Title | ||
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Normal Vector Based Fault-Tolerant Event Boundary Detection in Wireless Sensor Networks |
Abstract | ||
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This paper presented a distributed fault-tolerant event boundary detection scheme for wireless sensor networks. In this paper, the node coordinate and its reading were mapped on a 3D mesh surface, By comparing the node normal vector got by Normal Vector Based Fault-Tolerant Event Boundary Detection (NVBD) with a predefined threshold, the event boundary nodes are found. This approach was composed of two major tasks: (1) detecting the faulty node and then replacing its detection value with its neighbors' weighted median value, (2) computing node normal vector using its neighbors' detection values. Then we compared it with a threshold to judge if it is a boundary node. The results of numerical simulations show that the NVBD scheme can achieve a substantial improvement on detection performance. |
Year | DOI | Venue |
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2013 | 10.1109/TrustCom.2013.160 | TrustCom/ISPA/IUCC |
Keywords | Field | DocType |
weighted median value,3d mesh surface,detection performance,faulty node,nvbd scheme,node coordinate,event boundary node,mesh generation,fault tolerant computing,faulty node detection,node normal vector,boundary node,event boundary detection,distributed fault-tolerant event boundary detection scheme,fault-tolerant event boundary detection,normal vector based fault-tolerant event boundary detection,nvbd,predefined threshold,detection value,event boundary nodes,wireless sensor networks,fault tolerant,distributed processing,normal vector,fault detection,fault tolerance,fitting,vectors | Key distribution in wireless sensor networks,Polygon mesh,Computer science,Computer network,Weighted median,Real-time computing,Event horizon,Fault tolerance,Wireless sensor network,Normal,Mesh generation | Conference |
ISSN | Citations | PageRank |
2324-898X | 0 | 0.34 |
References | Authors | |
10 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Wei Wang | 1 | 257 | 34.45 |
ruihua zhang | 2 | 73 | 5.60 |
Zhongwei Chen | 3 | 0 | 0.34 |
Lei Ju | 4 | 0 | 0.34 |