Authors : Karishma M; Ashath Thauth S

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/bhnt3hnt

Scribd : https://tinyurl.com/5n79d5np

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY1945

Abstract : The Mobile Adhoc Networks (MANETs) are infrastructure-less and self-organised network made up of mobile nodes. Congestion control is a challenging task in MANET because of its node mobility of node, huge data transfer traffic, and actively changing nature of the network. Heavy congestion may result in huge packet loss, more delays, and expenditure of network resources due to repeated transmissions. In this work, we propose an intra-network data rate adaptation scheme to avoid packet loss which analyses the length of the queues in forwarding nodes and number of source nodes to adapt data transfer rate for transfer of data packets. The proposed scheme allows MANET nodes to select the correct transmission rates based on the traffic demands and supports dynamic transmission rate adjustments between neighbouring nodes. This paper also examines dropping attacks by malicious nodes in the network layer and to protect against such attacks, a mechanism for detection is introduced using the MANET’s node supportive participation. Since the transmission overheads are only used in the exchange of transmission signals among the neighboring nodes, the proposed model may be used by MANETs even with a large number of nodes. Simulation results of this scalable model, shows noteworthy improvement in PDR and network delay and packet loss due to queue overflow and network congestion.

Keywords : MANETs; Congestion Control; Deep Reinforced Learning (DRL); Date Rate Adaptation; Packet Drop Attack.

References :

1. Jothi Lakshmi .S and Karishma .M, “A Modified DSR Protocol Using Deep Reinforced Learning for MANETS”, IETE Journal of Research, June 2023, DOI: 10.1080/03772063.2023.2223168.
2. Kayarkar. Bhagyashree S and Deshmukh .V.S, “A survey of congestion control in proactive source routing protocol in mobile ad hoc net-works”, Compusoft, Vol.3, Iss.12, Dec-2014.
3. Z. Long, and Z. He, “Optimization and implementation of DSR route protocol based on ad hoc network”, International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, China, 2007, pp.1508–1511. DOI:10.1109/wicom.2007.380
4. Yaghmaee .Mohammah-H, Donald .Adjeroh, “Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks”, Computer Networks Vol. 53, Iss. 11, pp.1798–1811, July 2009.
5. Senthil Kumaran .T, Sankaranarayanan .V, ”Early congestion detection and adaptive routing in manet”, Egyptian Informatics Journal, Volume 12, Issue 3, pp.165–175, November 2011.
6. L. Ying, S. Shakkottai and A. Reddy, "On Combining Shortest-Path and Back-Pressure Routing Over Multihop Wireless Networks," IEEE INFOCOM 2009, Rio de Janeiro, Brazil, 2009, pp. 1674-1682, doi: 10.1109/INFCOM.2009.5062086.
7. S. Puri and S. R. Devene, "Congestion Avoidance and Load Balancing in AODV-Multipath Using Queue Length," 2009 Second International Conference on Emerging Trends in Engineering & Technology, Nagpur, India, 2009, pp. 1138-1142, doi: 10.1109/ICETET.2009.62.
8. J. Camp and E. Knightly, "Modulation Rate Adaptation in Urban and Vehicular Environments: Cross-Layer Implementation and Experimental Evaluation," IEEE/ACM Transactions on Networking, vol. 18, no. 6, pp. 1949-1962, Dec. 2010, doi: 10.1109/TNET.2010.2051454.
9. Manikandan .K, Durai .M.A.A.S, “Active queue management based congestion control protocol for wireless networks”, International Journal of Enterprise Network Management,  Volume 6, Issue 1, pp. 30–41, Jan. 2014, DOI:10.1504/IJENM.2014.063399.  
10. Y. Xi, B. -s. Kim, J. -b. Wei and Q. -y. Huang, "Adaptive Multirate Auto Rate Fallback Protocol for IEEE 802.11 WLANS," MILCOM 2006 - 2006 IEEE Military Communications conference, Washington, DC, USA, 2006, pp. 1-7, doi: 10.1109/MILCOM.2006.302449.
11. T. K. Mishra and S. Tripathi, "Explicit Throughput and Buffer Notification based congestion control: A cross layer approach," 2015 Eighth International Conference on Contemporary Computing (IC3), Noida, India, 2015, pp. 493-497, doi: 10.1109/IC3.2015.7346732.
12. A. Al-Saadi, R. Setchi, Y. Hicks and S. M. Allen, "Multi-rate medium access protocol based on reinforcement learning," 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), San Diego, CA, USA, 2014, pp. 2875-2880, doi: 10.1109/SMC.2014.6974366.
13. Sumendra Thakur, Mansi Gupta, “Mitigating congestion using data rate control for MANET”, International Journal of Current Engineering and Technology, Vol.4, pp 2887-2891, August 2014.
14. O. Kachirski and R. Guha, “Effective intrusion detection using multiple sensors in wireless ad hoc networks”, In Proceedings of the 36th Hawaii International Conference on System Sciences, pp. 57-61, 2003.
15. M.C. Man and V.K. Wei, “A taxonomy for attacks on mobile agents”, In Proceedings of the International Conference on Trends in Communications, Vol. 2, pp. 385-388, 2001.
16. Adnan Ahmed, Kamalrulnizam Abu Baker, Muhammad Ibrahim Channa, Khalid Haseeb, Abdul Waheed Khan, “A survey on trust based detection and isolation of malicious nodes in ad-hoc and sensor networks”, Frontiers of Computer Science, Volume 9, Issue 2, pp. 280–296 April 2014.
17. S. Sen, J.A. Clark, “Intrusion Detection in Mobile Ad Hoc Networks”, in Guide to Wireless Ad Hoc Networks. Computer Communications and Networks, S. Misra, I. Woungang, S. Chandra Misra, Eds. London: Springer, 2009, pp. 427–454.
18. Abderrahmane Baadache, Ali Belmehdi, “Fighting against packet dropping misbe-havior in multi-hop wireless ad hoc networks”, Journal of Network and Computer Applications, Volume 35, Issue 3, 2012, Pages 1130-1139, ISSN 1084-8045, https://doi.org/10.1016/j.jnca.2011.12.012.
19. M. Mohanapriya, I. Krishnamurthi, “Modified DSR protocol for detection and removal of selective black hole attack in MANET”, Computers & Electrical Engineering, Volume 40, Issue 2, 2014, Pages 530-538, ISSN 0045-7906, https://doi.org/10.1016/j.compeleceng.2013.06.001.
20. J. Zhang, C. Chen, Y. Xiang, W. Zhou and Y. Xiang, "Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions," in IEEE Transactions on Information Forensics and Security, vol. 8, no. 1, pp. 5-15, Jan. 2013, doi: 10.1109/TIFS.2012.2223675.
21. Tal Anker, D. Dolev and B. Hod, "Cooperative and Reliable Packet-Forwarding on Top of AODV," 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, Boston, MA, USA, 2006, pp. 1-10, doi: 10.1109/WIOPT.2006.1666450.
22. E. Sivajothi, N. Vijayalakshmi, A. Swaminathan, P. Vivekanandan, “An Overview of Route Discovery Mechanisms of Multicast Routing Protocols for MANETs”, International Journal of Engineering and Technology (IJET), Volume 5 No 5, pp. 3958–3966, Oct-Nov 2013.
23. Mahsa Seyyedtaj, Mohammad Ali Jabraeil Jamal, “Security improvements Zone Rout-ing Protocol in Mobile Ad Hoc Network”, International Journal of Computer Applications Technology and Research, . Volume 3 (9), pp. 536–540, September 2014.
24. Yatin Chauhan, Jaikaran Singh, Mukesh Tiwari, Anubhuti Khare, “Performance Eval-uation of AODV based on black hole attack in ad hoc network”, Global Journal of researches in engineering Electrical and electronics engineering, Volume 12, Issue 2, Version 1.0, February 2012.
25. P. Michiardi, R. Molva, “Preventing Denial of Service and Selfishness in Adhoc Net-works”, in: Proceedings of Working Session on Security in Ad Hoc Networks, 2005, pp. 223–245.
26. S. Bansal, M. Baker, “Observation-based Cooperation Enforcement in Ad hoc Net-works”, in: Proceedings of ACM/IEEE International Conference on Mobile Computing and Networking, 2004, pp. 325–355.
27. Khan, A.N., Tariq, M.A., Asim, M., Maamar, Z. and Baker, T., “Congestion avoidance in wireless sensor network using software defined network”, Computing, Volume 103(1), pp.2573-2596, November 2021, DOI:10.100/s00607-021-01010-z.
28. Priya sharma, Kiranbir kaur, "Hybrid Artificial Bee Colony and Tabu Search Based Power Aware Scheduling for Cloud Computing", International Journal of Intelligent Systems and Applications(IJISA), Volume 10, No.7, pp.39-47, 2018. DOI: 10.5815/ijisa.2018.07.04.