Jamming and Lost Link Detection in Wireless Networks with Fuzzy Logic
H. Reyes, and N. Kaabouch. International Journal of Scientific & Engineering Research, (February 2013)
Abstract
This paper presents a fuzzy logic technique to detect link loss in wireless networks. The system uses the parameters CCA (Clear Channel Assessment), BPR (Bad Packet Ratio), PDR (Packet Delivery Ratio) and RSS (Received Strength Signal) as inputs to assess the status of the link and in case it is lost determine the cause of the link failure. A fuzzy inference system inputs the aforementioned metrics to yield a jamming index JI used for the system to know how jammed a node is. Field tests were performed to verify the efficiency of the system. The results of the tests showed 98.40% and 95.25 % efficiency under constant and random jamming, respectively.
%0 Journal Article
%1 Reyes13
%A Reyes, Héctor Iván
%A Kaabouch, Naima
%D 2013
%J International Journal of Scientific & Engineering Research
%K detection experimental fuzzylogic jamming security simulation
%N 2
%T Jamming and Lost Link Detection in Wireless Networks with Fuzzy Logic
%V 4
%X This paper presents a fuzzy logic technique to detect link loss in wireless networks. The system uses the parameters CCA (Clear Channel Assessment), BPR (Bad Packet Ratio), PDR (Packet Delivery Ratio) and RSS (Received Strength Signal) as inputs to assess the status of the link and in case it is lost determine the cause of the link failure. A fuzzy inference system inputs the aforementioned metrics to yield a jamming index JI used for the system to know how jammed a node is. Field tests were performed to verify the efficiency of the system. The results of the tests showed 98.40% and 95.25 % efficiency under constant and random jamming, respectively.
@article{Reyes13,
abstract = {This paper presents a fuzzy logic technique to detect link loss in wireless networks. The system uses the parameters CCA (Clear Channel Assessment), BPR (Bad Packet Ratio), PDR (Packet Delivery Ratio) and RSS (Received Strength Signal) as inputs to assess the status of the link and in case it is lost determine the cause of the link failure. A fuzzy inference system inputs the aforementioned metrics to yield a jamming index JI used for the system to know how jammed a node is. Field tests were performed to verify the efficiency of the system. The results of the tests showed 98.40% and 95.25 % efficiency under constant and random jamming, respectively.},
added-at = {2013-08-29T16:03:06.000+0200},
author = {Reyes, Héctor Iván and Kaabouch, Naima},
biburl = {https://www.bibsonomy.org/bibtex/27fbe29b10ce83411c3e96809f51cc486/affitz},
interhash = {0db6c7ef49a56e1e1ec1d855e7442616},
intrahash = {7fbe29b10ce83411c3e96809f51cc486},
journal = {International Journal of Scientific & Engineering Research},
keywords = {detection experimental fuzzylogic jamming security simulation},
month = feb,
number = 2,
timestamp = {2013-09-25T10:49:14.000+0200},
title = {Jamming and Lost Link Detection in Wireless Networks with Fuzzy Logic},
volume = 4,
year = 2013
}