We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Performance Analysis of Dynamic Wireless Sensor Networks using Linguistic Fuzzy

by Zainab Hassan Fakhri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 2
Year of Publication: 2014
Authors: Zainab Hassan Fakhri
10.5120/15182-3529

Zainab Hassan Fakhri . Performance Analysis of Dynamic Wireless Sensor Networks using Linguistic Fuzzy. International Journal of Computer Applications. 87, 2 ( February 2014), 33-39. DOI=10.5120/15182-3529

@article{ 10.5120/15182-3529,
author = { Zainab Hassan Fakhri },
title = { Performance Analysis of Dynamic Wireless Sensor Networks using Linguistic Fuzzy },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 2 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 33-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number2/15182-3529/ },
doi = { 10.5120/15182-3529 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:54.597234+05:30
%A Zainab Hassan Fakhri
%T Performance Analysis of Dynamic Wireless Sensor Networks using Linguistic Fuzzy
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 2
%P 33-39
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Wireless sensor networks (WSNs) are becoming very popular due to their large use in many of applications such as monitoring and collecting data from undisturbed dangerous environments. But the nodes in a sensor network are severely affected by energy. Reducing energy consumption of nodes to increase the network lifetime is considered as a most important challenge, so this paper will simulate the Linguistic Fuzzy Trust Model (LFTM) over dynamic Wireless Sensor Networks to save energy and shows the effect of dynamics in the per-formance of the model. A comparison in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length is also presented between LFTM model over dynamic WSNs and LFTM model over static WSNs. Also in this paper, a compari¬son between the Linguistic Fuzzy Trust Model (LFTM) and the Bio-inspired Trust and Reputation Model for Wireless Sensor Networks (BTRM-WSN) is achieved in terms of the accuracy and the average path length. Both models will give quite good and accurate out¬comes over dynamic Wireless Sensor Networks.

References
  1. L. Akyildiz, W. Su, Y. Sankarasubramanian and E. Cayirci, "A survey on sensor networks", IEEE Communications Magazine, Vol. 40, No. 8, pp. 102-114, 2002.
  2. GómezMármol F, Martínez Pérez G ,"Security threats scenarios in trust and reputation models for distributed systems" ,Elsevier Computers & Security,28(7),545–556,2009.
  3. Marsh, S. P. , "Formalising trust as a computational concept", Ph. D. thesis, Department of Computing Science and Mathematics, University of Stirling,1994.
  4. Marti, S. , & Garcia-Molina, H. ,"Taxonomy of trust: categorizing P2P reputation systems", Computer Networks, 50(4), 472–484,2006.
  5. Tajeddine A, Kayssi A, Chehab A, Artail H," PATROL-F- a comprehensive reputation-based trust model with fuzzy subsystems", Third international conference, ATC,LNCS, Wuhan, China: Springer, vol. 4158, p. 205–17, 2006.
  6. Wang Y, Cahill V, Gray E, Harris C, Liao L ,"Bayesian network based trust management", Third international conference, ATC, LNCS, Wuhan, China: Springer, Vol. 4158, p. 246–57, 2006.
  7. Gómez Mármol F, Martínez Pérez G ," Providing trust in wireless sensor networks using a bio inspired technique", Telecommunication Systems Journal, 46(2),163–180,2011.
  8. Almena´ rez F, Mar?´n A, Campo C, Garc?´a C , "PTM: a pervasive trust management model for dynamic open environments", First workshop on pervasive security and trust, Boston , USA, Aug 2004.
  9. Moloney M, Weber S, "A context-aware trust-based security system for ad hoc networks", In Workshop of the 1st international conference on security and privacy for emerging areas in communication networks, p. 153–60 ,Athens, Greece, Sep 2005.
  10. Boukerche A, Xu L , El-Khatib K ,"Trust-based security for wireless ad hoc and sensor networks", Computer Communications,30(11–12),2413–27,2007.
  11. Sabater J, Sierra C , "REGRET: reputation in gregarious societies", Proceedings of the fifth international conference on autonomous agents ,ACM Press, p. 194–5, Montreal, Can¬ada, 2001.
  12. GómezMármol F, Gómez Marín-Blázquez J , Martínez Pérez G ,"Linguistic fuzzy logic en¬hancement of a trust mechanism for distributed networks", Proceedings of the Third IEEE International Symposium on Trust, Security and Privacy for Emerging Applications (TSP-10), 838–845, DOI: 10. 1109/CIT. 2010. 158, Bradford, UK, 2011.
  13. Dorigo, M. , & Gambardella, L. , "Ant colony system: a cooperative learning approach in the traveling salesman problem", IEEE Transaction on Evolutionary Computing, 1(1), 53 66,1997.
  14. Pedrycz W, Gomide F," An Introduction to Fuzzy Sets: Analysis and Design", the MI Press: Cambridge, Masssachusetts, USA, 1998.
  15. Jang JSR, Sun CT, Mizutani E, "Neuro-Fuzzy and Soft Computing", Prentice Hall: Upper Sad¬dle River, New Jersey, USA, 1997.
  16. Gómez Mármol F, Martínez Pérez G , "TRMSim-WSN, Trust and Reputation Models Simula¬tor for Wireless Sensor Networks", Proceedings of the IEEE International Conference on Communications (IEEE ICC 2009), Communication and Information Systems Security Symposium, DOI:10. 1109/ICC. 5199545, Dresden, Germany, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Dynamic Fuzzy Bio-inspired Sensor networks