期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

延迟容忍移动传感器网络中基于概率复制的数据传输策略及其性能研究 被引量：9

Data Delivery Scheme of DTMSN Based on Probability Replication and Its Performance Research
下载PDF
导出
摘要 该文提出了一种基于概率复制的数据传输策略PRD(Probability Replication Delivery scheme)用于空间中间断连通的延迟容忍移动传感器网络(DTMSN)数据传输。PRD由选择复制策略和队列管理组成,前者根据节点将消息传递给汇聚点的可能性,选择下一跳进行复制传输;队列管理则利用引入传输概率及复制数的消息生存时间决定队列中消息丢弃原则。仿真分析表明,与现有的几种数据传输策略相比,PRD能以较低的数据复制数及传输延迟获得较高的数据传输成功率。 A new data delivery scheme-PRD （Probability Replication Delivery scheme） is proposed for pervasive data gathering in DTMSN （Delay Tolerant Mobile Sensor Networks） that networks with intermittent connectivity in space.PRD consists of two key components for data transmission and queue management,respectively.The former makes decisions on when and where to transmit data messages according to the node delivery probability.The latter employs the message survival time based on probability and delivery copies to decide dropping for minimizing transmission overhead.Simulation results show that the proposed PRD data delivery scheme achieves the higher message delivery ratio with the lower transmission overhead and data delivery delay than other DTMSN data delivering approaches.
作者 张可 曾家智 刘伟
机构地区 电子科技大学电子科学技术研究院 电子科技大学计算机科学与工程学院
出处 《电子与信息学报》 EI CSCD 北大核心 2010年第3期677-681,共5页 Journal of Electronics & Information Technology
基金 国家自然科学基金(60703114 60673142) 电子科技大学青年科技基金(JX0862)资助课题
关键词 延迟容忍移动传感器网络 数据采集 概率复制 数据传输 队列管理 DTMSN Data gathering Probability replication Data delivery Queue management
分类号 TP393 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献11

  • 1罗武胜,翟永平,鲁琴.无线多媒体传感器网络研究[J].电子与信息学报,2008,30(6):1511-1516. 被引量：52
  • 2Verdone R. A statistical analysis of wireless connectivity in three dimensions. IEEE International Conference on Communications(ICC2005)[C]. Seoul, 2005: 3207-3210.
  • 3Wang Y, Lin F, and Wu H. Poster: efficient data transmission in delay fault tolerant mobile sensor networks (DFT-MSN), Proceedings of IEEE International Conference on Network Protocols (ICNP'05) [C]. Boston, 2005: 1-2.
  • 4Lin Yun-feng, Li Bao-chun, and Liang Ben. Efficient network coded data transmissions in disruption tolerant networks. Proceedings of IEEE INFOCOM 2008 [C]. Phoenix, 2008: 2080-2188.
  • 5Luo Pei-en, Huang Hong-yu, Shu Wei, Li Ming-lu, and Wu Min-you. Performance evaluation of Routing under realistic mobility vehicular DTN models. Wireless Communications and Networking Conference[C]. Las Vegas, 2008: 2206-2211.
  • 6Shah R C, Roy S, Jain S, and Brunette W. Data MULEs: modeling a three-tier architecture for sparse sensor networks. Proc. of the First International Workshop on Sensor Network Protocols and Applications[C]. Anchorage 2003: 30-41.
  • 7Wang Y and Wu H. Delay/fault-tolerant mobile sensor network (DFT-MSN): A new paradigm for pervasive information gathering[J]. IEEE Transactions on Mobile Computing, 2006, 6(8): 1021-1034.
  • 8Zhang H, Shen H, and Tan Y. Optimal energy balanced data gathering in wireless sensor networks. Parallel and Distributed Processing Symposium[C]. Long Beach, 2007: 1-10.
  • 9Wang Y, Wu H Y, and Dang H. Analytic study of delay/fault-tolerant mobile sensor networks (DFT-MSN's) [R]. Tech Report, Lafayette: CACS, University of Louisiana at Lafayette, 2006.
  • 10Zhu J Q, Cao J N, Liu M, Zheng Y, Gong H G, and Chen G H. Mobility prediction-based adaptive data gathering protocol. IEEE Global Telecommunications Conference[C] New Orleans, 2008: 1-5.

二级参考文献30

  • 1马华东,陶丹.多媒体传感器网络及其研究进展[J].软件学报,2006,17(9):2013-2028. 被引量：186
  • 2Chang C K and Huang J. Video surveillance for hazardous conditions using sensor networks. Proc. of the 2004 IEEE Int'l Conf. on Networking, Sensing & Control. New York, 2004: 1008-1013.
  • 3Holman R, Stanley J, and Ozkan-Haller T. Applying video sensor networks to nearshore environment monitoring. IEEE Trans. on Pervasive Computing, 2003, 2(4): 14-21.
  • 4Reeves A A. Remote monitoring of patients suffering from early symptoms of dementia. Intl. Workshop on Wearable and Implantable Body Sensor Networks, London, UK, April 2005: 21-23.
  • 5Hu F and Kumar S. Multimedia query with QoS considerations for wireless sensor networks in telemedicine. Proc.of Society of Photo-Optical Instrumentation Engineers -Intl. Conf. on Internet Multimedia Management Systems, Orlando, FL, September 2003: 21-30.
  • 6Paradiso J and Starner T. Energy scavenging for mobile andwireless electronics. IEEE Perv. Comput, 2005, 4(1): 18-27.
  • 7Akyildiz I, Melodia T, and Chowdhury K R. A survey on wireless multimedia sensor networks. Computer Networks, 2007, 5(1): 921-960.
  • 8Rabaey J, et al.. PicoRadio: Ad-hoc wireless networking of ubiquitous low-energy sensor/monitor nodes. Proceedings of the IEEE Computer Society Workshop on VLSI 2000.System Design for a System-on-Chip Era[C]. Los Alamitos, CA, USA, 2000: 9-12.
  • 9Ye W, Heidemann J, and Estrin D. Medium access control with coordinated, adaptive sleeping for wireless sensor networks. IEEE Trans. on Network, 2004, 12(3): 493-506.
  • 10Callaway Edgar H. Wireless Sensor Networks Architectures and Protocols[M]. Florida, USA: Auerbach Publications, 2003: 71-78.

共引文献51

同被引文献95

  • 1刘明,龚海刚,毛莺池,陈力军,谢立.高效节能的传感器网络数据收集和聚合协议[J].软件学报,2005,16(12):2106-2116. 被引量：65
  • 2Burleigh S, Hooke A, Torgerson L, Fall K, Cerf V, Durst B, and Scott K. Delay-Tolerant networking: an approach to interplanetary Internet[J]. IEEE Communications Magazine, 2003, 41(6): 128-136.
  • 3Krishnan R, Basu P, Mikkelson J M, Small C, and Ramanathan R. The SPINDLE disruption-tolerant networking system[C]. IEEE Military Communications Conference, Orlando, FL, USA, 2007: 1-7.
  • 4Sadler P Z C, Liu T, Fishchhoff I, Martonosi M, Lyon S, and Rubenstein D I. Habitat Monitoring with ZebraNet: Design and Experiences [M].Wireless Sensor Networks: A Systems Perspective, Artech House, 2005.
  • 5Fall K. A delay-tolerant network architecture for challenged Internets[C]. Proc. of the 2003 Conf. on Applications, Technologies, Architectures, and Protocols for Computer ColIununications. Karlsruhe: ACM, 2003: 27-34.
  • 6Zhang H, Shen H, and Tan Y. Optimal energy balanced data gathering in wireless sensor networks[C]. Parallel and Distributed Processing Symposium. Long Beach, 2007: 1-10.
  • 7Juang P, Oki H, Wang Y, Martonosi M, Peh L S, and Rubenstein A D. Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet[J]. ACM SIGOPS Operating Systems Review, 2002, 36(5): 96-107.
  • 8Wang Y and Wu H. Replication-based efficient data delivery scheme (RED) for delay/fault-tolerant mobile sensor network (DFT-MSN) [C]. Proc. of the 4th Annual IEEE Int'l Conf. onPervasive Computing and Communications Workshops. Washington: IEEE Computer Society, 2006: 485-489.
  • 9Muhammad Abdulla and Robert Simon. Simulation study of common mobility models for opportunistic networks[C]. Simulation Symposium,ANSS2008, 41st Annual, Ottawa, 2008: 43-50.
  • 10Krifa A, Barakat C, and Spyropoulos T. Optimal buffer management policies for delay tolerant networks[C]. Proc. of IEEE SECON, San Francisco, 2008: 260-268.

引证文献9

二级引证文献28

电子与信息学报
2010年 第3期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部