DocumentCode :
2264834
Title :
Impact of Deployment Point Arrangement on Intrusion Detection in Wireless Sensor Networks
Author :
Wang, Yun ; Lun, Zhendong
Author_Institution :
Dept. of Comput. Sci. Southern, Illinois Univ. Edwardsville, Edwardsville, IL, USA
fYear :
2010
fDate :
17-19 Aug. 2010
Firstpage :
421
Lastpage :
423
Abstract :
This paper introduces a novel deployment strategy to leverage the advantages of both Poisson and Gaussian distributions in random sensor deployment for intrusion detection. The basic idea is to employ multiple deployment points in the area of interest. How to choose the number and locations of the k deployment points for optimizing the network performance under given network investment is therefore a must-answer question. This paper theoretically and experimentally explores the problem under multi-level sensing and detection model. Simulation outcomes are shown to match very well with the theoretical results and validate the effectiveness of the proposed approach and the correctness of the modeling and analysis. This work provides insight on choosing the appropriate number of deployment points and their placement for efficient intrusion detection given arbitrary application requirements.
Keywords :
safety systems; sensor placement; wireless sensor networks; Gaussian distribution; Poisson distribution; deployment point arrangement; intrusion detection; random sensor deployment; wireless sensor networks; Analytical models; Gaussian distribution; Intrusion detection; Mobile communication; Mobile computing; Sensors; Wireless sensor networks; Gaussian distribution; Intrusion detection; Network deployment; Performance evaluation; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS), 2010 IEEE International Symposium on
Conference_Location :
Miami Beach, FL
ISSN :
1526-7539
Print_ISBN :
978-1-4244-8181-1
Type :
conf
DOI :
10.1109/MASCOTS.2010.56
Filename :
5581556
Link To Document :
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