Lossy nodes inference based on end-to-end passive monitoring in wireless sensor networks
Lossy nodes inference based on end-to-end passive monitoring in wireless sensor networks
参考文献20
-
1Turau v, Witt M, Venzke M. Field trials with wireless sensor networks: issues and remedies. In: Proceedings of International Multi-Conference on Computing in the Global Information Technology, Bucharest, Romania, 2006.
-
2Article No. 86 Langendoen K, Baggio A, Visser O. Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture. In: Proceedings of the 20th International Parallel and Distributed Processing Symposium, Rhodes Island, Greece, 2006. 8-15.
-
3Li Y J, Cai W D, Wang W, et aI. Lossy node identification in wireless sensor network. In: Proceedings of the 5th IEEE International Symposium on Network Computing and Applications, Washington, USA, 2006. 255-258.
-
4Rost S, Balakrishnan H. Memento: a health monitoring system for wireless sensor networks. In: Proceedings of the 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks, Reston, USA, 2006. 575-584.
-
5Meng X Q, Nandagopal T, Li L, et al. Contour maps: monitoring and diagnosis in sensor networks. Computer Networks, 2006, 50(15): 2820-2838.
-
6Ramanathan N, Chang K, Kapur R, et al. Sympathy for the sensor network debugger. In: Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, San Diego, USA, 2005. 255-267.
-
7Gupta S, Zheng R, Cheng A M K. ANDES: an anomaly detection system for wireless sensor networks. In: Proceedings of IEEE International Conference on Mobile Ad-hoc and Sensor Systems, Pisa, Italy, 2007. 1-9.
-
8Meier A, Motani M, Hu S Q, et aI. DiMo: distributed node monitoring in wireless sensor networks. In: Proceedings of the II th International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Vancouver, Canada, 2008. 117-121.
-
9Hartl G, Li B C. Loss inference in wireless sensor networks based on data aggregation. In: Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks, Berkeley, USA, 2004. 396-404.
-
10Mao Y Y, Kschischang F R, Li B C, et aI. A factor graph approach to link loss monitoring in wireless sensor networks. IEEE Journal on Selected Areas in Communications, 2005, 23(4): 820-829.
-
1罗超,李义杰,罗丹.流数据频繁项算法研究[J].辽宁工程技术大学学报（自然科学版）,2004,23(z1):57-59.
-
2杨立.基于权重的流数据频繁项挖掘算法的应用[J].微型机与应用,2011,30(2):106-108.
-
3赵德斌,唐剑琪,孙晓艳.An adaptive hybrid DPCM/DCT coding approach forhigh quality image compression[J].Journal of Harbin Institute of Technology(New Series),1999,6(3):77-81.
-
4Xiaozheng JIN Guanghong YANG.Distributed adaptive fault-tolerant control against actuator faults and lossy interconnection links[J].控制理论与应用（英文版）,2009,7(4):411-418.
-
5王刚,方杰冉,王洪金.Focusing of a Flat Left-Handed Metamaterial Lens in a Heterogeneous and Lossy Medium[J].Chinese Physics Letters,2009,26(5):240-243.
-
6陆慧娟,刘亚卿,夏海霞,陈贺婉.6LoWPAN网络中RPL路由协议的仿真与研究[J].小型微型计算机系统,2016,37(1):83-87. 被引量：9
-
7王国栋,王钢.有损链路环境下移动Ad Hoc网中一种具有能量效率和负载均衡的地理路由算法(英文)[J].Chinese Journal of Aeronautics,2010,23(3):334-340. 被引量：2
-
8刘春,郑征,蔡开元,张师超.数据流频繁闭集的在线挖掘[J].北京航空航天大学学报,2008,34(8):969-972. 被引量：2
-
9张广路,雷景生,吴兴惠.界标窗口中数据流频繁模式挖掘算法研究[J].计算机工程,2012,38(1):55-58. 被引量：1
-
10张广路,雷景生.界标窗口数据流频繁模式挖掘特性[J].计算机工程与应用,2011,47(10):131-134.
