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Distributed bandwidth selection approach for cooperative peer to peer multi-cloud platform

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Abstract

Network function virtualization (NFV) is a well-accepted software-defined network (SDN) architecture concept. NFV is severally used in cloud platform to enhance the utilization of available network resources. The concept behind NFV is a design of software process architecture with a bunch of collaborative resource utilization functions. The progression of platform providers builds a communication service plan with the help of virtual machines. We propose biogeography-based optimization (BBO) technique in order to enrich virtual network functions (VNFs) to utilize available bandwidth resource in an energy-efficient and cost-effective manner. The cooperative bandwidth sharing approach using BBO reduces delay mean at the time of supervision the impending requests in a multi-cloud environment. Experimental results validate that the utilization of available bandwidth has increased using the proposed scheme with respect to the single user-dedicated resource allocation and multi-user dedicated resource allocation. Delay means, as well as subscription cost, has reduced compared to the existing methods. The correctness of the investigational outcome has been established using an experimental setup along with the proposed algorithm.

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References

  1. Misra S, Das S, Khatua M, Obaidat MS (2014) QoS-guaranteed bandwidth shifting and redistribution in mobile cloud environment. IEEE Trans. Cloud Comput. 2(2):181–193

    Article  Google Scholar 

  2. D.G. Roy, D. De, M. M. Alam, and S. Chattopadhyay Multi-cloud scenario based QoS enhancing virtual resource brokering. International conference on recent advances in information technology, IEEE, 2016

  3. Wang J, Liu A, Yan T, Zeng Z (2018) A resource allocation model based on double-sided combinational auctions for transparent computing. Peer-to-Peer Netw Appl 11(4):679–696

    Article  Google Scholar 

  4. Chen J, Ota K, Wang L, He J (2019) Big data and smart computing in network systems. Peer-to-Peer Netw Appl 12(5):1308–1310

    Article  Google Scholar 

  5. Ma Z, Zhao Q, Huang J (2017) Optimizing bandwidth allocation for heterogeneous traffic in IoT. Peer-to-Peer Netw Appl 10(3):610–621

    Article  Google Scholar 

  6. Liu J, Wang S, Zhou A, Yang F, Buyya R (2017) Availability-aware virtual cluster allocation in bandwidth-constrained datacenters. IEEE Transactions on Services Computing (3):425–436. https://doi.org/10.1109/TSC.2017.2694838

  7. Zhang P, Yao H, Li M, Liu Y (2019) Virtual network embedding based on modified genetic algorithm. Peer-to-Peer Netw Appl 12(2):481–492

    Article  Google Scholar 

  8. Cao J, Ma Z, Xie J, Zhu X, Dong F, Liu B (2020) Towards tenant demand-aware bandwidth allocation strategy in cloud datacenter. Future Generation Computer Systems 105:904–915

  9. Wang Y, Cen H, Wang S (2018) Resource allocation of wireless backhaul in heterogeneous network based on the large-scale MIMO. Future Generation Computer Systems 88:117–126

  10. Zhang F, Ge J, Li Z, Li C, Wong C, Kong L, Chang V (2018) A load-aware resource allocation and task scheduling for the emerging cloudlet system. Futur Gener Comput Syst 87:438–456

    Article  Google Scholar 

  11. Tayyaba SK, Shah MA (2019) Resource allocation in SDN based 5G cellular networks. Peer-to-Peer Netw Appl 12(2):514–538

    Article  Google Scholar 

  12. Simon D (2008) Biogeography-based optimization. IEEE Trans Evol Comput 12(6):702–713

    Article  Google Scholar 

  13. Goodarzi AH, Zegordi SH (2016) A location-routing problem for cross-docking networks: a biogeography-based optimization algorithm. Comput Ind Eng 102:132–146

    Article  Google Scholar 

  14. Ahmed E, Gharavi H (2018) Cooperative vehicular networking: a survey. IEEE Trans Intell Transp Syst 19(3):996–1014

    Article  Google Scholar 

  15. Huang D, Zhang M, Zheng Y, Chen C, Huang Y (2015) Pre-allocation based flash crowd mitigation algorithm for large-scale content delivery system. Peer-to-Peer Netw Appl 8(3):493–500

    Article  Google Scholar 

  16. Roy DG, Mahato B, De D, Buyya R (2018) Application-aware end-to-end delay and message loss estimation in internet of things (IoT) – MQTT-SN protocols. Futur Gener Comput Syst 89:300–316

    Article  Google Scholar 

  17. Liu J, Ahmad S, Buyukkaya E, Hamzaoui R, Simon G (2015) Resource allocation in underprovisioned multioverlay peer-to-peer live video sharing services. Peer-to-peer Netw Appl 8(3):399–413

    Article  Google Scholar 

  18. Santos IL, Pirmez L, Delicato FC, Oliveira GM, Farias CM, Khan SU, Zomaya AY (2019) Zeus: a resource allocation algorithm for the cloud of sensors. Futur Gener Comput Syst 92:564–581

    Article  Google Scholar 

  19. Zhang H, Jiang H, Li B, Liu F, Vasilakos AV, Liu J (2016) A framework for truthful online auctions in cloud computing with heterogeneous user demands. IEEE Trans Comput 65(3):805–818

    Article  MathSciNet  Google Scholar 

  20. Wang W, Shi H, Wu D, Huang P, Gao B, Wu F, Xu D, Chen X (2017) VD-PSO: an efficient mobile sink routing algorithm in wireless sensor networks. Peer-to-Peer Netw Appl 10(3):537–546

    Article  Google Scholar 

  21. Roy DG, Das M, De D (2018) Cohort Assembly: A Load Balancing Grouping Approach for Traditional Wi-Fi Infrastructure Using Edge Cloud. In: Mandal J., Mukhopadhyay S., Dutta P., Dasgupta K. (eds) Methodologies and Application Issues of Contemporary Computing Framework. Springer, Singapore

  22. Harb, Hassan, Chady Abou Jaoude, and Abdallah Makhoul (2019) An energy-efficient data prediction and processing approach for the internet of things and sensing based applications. Peer-to-Peer Netw Appl 1–16

  23. Roy, D. G., Mahato, B., Ghosh, A., & De, D. (2019) Service aware resource management into cloudlets for data offloading towards IoT. Microsyst Technol, 1–15

  24. Gavvala SK, Jatoth C, Gangadharan GR, Buyya R (2019) QoS-aware cloud service composition using eagle strategy. Futur Gener Comput Syst 90:273–290

    Article  Google Scholar 

  25. Díaz JL, Entrialgo J, García M, García J, García DF (2017) Optimal allocation of virtual machines in multi-cloud environments with reserved and on-demand pricing. Futur Gener Comput Syst 71:129–144

    Article  Google Scholar 

  26. Feng G, Lv H, Li B, Wang C, Lv H, Wang H (2019) A near-optimal cloud offloading under multi-user multi-radio environments. Peer-to-Peer Netw Appl 12(5):1454–1465

    Article  Google Scholar 

  27. Wang G, Liu T (2018) Resource allocation for M2M-enabled cellular network using Nash bargaining game theory. Peer-to-Peer Netw Appl 11(1):110–123

    Article  Google Scholar 

  28. Li, R., Zheng, Q., Li, X., and Yan, Z. (2017) Multi-objective optimization for rebalancing virtual machine placement. Futur Gener Comput Syst

  29. Zhao, Weiguo, Liying Wang, and Zhenxing Zhang (2018) A novel atom search optimization for dispersion coefficient estimation in groundwater. Futur Gener Comput Syst

  30. Demir K, Germanus D, Suri N (2017) Robust QoS-aware communication in the smart distribution grid. Peer-to-Peer Netw Appl 10(1):193–207

    Article  Google Scholar 

  31. Darwish A (2018) Bio-inspired computing: algorithms review, deep analysis, and the scope of applications. Futur Comput Inform J 3(2):231–246

    Article  Google Scholar 

  32. Rarick R, Simon D, Villaseca FE, Vyakaranam B (2009) Biogeography-based optimization and the solution of the power flow problem. In 2009 IEEE International Conference on Systems, Man and Cybernetics, pp. 1003-1008. IEEE, 2009.

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Correspondence to Debashis De.

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Mahato, B., Guha Roy, D. & De, D. Distributed bandwidth selection approach for cooperative peer to peer multi-cloud platform. Peer-to-Peer Netw. Appl. 14, 177–201 (2021). https://doi.org/10.1007/s12083-020-00917-2

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