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An energy-efficient cuckoo search algorithm for virtual machine placement in cloud computing data centers

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Abstract

The advent of virtualization technology has created a huge potential application for cloud computing. In virtualization, a large hardware resource is often broken down into smaller virtual units. These small units are then provisioned to different clients. However, these services need to be provided in such a way that resources are properly utilized. To achieve this, many of the scheduling, allocation, and provisioning issues of data centers are formulated as optimization problems. The virtual machine placement problem (VMPP) is a typical provisioning problem of data centers. In VMPP, several virtual machine requests are to be hosted on physical machines such that a minimum number of physical machines are used. This work proposes a cuckoo search (CS) inspired algorithm for solving the VMPP. To improve the algorithm’s performance, new cost and perturbation functions are developed. The proposed method was tested on two well-known benchmark datasets. It outperformed the reordered grou** genetic algorithm, best-fit decreasing, first-fit decreasing, and an earlier CS method called multiCSA.

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References

  1. Varghese B, Buyya R (2018) Next generation cloud computing: new trends and research directions. Future Gener Comput Syst 79:849–861

    Article  Google Scholar 

  2. Etro F (2015) The economics of cloud computing. In: IRMA (ed) Cloud technology: concepts, methodologies, tools, and applications, IGI global, Hershey. https://doi.org/10.4018/978-1-4666-6539-2.ch101

  3. Rittinghouse John W, Ransome James F (2016) Cloud computing: implementation, management, and security. CRC Press, Florida

    Google Scholar 

  4. Martello S, Pisinger D, Vigo D (2000) The three-dimensional bin packing problem. Oper Res 48(2):256–267

    Article  MathSciNet  Google Scholar 

  5. Falkenauer E (1996) A hybrid grou** genetic algorithm for bin packing. J Heuristics 2(1):5–30

    Article  Google Scholar 

  6. Yang X-S, Deb S (2009) Cuckoo search via Lévy flights. In: 2009 world congress on nature & biologically inspired computing (NaBIC), Coimbatore. https://doi.org/10.1109/NABIC.2009.5393690

  7. Walton S, Hassan O, Morgan K, Brown MR (2011) Modified cuckoo search: a new gradient free optimisation algorithm. Chaos, Solitons Fractals 44(9):710–718

    Article  Google Scholar 

  8. Cid-Garcia Nestor M, Rios-Solis Yasmin A (2020) Positions and covering: a two-stage methodology to obtain optimal solutions for the 2d-bin packing problem. Plos One 15(4):e0229358

    Article  Google Scholar 

  9. Ross N, Keedwell E, Savic D (2020) Human-derived heuristic enhancement of an evolutionary algorithm for the 2d bin-packing problem. In: International Conference on Parallel Problem Solving from Nature, Springer. 413–427

  10. Dell’Amico M, Furini F, Iori M (2020) A branch-and-price algorithm for the temporal bin packing problem. Comput Oper Res 114:104825104825104825

    Article  MathSciNet  Google Scholar 

  11. Yao Y, Lai C, Cui Y (2017) A constructive heuristic for the two-dimensional bin packing based on value correction. Int J Comput Appl Technol 55(1):12–21

    Article  Google Scholar 

  12. Bennell JA, Cabo M, Martinez-Sykora A (2018) A beam search approach to solve the convex irregular bin packing problem with guillotine cuts. Eur J Oper Res 270(1):89–102

    Article  Google Scholar 

  13. Sato AK, Martins TC, Tsuzuki MSG (2018) Obstruction map local search solution for 2d irregular bin packing problem with cache acceleration. In: 2018 13th IEEE International Conference on Industry Applications (INDUSCON), IEEE. 837–843

  14. Mustafa S, Bilal K, Madani SA, Tziritas N, Khan SU, Yang LT (2015) Performance evaluation of energy-aware best fit decreasing algorithms for cloud environments. In: 2015 IEEE International Conference on Data Science and Data Intensive Systems, IEEE. 464–469

  15. Adamuthe Amol C, Pandharpatte Rupali M, Thampi Gopakumaran T (2013) Multiobjective virtual machine placement in cloud environment. In: 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies, IEEE. 8–13

  16. Xu J, Fortes Jose AB (2010) Multi-objective virtual machine placement in virtualized data center environments. In: 2010 IEEE/ACM Int’l Conference on Green Computing and Communications & Int’l Conference on Cyber, Physical and Social Computing, IEEE. 179–188

  17. Perumal B, Murugaiyan A (2016) A firefly colony and its fuzzy approach for server consolidation and virtual machine placement in cloud datacenters. Adv Fuzzy Syst 2016:5

    MathSciNet  Google Scholar 

  18. Wu Y, Tang M, Fraser W (2012) A simulated annealing algorithm for energy efficient virtual machine placement. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE. 1245–1250

  19. Gao Y, Guan H, Qi, Hou Y, Liu L (2013) A multi-objective ant colony system algorithm for virtual machine placement in cloud computing. J Comput Syst Sci 79(8):1230–1242

    Article  MathSciNet  Google Scholar 

  20. Wang S, Liu Z, Zheng Z, Sun Q, Yang F (2013) Particle swarm optimization for energy-aware virtual machine placement optimization in virtualized data centers. In: 2013 International Conference on Parallel and Distributed Systems, IEEE. 102–109

  21. Alboaneen DA, Tianfield H, Zhang Y (2016) Glowworm swarm optimisation algorithm for virtual machine placement in cloud computing. In: 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), IEEE. 808–814

  22. Patel P, Ranabahu AH, Sheth AP (2009) Service level agreement in cloud computing. https://corescholar.libraries.wright.edu/knoesis/78. Accessed 18 Jan 2021

  23. Abdel-Basset M, Abdle-Fatah L, Sangaiah AK (2018) An improved Lévy based whale optimization algorithm for bandwidth-efficient virtual machine placement in cloud computing environment. Clust Comput 22(4):8319–8334

    Google Scholar 

  24. Li Z, Li Y, Yuan T, Chen S, Jiang S (2019) Chemical reaction optimization for virtual machine placement in cloud computing. Appl Intell 49(1):220–232

    Article  Google Scholar 

  25. Sait SM, Bala A, El-Maleh AH (2016) Cuckoo search based resource optimization of datacenters. Appl Intell 44(3):489–506

    Article  Google Scholar 

  26. Liu X-F, Zhan ZH, Deng JD, Li Y, Gu T, Zhang J (2016) An energy efficient ant colony system for virtual machine placement in cloud computing. IEEE Trans Evolt Comput 22(1):113–128

    Article  Google Scholar 

  27. Ajiro Y, Tanaka A (2007) Improving packing algorithms for server consolidation. Int CMG Conf 253:399–406

    Google Scholar 

  28. Sgall J (2012) A new analysis of best fit bin packing. In: International Conference on Fun with Algorithms, Springer. 315–321

  29. Wilcox D, McNabb A, Seppi K (2011) Solving virtual machine packing with a reordering grou** genetic algorithm. In: 2011 IEEE Congress of Evolutionary Computation (CEC), IEEE 362–369

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Acknowledgements

We acknowledge all support from King Fahd University of Petroleum & Minerals (KFUPM), Saudi Arabia, University of Hafr al Batin, Saudi Arabia, and Universiti Teknologi PETRONAS (UTP), Malaysia. The authors are also grateful to Prof. Kevin Seppi of Brigham Young University, USA, for providing the VMPP instances in Dataset A.

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Authors and Affiliations

  1. College of Computer Science and Engineering, University of Hafr al Batin, Hafr al Batin, 31991, Saudi Arabia

    Hamza Onoruoiza Salami

  2. Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, Malaysia, 32610, Bandar Seri Iskandar, Perak, Malaysia

    Abubakar Bala & Idris Ismail

  3. Electrical Engineering Department, Bayero University Kano, PMB 3011, Gwarzo Road, Kano, Nigeria

    Abubakar Bala

  4. Computer Engineering Department and Center for Communications and IT Research, Research Institute, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia

    Sadiq M. Sait

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  1. Hamza Onoruoiza Salami
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  2. Abubakar Bala
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Correspondence to Hamza Onoruoiza Salami.

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Salami, H.O., Bala, A., Sait, S.M. et al. An energy-efficient cuckoo search algorithm for virtual machine placement in cloud computing data centers. J Supercomput 77, 13330–13357 (2021). https://doi.org/10.1007/s11227-021-03807-3

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  • DOI: https://doi.org/10.1007/s11227-021-03807-3

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