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Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

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Abstract

There are two actors in cloud computing environment cloud providers and cloud users. On one hand cloud providers hold enormous computing resources in the cloud large data centers that rent the resources out to the cloud users on a pay-per-use basis to maximize the profit by achieving high resource utilization. On the other hand cloud users who have applications with loads variation and lease the resources from the providers they run their applications within minimum expenses. One of the most critical issues of cloud computing is resource management in infrastructure as a service (IaaS). Resource management related problems include resource allocation, resource adaptation, resource brokering, resource discovery, resource mapping, resource modeling, resource provisioning and resource scheduling. In this review we investigated resource allocation schemes and algorithms used by different researchers and categorized these approaches according to the problems addressed schemes and the parameters used in evaluating different approaches. Based on different studies considered, it is observed that different schemes did not consider some important parameters and enhancement is required to improve the performance of the existing schemes. This review contributes to the existing body of research and will help the researchers to gain more insight into resource allocation techniques for IaaS in cloud computing in the future.

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References

  1. Jennings, B., Stadler, R.: Resource management in clouds: survey and research challenges. J. Netw. Syst. Manag. 23, 567–619 (2015)

    Article  Google Scholar 

  2. Whaiduzzaman, M., Haque, M.N., Chowdhury, M.R.K., Gani, A.: A study on strategic provisioning of cloud computing services. Sci. World J., 1–16 (2014)

  3. Abdulhamid, S.M., Abd Latiff, M.S., Abdul-Salaam, G., Madni, S.H.H.: Secure scientific applications scheduling technique for cloud computing environment using global league championship algorithm. PLoS ONE 11(7), e0158102 (2016)

    Article  Google Scholar 

  4. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7–18 (2010)

    Article  Google Scholar 

  5. Madni, S.H.H., Latiff, M.S.A., Coulibaly, Y., Abdulhamid, S.I.M.: An appraisal of meta-heuristic resource allocation techniques for IaaS Cloud. Indian J. Sci. Technol. 9(4), 1–14 (2016)

    Article  Google Scholar 

  6. Manvi, S.S., Shyam, G.K.: Resource management for Infrastructure as a Service (IaaS) in cloud computing: a survey. J. Netw. Comput. Appl. 41, 424–440 (2014)

    Article  Google Scholar 

  7. Chana, I., Singh, S.: Quality of service and service level agreements for cloud environments: issues and challenges. In: Mahmood, Z. (ed.) Cloud Computing, pp. 51–72. Springer, New York (2014)

    Google Scholar 

  8. Ma, T., Chu, Y., Zhao, L., Ankhbayar, O.: Resource allocation and scheduling in cloud computing: policy and algorithm. IETE Tech. Rev. 31(1), 4–16 (2014)

    Article  Google Scholar 

  9. Parikh, S.M.: A survey on cloud computing resource allocation techniques. In: 2013 Nirma University International Conference on Engineering (NUiCONE), pp. 1–5. IEEE (2013)

  10. Elghoneimy, E., Bouhali, O., Alnuweiri, H.: Resource allocation and scheduling in cloud computing. In: 2012 International Conference on Computing, Networking and Communications (ICNC), pp. 309–314. IEEE (2012)

  11. Mohan, N., Raj, E.B.: Resource Allocation Techniques in Cloud Computing–Research Challenges for Applications. In: 2012 Fourth International Conference on Computational Intelligence and Communication Networks (CICN), pp. 556–560. IEEE (2012)

  12. Hameed, A., Khoshkbarforoushha, A., Ranjan, R., Jayaraman, P.P., Kolodziej, J., Balaji, P., Zeadally, S., Malluhi, Q.M., Tziritas, N., Vishnu, A.: A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing 98, 751–774 (2014)

    Article  MathSciNet  Google Scholar 

  13. Mustafa, S., Nazir, B., Hayat, A., Madani, S.A.: Resource management in cloud computing: taxonomy, prospects, and challenges. Comput. Electr. Eng. 47, 186–203 (2015)

    Article  Google Scholar 

  14. Pawar, C.S., Wagh, R.: A review of resource allocation policies in cloud computing. World J. Sci. Technol. 2(3), 165–167 (2012)

    Google Scholar 

  15. Vinothina, V., Sridaran, R., Ganapathi, P.: A survey on resource allocation strategies in cloud computing. Int. J. Adv. Comput. Sci. Appl. 3(6), 97–104 (2012)

    Google Scholar 

  16. Bi, J., Zhu, Z., Yuan, H.: SLA-aware dynamic resource provisioning for profit maximization in shared cloud data centers. In: Wu, Y. (ed.) High Performance Networking, Computing, and Communication Systems, pp. 366–372. Springer, Berlin (2011)

    Chapter  Google Scholar 

  17. Abdulhamid, S.M., Latiff, M.S.A., Bashir, M.B.: Scheduling techniques in on-demand grid as a service cloud: a review. J. Theor. Appl. Inform. Technol. 63, 10–19 (2014)

    Google Scholar 

  18. Endo, P.T., de Almeida Palhares, A.V., Pereira, N.N., Goncalves, G.E., Sadok, D., Kelner, J., Melander, B., Mångs, J.-E.: Resource allocation for distributed cloud: concepts and research challenges. IEEE Netw. 25(4), 42–46 (2011)

    Article  Google Scholar 

  19. Mohamaddiah, M.H., Abdullah, A., Subramaniam, S., Hussin, M.: A survey on resource allocation and monitoring in cloud computing. Int. J. Mach. Learn. Comput. 4(1), 34 (2014)

    Google Scholar 

  20. Bashir, M.B., Abd Latiff, M.S., Abdulhamid, S.M., Loon, C.T.: Grid-based search technique for massive academic publications. Paper presented at the the 2014 third ICT international student project conference (ICT-ISPC2014), Thailand (2014)

  21. Toosi, A.N., Calheiros, R.N., Buyya, R.: Interconnected cloud computing environments: challenges, taxonomy, and survey. ACM Comput. Surv. 47(1), 7 (2014)

    Article  Google Scholar 

  22. Huang, L., Chen, H.-S., Hu, T.-T.: Survey on resource allocation policy and job scheduling algorithms of cloud computing1. J. Softw. 8(2), 480–487 (2013)

    Article  Google Scholar 

  23. Gong, Y., Ying, Z., Lin, M.: A survey of cloud computing. In: Proceedings of the 2nd International Conference on Green Communications and Networks 2012 (GCN 2012), Vol. 3, pp. 79–84. Springer, New York (2013)

  24. Ergu, D., Kou, G., Peng, Y., Shi, Y., Shi, Y.: The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment. J. Supercomput. 64(3), 835–848 (2013)

    Article  Google Scholar 

  25. Mann, Z.Á.: Allocation of virtual machines in cloud data centers-a survey of problem models and optimization algorithms. ACM Comput. Serv. 48, 11–34 (2015)

    Google Scholar 

  26. Akhter, N., Othman, M.: Energy aware resource allocation of cloud data center: review and open issues. Clust. Comput. 19, 1163–1182 (2016)

    Article  Google Scholar 

  27. Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., Stewart, L.A.: Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 4(1), 1 (2015)

    Article  Google Scholar 

  28. Kitchenham, B., Brereton, O.P., Budgen, D., Turner, M., Bailey, J., Linkman, S.: Systematic literature reviews in software engineering—a systematic literature review. Inform. Softw. Technol. 51(1), 7–15 (2009)

    Article  Google Scholar 

  29. Panda, S.K., Jana, P.K.: An efficient resource allocation algorithm for IaaS cloud. In: Distributed Computing and Internet Technology, pp. 351–355. Springer, New York (2015)

  30. Shyam, G.K., Manvi, S.S.: Resource allocation in cloud computing using agents. In: 2015 IEEE International Advance Computing Conference (IACC), pp. 458–463. IEEE (2015)

  31. An-ping, X., Chun-xiang, X.: Energy efficient multiresource allocation of virtual machine based on PSO in cloud data center. Mathematical Problems in Engineering (2014)

  32. Radhakrishnan, A., Kavitha, V.: Trusted virtual machine allocation in cloud computing IaaS service. Res. J. Appl. Sci. Eng. Technol. 7(14), 2921–2928 (2014)

    Google Scholar 

  33. Liang, Y., Rui, Q.P., Xu, J.: Computing resource allocation for enterprise information management based on cloud platform ant colony optimization algorithm. Adv. Mater. Res. 791, 1232–1237 (2013)

    Article  Google Scholar 

  34. Li, C., Li, L.: Efficient resource allocation for optimizing objectives of cloud users, IaaS provider and SaaS provider in cloud environment. J. Supercomput. 65(2), 866–885 (2013)

    Article  Google Scholar 

  35. Vernekar, S.S., Game, P.: Component based resource allocation in cloud computing. In: Proceedings of the International Conference on Information Systems Design and Intelligent Applications 2012 (INDIA 2012) held in Visakhapatnam, India, January 2012, pp. 907–914. Springer, New York (2012)

  36. Wang, W., Jiang, Y., Wu, W.: Multiagent-based resource allocation for energy minimization in cloud computing systems. IEEE Transactions on Systems, Man and Cybernetics (2016)

  37. Shelke, R., Rajani, R.: Dynamic resource allocation in cloud computing. Int. J. Eng. Res. Technol. 10 (2013)

  38. Jayanthi, S.: Literature review: dynamic resource allocation mechanism in cloud computing environment. In: 2014 International Conference on Electronics, Communication and Computational Engineering (ICECCE), pp. 279–281. IEEE (2014)

  39. Saraswathi, A., Kalaashri, Y., Padmavathi, S.: Dynamic resource allocation scheme in cloud computing. Proc. Comput. Sci. 47, 30–36 (2015)

    Article  Google Scholar 

  40. Wang, Z., Su, X.: Dynamically hierarchical resource-allocation algorithm in cloud computing environment. J. Supercomput. 71, 2748–2766 (2015)

    Article  Google Scholar 

  41. Wolke, A., Ziegler, L.: Evaluating dynamic resource allocation strategies in virtualized data centers. In: 2014 IEEE 7th International Conference on Cloud Computing (CLOUD), pp. 328–335. IEEE (2014)

  42. Xie, F., Liu, F.: Dynamic effective resource allocation based on cloud computing learning model. J. Netw. 9(11), 3092–3097 (2014)

    Google Scholar 

  43. Zhang, H.R., Yang, Y., Li, L., Cheng, W.Z., Ding, C.: A dynamic resource allocation framework in the cloud. Appl. Mech. Mater. 441, 974–979 (2014)

    Article  Google Scholar 

  44. Ali, J., Zafari, F., Khan, G.M., Mahmud, S.A.: Future clients’ requests estimation for dynamic resource allocation in cloud data center using CGPANN. In: 2013 12th International Conference on Machine Learning and Applications (ICMLA), pp. 331–334. IEEE (2013)

  45. Hu, W.X., Zheng, J., Hua, X.Y., Yang, Y.O.: A computing capability allocation algorithm for cloud computing environment. Appl. Mech. Mater. 347, 2400–2406 (2013)

    Article  Google Scholar 

  46. Oddi, G., Panfili, M., Pietrabissa, A., Zuccaro, L., Suraci, V.: A resource allocation algorithm of multi-cloud resources based on Markov decision process. In: 2013 IEEE 5th International Conference on Cloud Computing Technology and Science (CloudCom), pp. 130–135. IEEE (2013)

  47. Xiao, Z., Song, W., Chen, Q.: Dynamic resource allocation using virtual machines for cloud computing environment. IEEE Trans. Parallel Distrib. Syst. 24(6), 1107–1117 (2013)

    Article  Google Scholar 

  48. Dai, J., Hu, B., Zhu, L., Han, H., Liu, J.: Research on dynamic resource allocation with cooperation strategy in cloud computing. In: 2012 3rd International Conference on System Science, Engineering Design and Manufacturing Information (ICSEM), pp. 193–196. IEEE (2012)

  49. Hadji, M., Zeghlache, D.: Minimum cost maximum flow algorithm for dynamic resource allocation in clouds. In: 2012 IEEE 5th International Conference on Cloud Computing (CLOUD), pp. 876–882. IEEE (2012)

  50. Wang, L.Y., Liu, A.M.: The study on cloud computing resource allocation method. Appl. Mech. Mater. 198, 1506–1513 (2012)

    Article  Google Scholar 

  51. Wuhib, F., Stadler, R., Lindgren, H.: Dynamic resource allocation with management objectives—implementation for an OpenStack cloud. In: 2012 8th International Conference and 2012 Workshop on Systems Virtualiztion Management (SVM) Network and Service Management (CNSM), pp. 309–315. IEEE (2012)

  52. Yin, B., Wang, Y., Meng, L., Qiu, X.: A multi-dimensional resource allocation algorithm in cloud computing. J. Inform. Comput. Sci. 9(11), 3021–3028 (2012)

    Google Scholar 

  53. Zhang, Q., Zhu, Q., Boutaba, R.: Dynamic resource allocation for spot markets in cloud computing environments. In: 2011 Fourth IEEE International Conference on Utility and Cloud Computing (UCC), pp. 178–185. IEEE (2011)

  54. Teng, F., Magoulès, F.: A new game theoretical resource allocation algorithm for cloud computing. In: Advances in Grid and Pervasive Computing. Lecture Notes on Computer Science, vol. 6104, pp. 321–330. Springer, Berlin (2010)

  55. Wuhib, F., Yanggratoke, R., Stadler, R.: Allocating compute and network resources under management objectives in large-scale clouds. J. Netw. Syst. Manag. 23(1), 111–136 (2015)

    Article  Google Scholar 

  56. Islam, S., Keung, J., Lee, K., Liu, A.: Empirical prediction models for adaptive resource provisioning in the cloud. Future Gener. Comput. Syst. 28(1), 155–162 (2012)

    Article  Google Scholar 

  57. Patel, R., Dahiya, D.: Aggregation of cloud providers: a review of opportunities and challenges. In: 2015 International Conference on Computing, Communication & Automation (ICCCA), pp. 620–626. IEEE (2015)

  58. Dabbagh, M., Hamdaoui, B., Guizani, M., Rayes, A.: Energy-efficient resource allocation and provisioning framework for cloud data centers. IEEE Trans. Netw. Serv. Manage. 12(3), 377–391 (2015)

    Article  Google Scholar 

  59. Vasu, R., Nehru, E.I., Ramakrishnan, G.: Load forecasting for optimal resource allocation in cloud computing using neural method. Middle-East J. Sci. Res. 24(6), 1995–2002 (2016)

    Google Scholar 

  60. Wang, C.-F., Hung, W.-Y., Yang, C.-S.: A prediction based energy conserving resources allocation scheme for cloud computing. In: 2014 IEEE International Conference on Granular Computing (GrC), pp. 320–324. IEEE (2014)

  61. Mashayekhy, L., Nejad, M.M., Grosu, D., Vasilakos, A.V.: An online mechanism for resource allocation and pricing in clouds. IEEE Trans. Comput. 65(4), 1172–1184 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  62. Goutam, S., Yadav, A.K.: Preemptable priority based dynamic resource allocation in cloud computing with fault tolerance. In: 2015 International Conference on Communication Networks (ICCN), pp. 278–285. IEEE (2015)

  63. Wu, X., Gu, Y., Tao, J., Li, G., Jayaraman, P.P., Sun, D., Ranjan, R., Zomaya, A., Han, J.: An online greedy allocation of VMs with non-increasing reservations in clouds. J. Supercomput. 72(2), 371–390 (2016)

    Article  Google Scholar 

  64. Wu, X., Gu, Y., Li, G., Tao, J., Chen, J., Ma, X.: Online mechanism design for VMS allocation in private cloud. In: IFIP International Conference on Network and Parallel Computing, pp. 234–246. Springer, Berlin (2014)

  65. Gu, Y., Tao, J., Wu, X., Ma, X.: Online mechanism with latest-reservation for dynamic VMs allocation in private cloud. Int. J. Syst. Assur. Eng. Manag. (2016). doi:10.1007/s13198-016-0422-6

  66. Qian, L., Luo, Z., Du, Y., Guo, L.: Cloud computing: an overview. In: Jaatun, M.G., Zhao, G., Rong, C. (eds.) Cloud Computing, pp. 626–631. Springer, Berlin (2009)

    Chapter  Google Scholar 

  67. Kumar, N., Saxena, S.: A preference-based resource allocation in cloud computing systems. Proc. Comput. Sci. 57, 104–111 (2015)

    Article  Google Scholar 

  68. Mohana, R.: A position balanced parallel particle swarm optimization method for resource allocation in cloud. Indian J. Sci. Technol. 8(S3), 182–188 (2015)

    Article  Google Scholar 

  69. Nezarat, A., Dastghaibifard, G.: Efficient nash equilibrium resource allocation based on game theory mechanism in cloud computing by using auction. PloS ONE 10(10), e0138424 (2015)

    Article  Google Scholar 

  70. Samimi, P., Teimouri, Y., Mukhtar, M.: A combinatorial double auction resource allocation model in cloud computing. Inform. Sci. 357, 201–216 (2016)

    Article  Google Scholar 

  71. Li, H., Pu, Y., Lu, J.: A cloud computing resource pricing strategy research-based on resource swarm algorithm. In: 2012 International Conference on Computer Science & Service System (CSSS), pp. 2217–2222. IEEE (2012)

  72. Chintapalli, V.R.: A deadline and budget constrained cost and time optimization algorithm for cloud computing. In: International Conference on Advances in Computing and Communications, pp. 455–462. Springer, Berlin (2011)

  73. Teng, F., Magoules, F.: Resource pricing and equilibrium allocation policy in cloud computing. In: 2010 IEEE 10th International Conference on Computer and Information Technology (CIT), pp. 95–202. IEEE (2010)

  74. Kumar, K., Feng, J., Nimmagadda, Y., Lu, Y.-H.: Resource allocation for real-time tasks using cloud computing. In: 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN), pp. 1–7. IEEE (2011)

  75. Yi, P., Ding, H., Ramamurthy, B.: Budget-minimized resource allocation and task scheduling in distributed grid/clouds. In: 2013 22nd International Conference on Computer Communications and Networks (ICCCN), pp. 1–8. IEEE (2013)

  76. Casalicchio, E., Menascé, D.A., Aldhalaan, A.: Autonomic resource provisioning in cloud systems with availability goals. In: Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference. ACM, New York (2013)

  77. Gu, Y., Tao, J., Li, G., Sun, D.W., Wu, X., Jayaraman, P.P., Ranjan, R.: A preemptive truthful VMs allocation online mechanism in private cloud. J. Comput. Sci. (2016). doi:10.1016/j.jocs.2016.05.006

  78. Younge, A.J., Von Laszewski, G., Wang, L., Lopez-Alarcon, S., Carithers, W.: Efficient resource management for cloud computing environments. In: 2010 International Green Computing Conference, pp. 357–364. IEEE (2010)

  79. Mashayekhy, L., Nejad, M.M., Grosu, D., Vasilakos, A.V.: Incentive-compatible online mechanisms for resource provisioning and allocation in clouds. In: 2014 IEEE 7th International Conference on Cloud Computing (CLOUD), pp. 312–319. IEEE (2014)

  80. Nejad, M.M., Mashayekhy, L., Grosu, D.: Truthful greedy mechanisms for dynamic virtual machine provisioning and allocation in clouds. IEEE Trans. Parallel Distrib. Syst. 26(2), 594–603 (2015). doi:10.1109/tpds.2014.2308224

    Article  Google Scholar 

  81. Pradhan, P., Behera, P.K., Ray, B.: Modified round robin algorithm for resource allocation in cloud computing. Proc. Comput. Sci. 85, 878–890 (2016)

    Article  Google Scholar 

  82. Yang, Z., Liu, M., Xiu, J., Liu, C.: Study on cloud resource allocation strategy based on particle swarm ant colony optimization algorithm. In: 2012 IEEE 2nd International Conference on Cloud Computing and Intelligent Systems (CCIS), pp. 488–491. IEEE (2012)

  83. Xu, X., Yu, H.: A game theory approach to fair and efficient resource allocation in cloud computing. Mathematical Problems in Engineering (2014)

  84. Kaur, R., Luthra, P.: Load balancing in cloud computing. In: Proceedings of International Conference on Recent Trends in Information, Telecommunication and Computing, ITC. (2012)

  85. Aslam, S., Shah, M.A.: Load balancing algorithms in cloud computing: a survey of modern techniques. In: 2015 National Software Engineering Conference (NSEC), pp. 30–35. IEEE (2015)

  86. Katyal, M., Mishra, A.: A comparative study of load balancing algorithms in cloud computing environment. (2014). arXiv:1403.6918

  87. Parikh, K., Hawanna, N., Haleema, P.K., Iyengar, N.C.S.: Virtual machine allocation policy in cloud computing using CloudSim in Java. Int. J. Grid Distrib. Comput. 8(1), 145–158 (2015)

    Article  Google Scholar 

  88. Bhise, V.K., Mali, A.S.: Cloud resource provisioning for Amazon EC2. In: 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), pp. 1–7. IEEE (2013)

  89. Ray, S., Sarkar, A.D.: Resource allocation scheme in cloud infrastructure. In: 2013 International Conference on Cloud & Ubiquitous Computing & Emerging Technologies (CUBE), pp. 30–35. IEEE (2013)

  90. Villegas, D., Antoniou, A., Sadjadi, S.M., Iosup, A.: An analysis of provisioning and allocation policies for infrastructure-as-a-service clouds. In: 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 612–619. IEEE (2012)

  91. Zhang, Z., Wang, H., Xiao, L., Ruan, L.: A statistical based resource allocation scheme in cloud. In: 2011 International Conference on Cloud and Service Computing (CSC), pp. 266–273. IEEE (2011)

  92. Liu, L., Mei, H., Xie, B.: Towards a multi-QoS human-centric cloud computing load balance resource allocation method. J. Supercomput. 72, 2488–2501 (2016)

    Article  Google Scholar 

  93. Buyya, R., Beloglazov, A., Abawajy, J.: Energy-efficient management of data center resources for cloud computing: a vision, architectural elements, and open challenges. (2010). arXiv:1006.0308

  94. Beloglazov, A., Buyya, R.: Energy efficient resource management in virtualized cloud data centers. In: Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 826–831. IEEE Computer Society (2010)

  95. Pandi, K.M., Somasundaram, K.: Energy efficient in virtual infrastructure and green cloud computing: a review. Indian J. Sci. Technol. (2016). doi:10.17485/ijst/2016/v9i11/89399

  96. Singh, S.: Green computing strategies & challenges. In: 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), pp. 758–760. IEEE (2015)

  97. Ali, A., Lu, L., Zhu, Y., Yu, J.: An energy efficient algorithm for virtual machine allocation in cloud datacenters. In: Conference 2016, pp. 61–72. Springer, Berlin

  98. Beloglazov, A., Abawajy, J., Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener. Comput. Syst. 28(5), 755–768 (2012)

    Article  Google Scholar 

  99. Dashti, S.E., Rahmani, A.M.: Dynamic VMs placement for energy efficiency by PSO in cloud computing. J. Exp. Theor. Artif. Intell. 28, 351–367 (2016)

    Article  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  101. Kansal, N.J., Chana, I.: Artificial bee colony based energy-aware resource utilization technique for cloud computing. Concurr. Comput. 27(5), 1207–1225 (2015)

    Article  Google Scholar 

  102. Yanggratoke, R., Wuhib, F., Stadler, R.: Gossip-based resource allocation for green computing in large clouds. In: 2011 7th International Conference on Network and Service Management (CNSM), pp. 1–9. IEEE (2011)

  103. Jha, R.S., Gupta, P.: Power & load aware resource allocation policy for hybrid cloud. Proc. Comput. Sci. 78, 350–357 (2016)

    Article  Google Scholar 

  104. Gupta, P., Ghrera, S.: Power and fault aware reliable resource allocation for cloud infrastructure. Proc. Comput. Sci. 78, 457–463 (2016)

    Article  Google Scholar 

  105. Pavithra, B., Ranjana, R.: Energy efficient resource provisioning with dynamic VM placement using energy aware load balancer in cloud. In: 2016 International Conference on Information Communication and Embedded Systems (ICICES), pp. 1–6. IEEE (2016)

  106. Peng, Y., Kang, D.-K., Al-Hazemi, F., Youn, C.-H.: Energy and QoS aware resource allocation for heterogeneous sustainable cloud datacenters. Optical Switching and Networking (2016)

  107. Singh, K., Kaushal, S.: Energy efficient resource provisioning through power stability algorithm in cloud computing. In: Proceedings of the International Congress on Information and Communication Technology, pp. 255–263. Springer, Berlin (2016)

  108. Abdelmaboud, A., Jawawi, D.N., Ghani, I., Elsafi, A., Kitchenham, B.: Quality of service approaches in cloud computing: a systematic mapping study. J. Syst. Softw. 101, 159–179 (2015)

    Article  Google Scholar 

  109. Ardagna, D., Casale, G., Ciavotta, M., Pérez, J.F., Wang, W.: Quality-of-service in cloud computing: modeling techniques and their applications. J. Internet Serv. Appl. 5(1), 1–17 (2014)

    Article  Google Scholar 

  110. Batista, B.G., Estrella, J.C., Ferreira, C.H.G., Leite Filho, D.M., Nakamura, L.H.V., Reiff-Marganiec, S., Santana, M.J., Santana, R.H.C.: Performance evaluation of resource management in cloud computing environments. PloS ONE 10(11), 1–21 (2015)

    Article  Google Scholar 

  111. Li, J., Li, D., Ye, Y., Lu, X.: Efficient multi-tenant virtual machine allocation in cloud data centers. Tsinghua Sci. Technol. 20(1), 81–89 (2015)

    Article  Google Scholar 

  112. Horri, A., Mozafari, M.S., Dastghaibyfard, G.: Novel resource allocation algorithms to performance and energy efficiency in cloud computing. J. Supercomput. 69(3), 1445–1461 (2014)

    Article  Google Scholar 

  113. Katyal, M., Mishra, A.: Application of selective algorithm for effective resource provisioning in cloud computing environment. (2014). arXiv:1403.2914

  114. Lee, H.M., Jeong, Y.-S., Jang, H.J.: Performance analysis based resource allocation for green cloud computing. J. Supercomput. 69(3), 1013–1026 (2014)

    Article  Google Scholar 

  115. Li, Y.K.: QoS-aware dynamic virtual resource management in the cloud. In: Applied Mechanics and Materials, pp. 5809–5812. Trans Tech Publ 1 (2014)

  116. Pan, B.L., Wang, Y.P., Li, H.X., Qian, J.: Task scheduling and resource allocation of cloud computing based on QoS. Adv. Mater. Res. 915, 1382–1385 (2014)

    Article  Google Scholar 

  117. Kang, Z., Wang, H.: A novel approach to allocate cloud resource with different performance traits. In: 2013 IEEE International Conference on Services Computing (SCC), pp. 128–135. IEEE (2013)

  118. Nathani, A., Chaudhary, S., Somani, G.: Policy based resource allocation in IaaS cloud. Future Gener. Comput. Syst. 28(1), 94–103 (2012)

    Article  Google Scholar 

  119. Sagbo, K.A.R., Houngue, P.: Quality architecture for resource allocation in cloud computing. In: Service-Oriented and Cloud Computing. pp. 154–168. Springer, Berlin (2012)

  120. Wei, G., Vasilakos, A.V., Zheng, Y., Xiong, N.: A game-theoretic method of fair resource allocation for cloud computing services. J. Supercomput. 54(2), 252–269 (2010)

    Article  Google Scholar 

  121. Nguyen, T.-D., Nguyen, A.T., Nguyen, M.D., Van Nguyen, M., Huh, E.-N.: An improvement of resource allocation for migration process in cloud environment. Comput. J. 57(2), 308–318 (2013)

    Article  Google Scholar 

  122. Papagianni, C., Leivadeas, A., Papavassiliou, S., Maglaris, V., Cervelló-Pastor, C., Monje, A.: On the optimal allocation of virtual resources in cloud computing networks. IEEE Trans. Comput. 62(6), 1060–1071 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  123. Kumar, N., Chilamkurti, N., Zeadally, S., Jeong, Y.-S.: Achieving quality of service (QoS) using resource allocation and adaptive scheduling in cloud computing with grid support. Comput. J. 57(2), 281–290 (2014)

    Article  Google Scholar 

  124. Guo, J., Liu, F., Lui, J.C., Jin, H.: Fair network bandwidth allocation in IaaS datacenters via a cooperative game approach. IEEE/ACM Trans. Netw. 24(2), 873–886 (2016)

    Article  Google Scholar 

  125. Wang, H., Wang, F., Liu, J., Wang, D., Groen, J.: Enabling customer-provided resources for cloud computing: potentials, challenges, and implementation. IEEE Trans. Parallel Distrib. Syst. 26(7), 1874–1886 (2015)

    Article  Google Scholar 

  126. Brummett, T., Galloway, M.: Towards providing resource management in a local IaaS cloud architecture. In: Information Technology: New Generations, pp. 413–423. Springer, Berlin (2016)

  127. Lin, C.H., Lu, C.T., Chen, Y.H., Li, J.S.: Resource allocation in cloud virtual machines based on empirical service traces. Int. J. Commun. Syst. 27(12), 4210–4225 (2014)

    Article  Google Scholar 

  128. Pillai, P.S., Rao, S.: Resource allocation in cloud computing using the uncertainty principle of game theory. IEEE Syst. J. 10(2), 637–648 (2016)

    Article  Google Scholar 

  129. Rezvani, M., Akbari, M.K., Javadi, B.: Resource allocation in cloud computing environments based on integer linear programming. Comput. J. 52(2), 300–314 (2014)

    Google Scholar 

  130. Srinivasa, K., Srinidhi, S., Kumar, K.S., Shenvi, V., Kaushik, U.S., Mishra, K.: Game theoretic resource allocation in cloud computing. In: 2014 Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT), pp. 36–42. IEEE (2014)

  131. Tyagi, M., Manoria, M.: Secured data storage and computation technique for effective utilization of servers in cloud computing. In: Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems, vol. 1, pp. 531–541. Springer, Berlin (2016)

  132. Mell, P., Grance, T.: The NIST definition of cloud computing. Computer Security Division, Information Technology Laboratory (2011)

  133. Nabi, M., Toeroe, M., Khendek, F.: Availability in the cloud: state of the art. J. Netw. Comput. Appl. 60, 54–67 (2016)

    Article  Google Scholar 

  134. Hassan, S., Abbas Kamboh, A., Azam, F.: Analysis of cloud computing performance, scalability, availability, & security. In: 2014 International Conference on Information Science and Applications (ICISA), pp. 1–5. IEEE (2014)

  135. Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25(6), 599–616 (2009)

    Article  Google Scholar 

  136. Li, X., Li, Y., Liu, T., Qiu, J., Wang, F.: The method and tool of cost analysis for cloud computing. In: IEEE International Conference on Cloud Computing, 2009, CLOUD’09, pp. 93–100. IEEE (2009)

  137. Tziritas, N., Xu, C.-Z., Loukopoulos, T., Khan, S.U., Yu, Z.: Application-aware workload consolidation to minimize both energy consumption and network load in cloud environments. In: 2013 42nd International Conference on Parallel Processing (ICPP), pp. 449–457. IEEE (2013)

  138. Madni, S.H.H., Latiff, M.S.A., Coulibaly, Y.: Resource scheduling for infrastructure as a service (IaaS) in cloud computing: challenges and opportunities. J. Netw. Comput. Appl. 68, 173–200 (2016)

    Article  Google Scholar 

  139. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Article  Google Scholar 

  140. Xiong, K., Perros, H.: Service performance and analysis in cloud computing. In: 2009 World Conference on Services-I, pp. 693–700. IEEE (2009)

  141. Faragardi, H.R., Shojaee, R., Tabani, H., Rajabi, A.: An analytical model to evaluate reliability of cloud computing systems in the presence of QoS requirements. In: 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS), pp. 315–321. IEEE (2013)

  142. Bashir, M.B., Abd Latiff, M.S., Ahmed, A.A., Yousif, A., Eltayeeb, M.E.: Content-based information retrieval techniques based on grid computing: a review. IETE Tech. Rev. 30(3), 223–232 (2013)

    Article  Google Scholar 

  143. Patel, P., Ranabahu, A.H., Sheth, A.P.: Service level agreement in cloud computing (2009)

  144. Jing, S.-Y., Ali, S., She, K., Zhong, Y.: State-of-the-art research study for green cloud computing. J. Supercomput. 65(1), 445–468 (2013)

    Article  Google Scholar 

  145. Garg, S.K., Buyya, R.: Green cloud computing and environmental sustainability. Harnessing Green IT: Principles and Practices, pp. 315–340 (2012)

  146. Abdullahi, M., Ngadi, M.A.: Hybrid symbiotic organisms search optimization algorithm for scheduling of tasks on cloud computing environment. PloS ONE 11(6), e0158229 (2016)

    Article  Google Scholar 

  147. Hooper, A.: Green computing. Commun. ACM 51(10), 11–13 (2008)

    Article  Google Scholar 

  148. Chen, M., Mao, S., Liu, Y.: Big data: a survey. Mobile Netw. Appl. 19(2), 171–209 (2014)

  149. Pecero, J.E., Diaz, C.O., Castro, H., Villamizar, M., Sotelo, G., Bouvry, P.: Energy savings on a cloud-based opportunistic infrastructure. In: Service-Oriented Computing–ICSOC 2013 Workshops, pp. 366–378. Springer, Berlin (2014)

  150. Jebalia, M., Ben Letaïfa, A., Hamdi, M., Tabbane, S.: A comparative study on game theoretic approaches for resource allocation in cloud computing architectures. In: 2013 IEEE 22nd International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp. 336–341. IEEE (2013)

  151. Kashan, A.H., Karimi, B.: A new algorithm for constrained optimization inspired by the sport league championships. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8. IEEE (2010)

  152. Abdulhamid, S.M., Latiff, M.S.A., Madni, S.H.H., Oluwafemi, O.: A survey of league championship algorithm: prospects and challenges. Indian J. Sci. Technol. 8(S3), 101–110 (2015)

    Article  Google Scholar 

  153. Yazdani, M., Jolai, F.: Lion optimization algorithm (LOA): a nature-inspired metaheuristic algorithm. J. Comput. Design Eng. 3(1), 24–36 (2016)

    Article  Google Scholar 

  154. Kashan, A.H.: A new metaheuristic for optimization: optics inspired optimization (OIO). Comput. Oper. Res. 55, 99–125 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  155. Mirjalili, S.: SCA: a sine cosine algorithm for solving optimization problems. Knowledge-Based Systems (2016)

  156. Neshat, M., Sepidnam, G., Sargolzaei, M.: Swallow swarm optimization algorithm: a new method to optimization. Neural Comput. Appl. 23(2), 429–454 (2013)

    Article  Google Scholar 

  157. Rao, R.V., Savsani, V.J., Vakharia, D.: Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput. Aided Des. 43(3), 303–315 (2011)

    Article  Google Scholar 

  158. Zheng, Y.-J.: Water wave optimization: a new nature-inspired metaheuristic. Comput. Oper. Res. 55, 1–11 (2015)

    Article  MathSciNet  MATH  Google Scholar 

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  1. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

    Syed Hamid Hussain Madni, Muhammad Shafie Abd Latiff, Yahaya Coulibaly & Shafi’i Muhammad Abdulhamid

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  1. Syed Hamid Hussain Madni
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  2. Muhammad Shafie Abd Latiff
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  3. Yahaya Coulibaly
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  4. Shafi’i Muhammad Abdulhamid
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Madni, S.H.H., Latiff, M.S.A., Coulibaly, Y. et al. Recent advancements in resource allocation techniques for cloud computing environment: a systematic review. Cluster Comput 20, 2489–2533 (2017). https://doi.org/10.1007/s10586-016-0684-4

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