. Johnson. PW-MAC:An energy-efficient predictive-wakeup MAC protocol for wireless sensor networks. In Proc. IEEE INFOCOM Shanghai, China, Apr.2011,1305-1313.
[115]R.R. Choudhury, N.H. Vaiya. MAC-Layer Anycasting in Ad Hoc Networks. Sigcomm Corn-put. Commmun. Rev.34:75-80, Jan.2004.
[116]M. Zorzi and R. R. Rao. Geographic Random Forwarding (GcRaF) for Ad Hoc and Sensor Networks:Energy and Latency Performance. IEEE transactions on Mobile Computing. 2(4):349-365, October 2003.
[117]M. Zorzi and R. R. Rao. Geographic Random Forwarding (GcRaF) for Ad hoc and Sensor Networks:Multihop Performance. IEEE transactions on Mobile Computing.2(4):337-348. October 2003.
[118]F.A. Tobagi and L. Kleinrock. Packet Switching in Radio Channels. Ⅱ:The Hidden Ter-minal Problem in Carrier Sense Multiple-Access and the Busy-Tone Solution. IEEE trans-actions on Communication,23:1417-1433, Dec.1975.
[119]S. Liu, K. Fan, and P. Sinha. CMAC:An energy-efficient mac layer protocol using convergent packet forwarding for wireless sensor networks. ACM Trans. Sen. Netw.,5:1-34. Nov.2009.
[120]J. Kim. X. Lin, N. B. Shroff, and P. Sinha. Minimizing delay and maximizing lifetime for wireless sensor networks with anycast. IEEE/ACM Transactions on Networking,18(2):515-528, April 2010.
[121]J. Kim, X. Lin, and N. B. Shroff. Optimal anycast technique for delay-sensitive energy-constrained asynchronous sensor networks. IEEE/ACM Trans. Netw.19(2):484-497,2011.
[122]F. Ashraf, N.H. Vaidya, R.H. Kravets. Any-MAC: Extending any asynchronous MAC with anycast to improve delay in WSN. In Proc. IEEE SECON, Salt Lake City, Utah, USA, June 2011,19-27.
[123]M. Lucchi, M. Chiani. Distributed Detection of Local Phenomena with Wireless Sensor Networks. In Proc. of IEEE ICC, Cape Town, South Africa, May 2010,1-6.
[124]H. Shu, Q. Liang. Fundamental performance analysis of event detection in wireless sensor networks. In Proc. of IEEE WCNC,3-6 April 2006.2187-2192.
[125]Y. Zou, K. Chakrabarty. A distributed coverage- and connectivity-centric technique for selecting active nodes in wireless sensor networks. IEEE Transactions on Computers. 54(8):978-991,2005.
[126]Y. S. Li, C. Y. Ai, C. T. Vu, et al. Delay-bounded and energy-efficient composite event monitoring in heterogeneous wireless sensor networks. IEEE Transaction on Parallel, and Distributed Systems,21(9):1373-1385,2010.
[127]T. Spyropoulos, K. Psounis, C.S. Raghavendra. Efficient Routing in Intermittently Con-nected Mobile Networks:The Multiple-Copy Case. IEEE Transaction on Networks, 16(1):77-90,2008.
[128]M. Uddin, H. Ahmadi, T. Abdelzaher, R. Kravets. A Low-energy, Multi-copy Inter-contact Routing Protocol for Disaster Response Networks. In Proc. of IEEE SECON. Rome. Italy June 2009,1-9.
[129]U. Acer, P. Giaccon, D. Hay, et al. Timely data delivery in a realistic bus network. In Proc. of IEEE INFOCOM, Shanghai, China,2011,446-450.
[130]A. Elwhishi,P. Ho. K. Naik. B. Shihada. Self Adaptive Contention Aware Routing Pro-tocol for Intermittently Connected Mobile Networks. IEEE Transactions on Parallel and Distributed Systems,accepted,2012.
[131]K. Fall and K. Varadhan。The ns manual.http://www.isi.edu/nsnam/ns.May 2010.
[132]H. Higaki. NeBuST:Low-latency congested sensor data transmission protocol. In Proc. IEEE International Conference on Communications and Information Technology. Aqaba. Jordan,March 2011,36-42.
[133]M.M.Bhuiyan, I. Gondal, J. Kamruzzaman. CODAR: Congestion and Delay Aware Rout-ing to detect time critical events in WSNs. In Proc. IEEE International Conference on Information Networking, Jan.26-28,2011,357-362.
[134]Tao L. Q.. Yu F. Q. ECODA:enhanced congestion detection and avoidance for multiple class of traffic in sensor networks. IEEE Transactions on Consumer Electronics,2010. 56(3):1387-1394.
[135]Yaghmaee M. H., Adjeroh D. Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks. Computer Networks, July 2009, 53(11):1798-1811.
[136]L.B. Le, E. Hossain, A.S. Alfa. Service differentiation in multirate wireless networks with weighted round-robin scheduling and ARQ-based error control. IEEE Transactions on Com-munications, Feb.2006,54(2):208-215.
[137]O. Durmaz Incel, A. Ghosh, B. Krishnamachari, K. Chintalapudi Fast Data Collection in Tree-Based Wireless Sensor Networks. IEEE Transactions on Mobile Computing. Feb. 2011.1536-1233.
[138]T. Peerapol, J. La Richard. Characterization of Queue Fluctuations in Probabilistic AQM Mechanisms. In Proc. ACM SIGMETRICS.200A.283-294.
[139]H. W. Huo, H. K. Zhang. Y. C. Niu, ct al. MSRLab6:An IPv6 wireless sensor networks testbed. In Proc. International Conference on Signal Processing(ICSP),2006.2950-2956.
[140]V. Raghunathan. C. Schurgcrs, Sung Park. M.B. Srivastava. Energy-aware wireless mi-crosensor networks. IEEE Signal Processing Magazine,19(2):40-50.Mar.2002.
[141]Y. Xu, J. Heidemann, and D. Estrin. Geography-informed energy conservation for ad hoc routing. In Proc. Mobicom,2001,70-84.
[142]M.J. Miller. N.H. Vaidya. Minimizing energy consumption in sensor networks using a wakeup radio. IEEE Wireless Communications and Networking Conference(WCNC'04). March 2004,2335-2340.
[143]E. Shih, P. Bahl, and M. Sinclair. Wake on wireless:an event driven energy saving strategy for battery operated devices. In Proc. IEEE MobiCom.Atlanta, Georgia. USA. Sept.2002. 160-171.
[144]B. Karp, H. T. Kung. GPSR: greedy perimeter stateless routing for wireless networks. in Proc. MobiCom'00, Boston, Massachusetts,United States.2000.243-254.
[145]C. Perkins, E. Rover. Ad-hoc on-demand distance vector routing. in Proc. WMCSA'99, New Orleans, Louisiana, USA,1999,90-100.
[146]V. Shnayder, M. Hempstead, B. Chen, et al. Simulating the power consumption of large-scale sensor network applications, in Proc. ACM Sensys. ACM.2004.188-200.
[147]V. Jacobson. Congestion avoidance and control, in Proc. ACM SIGCOMM Computer Com-munication Review,18(4):314-329,1988.