Probabilistic Approach of Ant Colony Inspired Adaptive Routing Algorithm for Cognitive Wireless Sensor Networks
Probabilistic Approach of Ant Colony Inspired Adaptive Routing Algorithm for Cognitive Wireless Sensor Networks |
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| © 2024 by IJETT Journal | ||
| Volume-72 Issue-3 |
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| Year of Publication : 2024 | ||
| Author : Amit N. Thakare, Latesh G. Bhagat (Malik) |
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| DOI : 10.14445/22315381/IJETT-V72I3P102 | ||
How to Cite?
Amit N. Thakare, Latesh G. Bhagat (Malik), "Probabilistic Approach of Ant Colony Inspired Adaptive Routing Algorithm for Cognitive Wireless Sensor Networks," International Journal of Engineering Trends and Technology, vol. 72, no. 3, pp. 10-25, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I3P102
Abstract
Wireless sensor networks are collections of sensor nodes deployed in an unattended fashion with sensing wireless computations and communication capabilities. The wireless sensor network with the cognitive capability produced the new terminology of Cognitive Radio Sensor Networks (CRSN). In CRSN, the unlicenced sensor nodes use their temporarily available vacant, licenced spectrum band and a number of channels as required for communication. The many open challenges are still under consideration in WSN. In this paper, challenges arising for adaptive routing as fault-tolerance issues are proposed for the adaptive routing algorithm with a probabilistic approach and the metaheuristic clustering approach. The CRSN with available spectrum channels with PU (Primary User) and SU (Secondary User) activity with spectrum sensing and spectrum hands-off functionalities based on availability are considered. Inspired by the foraging approach of ANTs (Ant Colony Optimization) for making probabilistic route selection the shortest path in a multi-hop fashion. The proposed routing algorithm solves routing issues by having the capability of the cognitive approach in the AODV and DSR routing protocols as the network layer protocol is compared. Performance parameters such as packet delivery fraction, average end-to-end delay, and average throughput are analysed to find an optimised solution for the telecommunications network.
Keywords
Ant Colony Optimization, CRSN, Markov model, Performance analysis, Wireless Sensor Network.
References
[1] Hang Su, and Xi Zhang, “Cross–Layer Based Opportunistic MAC Protocols for QoS Provisioning Over Cognitive Radio Wireless Networks,” IEEE Journal on Selecting Areas in Communications, vol. 26, no. 1, pp. 118-129, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[2] D.P. Mackinuon, Introduction to Statistical Mediation Analysis, 1st ed., Routledge, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[3] D.G. Reina, “The Role of Congestion in Probabilistic Broadcasting for Ubiquitous Wireless Multi-Hop Networks through Mediation Analysis,” Pervasive and Mobile Computing, vol. 24, pp. 16-29, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Gunter Bolch et al., Queueing Networks and Markov Chains: Modeling and Performance Evaluation with Computer Science Applications, John Wiley & Sons, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Vahid Esmaeelzadeh et al., “CogNS: A Simulation Framework for Cognitive Radio Networks,” Wireless Personal Communications, vol. 72, no. 4, pp. 2849-2865, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[6] M.D. Felice, and K.R. Chowdhury, “Search: A Routing Protocol for Mobile Cognitive Radio Ad-Hoc Networks,” Computer Communications, vol. 32, no. 18, pp. 1983-1997, 1997.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Zhongliang Liang et al., “Delay Performance Analysis for Supporting Real-Time Traffic in a Cognitive Radio Sensor Network,” IEEE Transactions on Wireless Communications, vol. 10, no. 1, pp. 325-335, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Ozgur B. Akan, Osman B. Karli, and Ozgur Ergul, “Cognitive Radio Sensor Network,” IEEE Network, vol. 23, no. 4, pp. 34-40, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Gyanendra Prasad Joshi, Seung Yeob Nam, and Sung Won Kim, “Cognitive Radio Wireless Sensor Networks: Applications, Challenges and Research Trends,” Sensors, vol. 13, no. 9, pp. 11196–11228, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Balakrishnan Chandrashekaran, “Survey of Network Traffic Models,” Thesis, Washington University in St. Louis CSE, 2009.
[Google Scholar] [Publisher Link]
[11] Le The Dung, Tran Dinh Hieu, and Seong-Gon Choi, “Simulation Modeling and Analysis of One Hop Count Distribution in Cognitive Radio Ad-Hoc Networks with Shadow Fading,” Simulation, Modeling Practice and Theory, vol. 69, pp. 43-54, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Ian F. Akyildiz et al., “NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey,” Computer Networks, vol. 50, no. 13, pp. 2127-2159, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Won-yeol Lee, and Ian. F. Akyildiz, “Optimal Spectrum Sensing Framework for Cognitive Radio Networks,” IEEE Transactions on Wireless Communications, vol. 7, no. 10, pp. 3845-3857, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[14] W.B. Heinzelman, A.P. Chandrakasan, and H. Balakrishnan, “An Application-Specific Protocol Architecture for Wireless Microsensor Networks,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 660-670, 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Siva D. Muruganthan et al., “A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks,” IEEE Communications Magazine, vol. 43, no. 3, pp. 8-13, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[16] D. Mahmood et al., “MODLEACH: A Variant of LEACH for WSNs,” 2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications, Compiegne, France, pp. 158-163, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Min Hla Yin, and Z. Win, “Fault Management Using Cluster-Based Protocol in Wireless Sensor Networks,” International Journal of Future Computer and Communication, vol. 3, no. 1, pp. 36-39, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Perumalsamy Deepalakshmi, and Shanmugasundaram Radhakrishnan, “An Ant Colony-Based Multi-Objective Quality of Service Routing For Mobile Ad-Hoc Networks,” EURASIP Journal on Wireless Communications and Networking, vol. 2011, no. 153, pp. 1-12, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Gianni Di Caro, Frederick Ducatelle, and Luca Maria Gambardella, “Anthocnet: An Adaptive Nature-Inspired Algorithm for Routing in Mobile Ad Hoc Networks,” European Transactions on Telecommunications, vol. 16, no. 5, pp. 443-455, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Hang Su, and Xi Zhang, “Cross-Layer-Based Opportunistic MAC Protocols for QoS Provisioning Over Cognitive Radio Wireless Networks,” IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 118-129, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[21] B. Krishnamachari, and S. Iyengar, “Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks,” IEEE Transactions on Computers, vol. 53, no. 3, pp. 241- 250, 2004. [CrossRef] [CrossRef] [Google Scholar] [Publisher Link]
[22] Z. Liang, and D. Zhao, “Quality of Service Performance of a Cognitive Radio Sensor Network,” International Conference on Communications (ICC), Cape Town, South Africa, pp. 1-5, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Wayne Yang, “Markov Chains and Ant Colony Optimization,” The University of Chicago Mathematics, pp. 1-27, 2013.
[Publisher Link]
[24] The Network Simulator - ns-2. [Online]. Available: http://www.isi.edu/nsnam/ns/
[25] Introduction to Probability, Statistics, and Random Processes. [Online]. Available: https://www.probabilitycourse.com
[26] J.F.C. Kingman, Poisson Process, Clarendon Press, 1993.
[Google Scholar] [Publisher Link]
[27] M. Darigo, “Optimization, Learning and Natural Algorithms,” Ph.D. Thesis, Politecnico di Milano, Italian, 1992.
[Google Scholar] [Publisher Link]
[28] Kashif Saleem et al., “Ant-Based Self-Organized Routing Protocol for Wireless Sensor Networks,” International Journal of Communication Networks and Information Security (IJCNIS), vol. 1, no. 2, 2009.
[Google Scholar] [Publisher Link]
[29] Michael Brand et al., “Ant Colony Optimization Algorithm for Robot Path Planning,” 2010 International Conference on Computer Design and Applications, Qinhuangdao, China, pp. 436-440, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Kwang Mong Sim, and Weng Hong Sun, “Ant Colony Optimization for Routing and Load Balancing: Survey and New Directions,” IEEE Transactions on Systems and Humans, vol. 33, no. 5, pp. 560-572, 2003.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Swagatam Das, Ajith Abraham, and Amit Konar, Metaheuristic Clustering. In: Studies in Computational Intelligence, Springer Berlin Heidelberg, pp. 1-252, 2009.
[Google Scholar] [Publisher Link]
[32] Hajara Idris et al., “An Improved Ant Colony Optimization Algorithm with Fault Tolerance for Job Scheduling in Grid Computing Systems,” PLoS ONE, vol. 12, no. 5, pp. 1-24, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Lary pass, Beginning R: An Introduction to Statistical Programming, Apress, pp. 1-336, 2012.
[Google Scholar] [Publisher Link]
[34] Falko Dessler, and Ozgur Akan, “A Survey of Bio-Inspired Networking,” Computer Networks, vol. 54, no. 6, pp. 881- 900, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[35] R. Latha, P. Vetrivelan, and M. Jagannath, “Balancing Emergency Message Dissemination and Network Lifetime in Wireless Body Area Network Using Ant Colony Optimization and Bayesian Game Formulation,” Information in Medicine Unlocked, vol. 8, pp. 60-65, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[36] Amit. N.Thakare, Latesh G. Bhagat(Malik), Achamma Thomas, “Analysis od adaptive bio-inspired routing protocol with multi-hops communication in WSN”, Mc-Graw Hill education publication, 2017.
[37] A. Ozan Bicen, and Ozgur B. Akan, “Reliability and Congestion Control in Cognitive Radio Sensor Networks,” Ad Hoc Networks, vol. 9, no. 7, pp. 1154-1164, 2011.
[CrossRef] [Google Scholar] [Publisher Link]