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Congestion Avoidance Using Enhanced Blue Algorithm

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Abstract

This paper addresses congestion avoidance using enhanced blue algorithm (EBA) for data transferring in a network. The congestion of data always affects the data transmission on the internet for various applications. For developing data transmission performance, the congestion of data is a challenging task. Although, different approaches have been used to avoid data congestion, yet we have considered a data transmission framework for better performance compare to existing approaches. Thus, we considered the advanced Blue Algorithm which is used to determine the node's capacity with middle path and it prevents congestion by monitoring of data during data transmission. The role of gateway is considered to supervise status of congestion for both data sending and receiving based on positive or negative acknowledgment as well as data size. The gateway is also used for a congestion notification system to alleviate congestion and enhance throughput. During experimental analysis, we have taken comparative performance between existing and our proposed model. For example, in Enhanced Ad hoc On-demand Distance Vector (EAODV), during the packet size of 10, the average end-to-end delay is 32.63 ms whereas in proposed advanced Blue algorithm, the average delay is only 19.11 ms. Thus, the proposed model using Blue algorithm is performed better than existing method.

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References

  1. Ahmed, A., & Nasrelden, N (2018). New congestion control algorithm to improve computer networks performance, 2018 International Conference on Innovative Trends in Computer Engineering (ITCE), IEEE Explore, pp. 1–6.

  2. Lu, Y., Fan, X., & Qian, L., (2017). Dynamic ECN marking threshold algorithm for TCP congestion control in data centre networks. The International Journal for the Computer and Telecommunications Industry, pp. 197–208.

  3. Wang, W., Wang, X., & Wang, D. (2017). Energy efficient congestion control for multipath TCP in heterogeneous networks. IEEE Transaction On Cyber-Threats And Countermeasures In The Healthcare Sector, 6, 2889–2897.

    Google Scholar 

  4. Atilla, E., & Srikant, R, (2004). Fair resource allocation in wireless networks using queue-length-based scheduling and congestion control. Proceedings of Infocom, pp.1–26.

  5. Srinivasa Rao, K., Sudhistna Kumar, R., Venkatesh, P., Sivaram Naidu, R. V., & Ramesh. (2012). A, ‘development of energy efficient and reliable congestion control protocol for multicasting in mobile adhoc networks compare with AODV based on receivers.’ International Journal of Engineering Research and Applications (IJERA), 2(2), 631–634.

    Google Scholar 

  6. Gaurav Sharma, D.E., Shaw, L.P., Changhee, J., Ness, B. Shroff & Ravi, R. Mazumdar, (2010). Joint congestion control and distributed scheduling for throughput guarantees in wireless networks. ACM Journal, pp. 1–25.

  7. Bansal, G., Kenney, J. B., & Rohrs, C. E. (2013). LIMERIC: a linear adaptive message rate algorithm for DSRC congestion control. IEEE Transactions on Vehicular Technology, 62(9), 4182–4197.

    Article  Google Scholar 

  8. Xiao, K., Mao, S., & Tugnait, J. K. (2017). MAQ: a multiple model predictive congestion control scheme for cognitive radio networks. IEEE Transactions On Wireless Communications, 16(4), 2614–2626.

    Article  Google Scholar 

  9. Sharma, V. K., & Bhadauria, D. S. S. (2012). Mobile agentbased congestion control using Aodv routing protocol technique for mobile Ad-Hoc network’. International Journal of Wireless & Mobile Networks (IJWMN), 4(2), 229–314.

    Google Scholar 

  10. Verma, P., Singh, N., & Sharma, M. (2018) ‘Modeling and performance analysis of VI-CRA: A congestion control algorithm for vehicular networks. International Journal of Communication Systems. pp. 1–16.

  11. Habachi, O., Yusuo, Hu., van der Schaar, M., Hayel, Y., & Feng, Wu. (2012). MOS-based congestion control for conversational services in wireless environments. IEEE Journal On Selected Areas In Communications, 30(7), 1225–1236.

    Article  Google Scholar 

  12. Zhao, Y., Fang, X., Huang, R., & Fang, Y. (2014) Joint Interference Coordination and Load Balancing for OFDMA Multihop Cellular Networks. IEEE Transactions on Mobile Computing, Vol. 13, No. 1.

  13. Segara, A. P., Ijtihadie, R. M., Ahmad, T., & Maniriho, P. (2021) Route Discovery to Avoid Congestion in Software Defined Networks. 6th International Conference on Science in Information Technology-(ICSITech), https://doi.org/10.1109/ICSITech 49800.2020.9392049

  14. Hernandez, L., Jimenez, G., Pranolo, A., Rios, CU (2020). Comparative performance analysis between software-defined networks and conventional IP Networks", 2020 5th International Conference on Science in Information Technology(ICSITech), pp. 235–240. DOI: https://doi.org/10.1109/ICSITech 46713.2019.8987508.

  15. Rene, S., Ascigil, O., Psaras, I., & Pavlou, G. (2022). A congestion control framework based on in-network resource pooling. IEEE/ACM Transactions on Networking, 30(2), 683–697.

    Article  Google Scholar 

  16. Vári, B. K., Pelenczei, B., Aradi, S., & Bécsi, T. (2022). Reward design for intelligent intersection control to reduce emission. IEEE Access, 10, 39691–39699.

    Article  Google Scholar 

  17. Pham, Q. V., & Hwang, W. J. (2017). Network utility maximizationbased congestion control over wireless networks: A survey and potential directives’. IEEE Communications Surveys & Tutorials, Second Quarter, 19(2), 1173–1200.

    Article  Google Scholar 

  18. Yufang, X., & Edmund M, Y. (2007). Node-based optimal power control, routing, and congestion control in wireless networks’, Army Research Office (ARO) Young Investigator Program (YIP) grant DAAD19–03- 1–0229 and by National Science Foundation (NSF) grant CCR-0313183, pp. 1–51.

  19. Bhuyan, H. K., Kamila, N. K., & Dash, S. K. (2011). An approach for privacy preservation of distributed data in peer-to-peer network using multiparty computation. International Journal Computer Science and Issues (IJCSI), 3, 424–429.

    Google Scholar 

  20. Bhuyan, H. K., Mohanty, M., & Das, S. R. (2012). Privacy preserving for feature selection in data mining using centralized network. International Journal Computer Science and Issues (IJCSI), 9, 434–440.

    Google Scholar 

  21. Yuzhou, L., Yan, S., Min, S., Guoqing, L., & Chao, X. (2015). ‘Optimal rate allocation based on cross-layer design and end-to-end congestion control in WCDMA Networks. Communications System Design, pp. 58–68.

  22. Shi, K., Shu, Y., Yang, O., & Luo, J. (2010). Receiver-assisted congestion control to achieve high throughput in lossy wireless networks. iEEE Transactions on Nuclear Science, 57(2), 491–496.

    Article  Google Scholar 

  23. Vijayaraj, A., Suresh, R. M., & Poonkuzhali, S. (2018). Load balancing in wireless networks using reputation-ReDS in the magnified distributed hash table. Springer Multimedia Tools and Applications, 77, 10347–10364.

    Article  Google Scholar 

  24. Yunliang, L., Laixian, P., Renhui, X., Aijing, Li, Lin, G. (2021). Neighbor discovery algorithm with collision avoidance in Ad Hoc Network using Directional Antenna. IEEE 6th International Conference on Computer and Communications (ICCC) 2021. Pp. 458–462. DOI: https://doi.org/10.1109/ICCC51575.2020.9344952.

  25. Ahmed, O., Ren, F., Hawbani, A., & Al-Sharabi, Y. (2020). Energy optimized congestion control-based temperature aware routing algorithm for software defined wireless body area networks. IEEE Access, 8, 41085–41099. https://doi.org/10.1109/ACCESS.2020.2976819

    Article  Google Scholar 

  26. Fan, Q., & Yuan, X. (2014). ‘Robust joint congestion control and scheduling for time-varying multi-hop wireless networks with feedback delay. IEEE Transaction on Wireless Communications, 13, 5211–5222.

    Article  Google Scholar 

  27. Bhuyan, H. K., Dash, S. K., Roy, S., & Swain, D. K. (2012). Privacy Preservation with Penalty in Decentralized Network using Multiparty Computation. International Journal of Advancements in Computing Technology (IJACT), 4, 297–303.

    Article  Google Scholar 

  28. Bhuyan, H. K., Pani, S. K., (2021). Cloud resource management for network cameras, book: applications of machine learning in big-data analytics and cloud computing, Chapter 10, River Publishers, pp: 207–229.

  29. Rostami, A., Cheng, B., Bansal, G., Sjoberg, K., Gruteser, M., & Kenney, J. B. (2016). Stability challenges and enhancements for vehicular channel congestion control approaches. IEEE Transactions On Intelligent Transportation Systems, 17(10), 2935–2948.

    Article  Google Scholar 

  30. Silva, A. P., Burleigh, S., Hirata, C. M. & Obraczka, K. (2014). A survey on congestion control for delay and disruption tolerant networks. Elsevier Ad Hoc Networks, Special Issue on New Research Challenges in Mobile, Opportunistic and Delay-Tolerant Networks, pp. 1–17.

  31. Casetti, C., Gerla, M., Mascolo, S., Sanadidi, M.Y. & Wang, R. (2002). TCP westwood: end-to-end congestion control for wired/wireless networks. Kluwer Academic Publishers. Manufactured in the Netherlands pp. 467–479.

  32. Vijayaraj, A., Indhuja, S. (2017) Detection of malicious nodes to avoid data loss in wireless networks using elastic routing table, IEEE 3rd International Conference on Sensing, Signal Processing and Security (ICSSS), pp. 490–496.

  33. Wang, C.-C. & Harfoush, K. (2008) Shortest-path routing in randomized DHT-based Peer-to-Peer systems. Elsevier, Computer Networks, pp. 3307–3317.

  34. Radenkovic, M., & Grundy, A. (2012). Efficient and adaptive congestion control for heterogeneous delay-tolerant networks. Elsevier -Ad Hoc Networks, 10, 1322–1345.

    Article  Google Scholar 

  35. Vijayaraj, A., Suresh, R. M., & Poonkuzhali, S. (2019). Node discovery with development of routing tree in wireless networks. Cluster Computing, Springer, 22, 10861–10871.

    Article  Google Scholar 

  36. Liu, J., Huang, J., Jiang, W., Li, Z., Li, Y., Lyu, W., Jiang, W., Zhang, J., & Wang, J. (2022). End-to-end congestion control to provide deterministic latency over internet. IEEE Communications Letters, 26(4), 843–847.

    Article  Google Scholar 

  37. Kadhum, M. M., & Manickam, S. (2015). Dynamic queue velocity-based probability function for congestion avoidance in highspeed networks. IEEE International Broadband and Photonics Conference, Bali, 23–25, 92–96.

    Google Scholar 

  38. Chakraborty, C., Mishra, K., Majhi, S. K., Bhuyan, H. K. (2022). Intelligent latency-aware tasks prioritization and offloading strategy in Distributed Fog-Cloud of Things. IEEE Transactions on Industrial Informatics, pp. 1–8

  39. Zhang, T., Dai, W., Guiling, Wu., Li, X., Chen, J., & Qiao, C. (2014). A dual price-based congestion control mechanism for optical burst switching networks. IEEE Transaction on Lightwave Technology, 32(14), 2492–2501.

    Article  Google Scholar 

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Vijayaraj, A., Bhuyan, H.K., Vasanth Raj, P.T. et al. Congestion Avoidance Using Enhanced Blue Algorithm. Wireless Pers Commun 128, 1963–1984 (2023). https://doi.org/10.1007/s11277-022-10028-1

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