M. P. Gilesh
ABSTRACT
Allocating resources economically to virtual data centers is an important concern for cloud service providers while serving a new virtual data center deployment request. The cloud service providers may want to optimally place these topology adherent virtual data centers on their physical data centers to increase the resource utilization and the revenue. However, multiple provisioning, scaling, and de-provisioning of several virtual data centers of various sizes and topologies leave the cloud data center fragmented in terms of the residual server and network resources. Migrating the existing virtual machines and virtual network, if required, to accommodate a new virtual data center can increase the probability of acceptance and hence, the quality of experience of the customers. However, the migrations are costly and hence should be bounded to increase the revenue. In this paper, we propose a model to find a minimum cost virtual machine migration pattern to accommodate a new virtual data center. The objective is to limit the cost of migration so that the cloud service provider is benefited in terms of revenue. We propose a greedy and a meta-heuristic algorithm to solve the problem. Experimental results show that the proposed technique can reduce the average migration time upto 20% and the penalty for corresponding service level agreement violation by 200%.
- A. Amokrane, M.F. Zhani, R. Langar, R. Boutaba, and G. Pujolle. 2013. Greenhead: Virtual Data Center Embedding across Distributed Infrastructures. IEEE Trans. on Cloud Computing 1, 1 (Jan 2013), 36--49.Google Scholar
Cross Ref
- D G Anderson. 2002. Theoretical Approaches to Node Assignment. Unpublished Manuscript (2002). http://www.cs.cmu.edu/~dga/papers/anderson-assign.psGoogle Scholar
- M. F. Bari, M. F. Zhani, Q. Zhang, R. Ahmed, and R. Boutaba. 2014. CQNCR: Optimal VM migration planning in cloud data centers. In 2014 IFIP Networking Conference. 1--9.Google Scholar
- J. Chase and D. Niyato. 2017. Joint Optimization of Resource Provisioning in Cloud Computing. IEEE Transactions on Services Computing 10, 3 (May 2017), 396--409.Google ScholarCross Ref
- M. P. Gilesh, S. D. M. Kumar, L. Jacob, and U. Bellur. 2017. Towards a Complete Virtual Data Center Embedding Algorithm Using Hybrid Strategy. In 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS). 2616--2617.Google Scholar
- Chuanxiong Guo, Guohan Lu, Helen J. Wang, Shuang Yang, Chao Kong, Peng Sun, Wenfei Wu, and Yongguang Zhang. 2010. SecondNet: A Data Center Network Virtualization Architecture with Bandwidth Guarantees. In Proceedings of the 6th International Conference (Co-NEXT '10). ACM, New York, NY, USA, Article 15, 12 pages. Google ScholarDigital Library
- Dervis Karaboga. 2005. An idea based on honey bee swarm for numerical optimization. Technical Report. Erciyes University.Google Scholar
- Silvano Martello and Paolo Toth. 1990. Knapsack Problems: Algorithms and Computer Implementations. John Wiley & Sons, Inc., New York, NY, USA. Google ScholarDigital Library
- Senthil Nathan, Umesh Bellur, and Purushottam Kulkarni. 2015. Towards a Comprehensive Performance Model of Virtual Machine Live Migration. In Proceedings of the Sixth ACM Symposium on Cloud Computing (SoCC '15). ACM, New York, NY, USA, 288--301. Google ScholarDigital Library
- Nokia Siemens Networks GMBH & Co. KG, Klaus Hoffmann, and Marco Hoffman. 2012. Associating Computing Resources And Communication Resources With A Service In A Resource Management Architecture. (30 Aug 2012). https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2012113446&redirectedID=true&trk=prof-patent-title-linkGoogle Scholar
- Lorenzo Saino, Cosmin Cocora, and George Pavlou. 2013. A Toolchain for Simplifying Network Simulation Setup. In Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques (SIMUTOOLS '13). ICST, Cannes, France, 10. Google ScholarDigital Library
- Anja Strunk. 2012. Costs of Virtual Machine Live Migration: A Survey. In Proceedings of the 2012 IEEE Eighth World Congress on Services (SERVICES '12). IEEE Computer Society, Washington, DC, USA, 323--329. Google ScholarDigital Library
- VMware. 2015. Service Level Agreement for VMware vCloud Air. (2015). https://www.vmware.com/support/vcloud-air/sla.htmlGoogle Scholar
- F. Yan, T. T. Lee, and W. Hu. 2016. Congestion-Aware Embedding of Heterogeneous Bandwidth Virtual Data Centers With Hose Model Abstraction. IEEE/ACM Transactions on Networking PP, 99 (2016), 1--14. Google ScholarDigital Library
- Qi Zhang, M.F. Zhani, M. Jabri, and R. Boutaba. 2014. Venice: Reliable virtual data center embedding in clouds. In 2014 Proceedings IEEE INFOCOM. Toronto, 289--297.Google Scholar
- M.F. Zhani, Qi Zhang, G. Simon, and R. Boutaba. 2013. VDC Planner: Dynamic migration-aware Virtual Data Center embedding for clouds. In 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013). Ghent, Belgium, 18--25.Google Scholar
Index Terms
- Bounding the cost of virtual machine migrations for resource allocation in cloud data centers
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