DocumentCode
1938139
Title
Three Dimensional Intrusion Objects Detection under Randomized Scheduling Algorithm in Sensor Networks
Author
Zhang, Yanping ; Xiao, Yang ; Wu, Kui ; Du, Xiaojiang ; Sun, Bo
Author_Institution
Dept. of Comput. Sci., Univ. of Alabama, Tuscaloosa, AL
fYear
2008
fDate
10-12 Dec. 2008
Firstpage
16
Lastpage
22
Abstract
Wireless sensor networks are widely used for monitoring applications. The monitored area and the intrusion object are mostly three dimensional. In this paper, we are particularly interested in a sensor network used for monitoring a field to detect intrusion objects such as submarine in some sea area, or goods on shelves in warehouse. In these applications, sensors float in different depth of water or on different height of shelves in three dimensional situations. Since sensor nodes have limited energy supply, sensor networks may be configured to put some sensor nodes in sleep mode to save energy. This is a special case of a randomized scheduling algorithm. In this paper, we study the performance of several randomized scheduling algorithms in terms of intrusion coverage intensity when an intrusion object is considered to occupy a three dimensional space. We study the impact of the size of intrusion object on the sensor networkpsilas configuration.
Keywords
object detection; randomised algorithms; scheduling; telecommunication network reliability; wireless sensor networks; energy saving; field monitoring application; randomized scheduling algorithm; three-dimensional intrusion object detection; wireless sensor network lifetime; Biomedical monitoring; Computer science; Computerized monitoring; Energy consumption; Energy efficiency; Intrusion detection; Object detection; Scheduling algorithm; Underwater vehicles; Wireless sensor networks; Intrusion Detection; Randomized Scheduling Algorithm; Sensor Networks; Three Dimensional;
fLanguage
English
Publisher
ieee
Conference_Titel
Mobile Ad-hoc and Sensor Networks, 2008. MSN 2008. The 4th International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3457-2
Type
conf
DOI
10.1109/MSN.2008.34
Filename
4721243
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