An Efficient Virtual Resources Allocation Strategy for Cloud Computing
Abstract: In this paper, a virtual resource application-allocation model and an efficient virtual resource al-location strategy are presented aiming at the huge energy consumption problem during the idle time of host server in cloud data center. The strategy can maximize the use of the host server and reduce energy consumption of the infrastructure under the premise of meeting the users’ needs. The cloud tasks are submitted to the cloud center after the statistical synthesis at the ends of the cloud, and unified allocated by the resource manager of cloud center in order to achieve optimal utilization of the servers. Simulation results show that our proposed strategy has good effect for different number and type of cloud tasks scheduling, and can improve the utilization of cloud computing center server.
文章引用: 于宁 , 张金泉 , 倪丽娜 (2016) 云计算中虚拟资源高效分配策略研究。 计算机科学与应用， 6， 184-189. doi: 10.12677/CSA.2016.63023
 Ran, J.H., Li, S.Q., Liu, Y., et al. (2011) Study on Management and Dispatching of Virtual Computing Resources Based on Pool Theory. 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM), Wuhan, 23-25 September 2011, 1-7.
Gao, Y., Guan, H., Qi, Z., et al. (2013) A Multi-Objective Ant Colony System Algorithm for Virtual Machine Placement in Cloud Computing. Journal of Computer and System Sciences, 79, 1230-1242.
Hassan, M.M. and Alamri, A. (2014) Virtual Machine Resource Al-location for Multimedia Cloud: A Nash Bargaining Approach. Procedia Computer Science, 34, 571-576.
 You, X., Xu, X., Wan, J., et al. (2009) Ras-m: Resource Allocation Strategy Based on Market Mechanism in Cloud Computing. ChinaGrid Annual Conference, ChinaGrid’09, Yantai, 21-22 August 2009, 256-263.
 Deng L, Yao L. (2015) Dynamic Allocation of Virtual Resources Based on Genetic Algorithm in the Cloud. Advances in Services Computing, 9464, 153-164.
 Chen, Z.G., Du, K.J., Zhan, Z., et al. (2015) Deadline Constrained Cloud Computing Resources Scheduling for Cost Optimization Based on Dynamic Ob-jective Genetic Algorithm. 2015 IEEE Congress on IEEE Evolutionary Computation (CEC), Sendai, 25-28 May 2015, 708-714.
 Huang, D., Du, P., Zhu, C., et al. (2015) Multi-Resource Packing for Job Scheduling in Virtual Machine Based Cloud Environment. 2015 IEEE Symposium on Service-Oriented System Engineering (SOSE), San Francisco Bay, 30 March- 3 April 2015, 216-221.
 Choi, J., Adufu, T., Kim, Y., et al. (2015) A Job Dispatch Optimization Method on Cluster and Cloud for Large-scale High-Throughput Computing Service. 2015 International Conference on Cloud and Autonomic Computing (ICCAC), Boston, 21-25 September 2015, 283-290.
 Liaqat, M., Ninoriya, S., Shuja, J., et al. (2016) Virtual Machine Migration Enabled Cloud Resource Management: A Challenging Task. arXiv preprint arXiv:1601.03854
Zhou, A., Sun, Q., Sun, L., et al. (2015) Maximizing the Profits of Cloud Service Providers via Dynamic Virtual Resource Renting Approach. EURASIP Journal on Wireless Communications and Networking, 2015, 1-12.
 周山杰. 云计算环境下面向任务分类的个性虚拟化策略[D]: [硕士学位论文]. 沈阳: 辽宁大学, 2012.