A review of virtual machine (VM) resource scheduling algorithms in cloud computing environment

References

• A. Iosup, S. Ostermann, M.N. Yigitbasi, et al., Performance analysis of cloud computing services for many-tasks scientific computing, IEEE Trans. Parallel Distrib. Syst. 22 (6) (2011): 931–945. doi: 10.1109/TPDS.2011.66
   Web of Science ®Google Scholar
• A.S. Prasad, S. Rao, A mechanism design approach to resource procurement in cloud computing, IEEE Trans. Comput. 63 (1) (2014): 17–30. doi: 10.1109/TC.2013.106
   Web of Science ®Google Scholar
• J. Li, X. Tan, X.F. Chen, et al., OPoR: enabling proof of retrievability in cloud computing with resource-constrained devices, IEEE Trans. Cloud Comput. 3 (2) (2015): 195–205. doi: 10.1109/TCC.2014.2366148
   Web of Science ®Google Scholar
• J.W. Lin, C.H. Chen, J.M. Chang, QoS-aware data replication for data-intensive applications in cloud computing systems, IEEE Trans. Cloud Computing (1) (2013): 101–115. doi: 10.1109/TCC.2013.1
   Google Scholar
• D. Bruneo, A stochastic model to investigate data centre performance and QoS in IaaS cloud computing systems, IEEE Trans. Parallel Distrib. Syst. 25 (3) (2014): 560–569. doi: 10.1109/TPDS.2013.67
   Web of Science ®Google Scholar
• P.B. Si, Q. Zhang, F.R. Yu, et al., QoS-aware dynamic resource management in heterogeneous mobile cloud computing networks, Chin. Commun. 11 (5) (2014): 144–159. doi: 10.1109/CC.2014.6880470
   Web of Science ®Google Scholar
• Ramesh C. Poonia, Reena dadhich and X. Z. Gao, (in press), “Simulation Based Efficient Analysis of Radio Propagation Model using On-demand Routing Protocols in the Indian Automotive Networks”, the Int. J. Autonomous and Adaptive Communications Systems.
   Google Scholar
• H. Zhao, X.X. Liu, X.L. Li, Towards efficient and fair resource trading in community-based cloud computing, J. Parallel Distrib. Comput. 74 (11) (2014): 3087–3097. doi: 10.1016/j.jpdc.2014.07.005
   Web of Science ®Google Scholar
• M.H. Eawna, S.H. Mohammed, E.S.M. El-horbaty, Hybrid algorithm for resource provisioning of multi-tier cloud computing, Procedia Comput. Sci. 65 (2015): 682–690. doi: 10.1016/j.procs.2015.09.012
   Google Scholar
• Z. Yang, C.Q. Yin, Y. Liu, A cost based resource scheduling paradigm in cloud computing, in: Proceedings of the 12th International Conference on Parallel and Distributed Computing, vol. 1, (15), 2011: 417–422.
   Google Scholar
• K. Zhu, H.G. Song, L.J. Liu, Hybrid genetic algorithm for cloud computing applications, IEEE Asia-Pacific Serv. Comput. Conf. 1 (2011): 182–187.
   Google Scholar
• X.S. Yang, A new metaheuristic bat-inspired algorithm, Science 284 (2010): 65–74.
   Google Scholar
• Zhang, X., Liu, C., Nepal, S., Pandey, S., & Chen, J., A privacy leakage upper bound constraint-based approach for cost-effective privacy preserving of intermediate data sets in cloud. Parallel and Distributed Systems, IEEE Transactions, 24 (6), 2013: 1192–1202.
   Google Scholar
• Verma, A., & Kaushal, S., Deadline and budget distribution based cost-time optimization workflow scheduling algorithm for cloud. In IJCA Proceedings on international conference on recent advances and future trends in information technology.
   Google Scholar
• Wenhao, L.I., 2010, A community cloud oriented workflow system framework and its scheduling strategy. IEEE 2nd Symposium on Web Society (SWS), 2010: 316–325.
   Google Scholar
• Rimal, B.P. and El-Refaey, M.A., 2010, A framework of scientific workflow management systems for multi-tenant cloud orchestration environment. 19th IEEE international workshop on In Enabling technologies: Infrastructures for collaborative enterprises (wetice), 2010: 88–93.
   Google Scholar
• V. Nelson, V. Uma “Semantic based Resource Provisioning and Scheduling in Inter-Cloud Environment,” International Conference on Recent Trends in Information Technology (ICRTIT), 2012: 250–254.
   Google Scholar
• Li, W., Tordsson, J., & Elmroth, E., Virtual machine placement for predictable and time-constrained peak loads. In Economics of Grids, Clouds, Systems, and Services, 2011: 120–134.
   Google Scholar
• Ezugwu, A. E., Buhari, S. M., & Junaidu, S. B., Virtual machine allocation in cloud computing environment. International Journal of Cloud Applications and Computing (IJCAC), 3 (2), 2013: 47–60. doi: 10.4018/ijcac.2013040105
   Google Scholar
• Z. Xiao, W. Song and Q. Chen., Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment. In IEEE Transactions on Parallel and Distributed Systems, 24, 6, 2013: 1107–1117. doi: 10.1109/TPDS.2012.283
   Web of Science ®Google Scholar
• Zuo, L.Y., Cao, Z.B. and Dong, S.B., Virtual resource evaluation model based on entropy optimized and dynamic weighted in cloud computing. J. Softw, 2013: 1937–1946.
   Google Scholar
• Yang, C. L., & Huang, R. H. (2011). Optimal number and scheduling of freeway bus fleet. Journal of Statistics and Management Systems, 14(5), 949–964. doi: 10.1080/09720510.2011.10701594
   Google Scholar
• Ling, Jin, et al., “Cloud seedability study with a dual-model system.” Atmospheric and Oceanic Science Letters 6.4 (2013): 197–202. doi: 10.1080/16742834.2013.11447080
   Google Scholar
• Li, K., Zhang, Z., & Ma, H. (2014). Secure Multi-party Computation based on m-out-n OT. Journal of Discrete Mathematical Sciences and Cryptography, 17(3), 213–226. doi: 10.1080/09720529.2013.842061
   Google Scholar