IT sector is adopting novel cloud computing to converge the business and technology platforms in terms of ease of services which allow users to access the resources in pay as go fashion anytime and anywhere. To accomplish this goal several challenges have to face in which balancing the load among the nodes is one of them. Despite the significance of load balancing algorithms there is no organized literature which could cover or analyze the dynamic migration techniques, their scope, limitations and challenges, so this article focus on those dynamic load balancing techniques in which lot of work has done to reduce the migration time of tasks form one VM to other. Task migration is an important load balancing metric in cloud computing by relocating active virtual machines (VMs) from one candidate node to another. To achieve better system performance load must be distribute evenly across the servers, for this under loading and overloading of VM should be avoid by migrating the extra tasks in shortest period. In this literature we have given the detailed overview of qualitative and quantitative analysis of existing task migration schemes, also merits, demerits and important challenges are addressed so that more resourceful and scalable migration algorithms could be develop in near future.

1. Calheiros, R. N. , Ranjan, R. , Beloglazov, A. , De Rose, C. A. , & Buyya, R. (2011). CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and experience, 41(1), 23-50.
2. Wu, T. Y. , Guizani, N. , & Huang, J. S. (2017). Live migration improvements by related dirty memory prediction in cloud computing. Journal of Network and Computer Applications, 90, 83-89.
3. Sreenivas, V. , Prathap, M. , & Kemal, M. (2014, February). Load balancing techniques: Major challenge in Cloud Computing-a systematic review. In Electronics and Communication Systems (ICECS), 2014 International Conference on (pp. 1-6). IEEE.
4. Gupta, A. , & Garg, R. (2017, September). Load Balancing Based Task Scheduling with ACO in Cloud Computing. In Computer and Applications (ICCA), 2017 International Conference on (pp. 174-179). IEEE.
5. Verma, P. , Shrivastava, S. , & Pateriya, R. K. (2017). Enhancing Load Balancing in Cloud Computing by Ant Colony Optimization Method.
6. Sarma, P. , Chana, I. G. , & Bala, A. G. (2017). Optimized Hybrid Task Scheduling Algorithm in Cloud (Doctoral dissertation).
7. Arya, P. S. S. K. , & Tripathi, P. (2016). Various Issues & Challenges of Load Balancing Over Cloud: A Survey. International Journal of Engineering and Computer Science, 5(8).
8. Ghumman, N. S. , & Sachdeva, R. (2016). An Efficient Approach for Load Balancing in Cloud Computing using Composite Techniques. International Journal of Research in Engineering and Applied Sciences, 6(2), 145-149.
9. Xu, M. , Tian, W. , & Buyya, R. (2017). A survey on load balancing algorithms for virtual machines placement in cloud computing. Concurrency and Computation: Practice and Experience, 29(12).
10. Milani, A. S. , & Navimipour, N. J. (2016). Load balancing mechanisms and techniques in the cloud environments: Systematic literature review and future trends. Journal of Network and Computer Applications, 71, 86-98.
11. Ramezani, F. , Lu, J. , & Hussain, F. K. (2014). Task-based system load balancing in cloud computing using particle swarm optimization. International journal of parallel programming, 42(5), 739-754.
12. Harraz, A. , Cherkaoui, R. , Bissiriou, C. , & Zbakh, M. (2016, May). Study of an adaptive approach for a Cloud system implementation. In Cloud Computing Technologies and Applications (CloudTech), 2016 2nd International Conference on (pp. 230-236). IEEE.
13. Babu, K. R. , & Samuel, P. (2016). Enhanced bee colony algorithm for efficient load balancing and scheduling in cloud. In Innovations in bio-inspired computing and applications (pp. 67-78). Springer, Cham.
14. Gutierrez-Garcia, J. O. , & Ramirez-Nafarrate, A. (2015). Agent-based load balancing in cloud data centers. Cluster Computing, 18(3), 1041-1062.
15. Wang, T. , Lin, Z. , Yang, B. , Gao, J. , Huang, A. , Yang, D. , & Niu, J. (2012). MBA: A market-based approach to data allocation and dynamic migration for cloud database. Science China Information Sciences, 55(9), 1935-1948.
16. De Falco, Ivanoe, et al. "Extremal Optimization applied to load balancing in execution of distributed programs. " Applied Soft Computing (2015): 501-513.
17. Kalra, M. , & Singh, S. (2015). A review of metaheuristic scheduling techniques in cloud computing. Egyptian informatics journal, 16(3), 275-295.
18. Ahmad, R. W. , Gani, A. , Hamid, S. H. A. , Shiraz, M. , Yousafzai, A. , & Xia, F. (2015). A survey on virtual machine migration and server consolidation frameworks for cloud data centers. Journal of Network and Computer Applications, 52, 11-25.
19. Beloglazov, A. , & Buyya, R. (2010, May). 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.
20. Osman, S. , Subhraveti, D. , Su, G. , & Nieh, J. (2002). The design and implementation of Zap: A system for migrating computing environments. ACM SIGOPS Operating Systems Review, 36(SI), 361-376.
21. Deshpande, Umesh, Unmesh Kulkarni, and Kartik Gopalan. "Inter-rack live migration of multiple virtual machines. " Proceedings of the 6th international workshop on Virtualization Technologies in Distributed Computing Date. ACM, 2012.
22. Gkatzikis, L. , & Koutsopoulos, I. (2013). Migrate or not? Exploiting dynamic task migration in mobile cloud computing systems. IEEE Wireless Communications, 20(3), 24-32.
23. Koto, A. , Yamada, H. , Ohmura, K. , & Kono, K. (2012, July). Towards unobtrusive VM live migration for cloud computing platforms. In Proceedings of the Asia-Pacific Workshop on Systems (p. 7). ACM.
24. Svärd, P. , Hudzia, B. , Tordsson, J. , & Elmroth, E. (2011). Evaluation of delta compression techniques for efficient live migration of large virtual machines. ACM Sigplan Notices, 46(7), 111-120.
25. Hines, M. R. , Deshpande, U. , & Gopalan, K. (2009). Post-copy live migration of virtual machines. ACM SIGOPS operating systems review, 43(3), 14-26.
26. Yin, F. , Liu, W. , & Song, J. (2014). Live virtual machine migration with optimized three-stage memory copy. In Future Information Technology (pp. 69-75). Springer, Berlin, Heidelberg.
27. Sahni, S. , & Varma, V. (2012, October). A hybrid approach to live migration of virtual machines. In Cloud Computing in Emerging Markets (CCEM), 2012 IEEE International Conference on (pp. 1-5). IEEE.
28. Verma, A. , Ahuja, P. , & Neogi, A. (2008, December). pMapper: power and migration cost aware application placement in virtualized systems. In Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware (pp. 243-264). Springer-Verlag New York, Inc.
29. Zhang, X. , Huo, Z. , Ma, J. , & Meng, D. (2010, September). Exploiting data deduplication to accelerate live virtual machine migration. In Cluster Computing (CLUSTER), 2010 IEEE International Conference on (pp. 88-96). IEEE.
30. Wang, Z. , Zhu, X. , McCarthy, C. , Ranganathan, P. , & Talwar, V. (2008, June). Feedback control algorithms for power management of servers. In Third International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks.
31. Von Laszewski, G. , Wang, L. , Younge, A. J. , & He, X. (2009, August). Power-aware scheduling of virtual machines in dvfs-enabled clusters. In Cluster Computing and Workshops, 2009. CLUSTER'09. IEEE International Conference on (pp. 1-10). IEEE.
32. Jeong, J. , Kim, S. H. , Kim, H. , Lee, J. , & Seo, E. (2013). Analysis of virtual machine live-migration as a method for power-capping. The Journal of Supercomputing, 66(3), 1629-1655.
33. Morrison, D. G. , & Schmittlein, D. C. (1988). Generalizing the NBD model for customer purchases: What are the implications and is it worth the effort?. Journal of Business & Economic Statistics, 6(2), 145-159.
34. Hirofuchi, T. , Ogawa, H. , Nakada, H. , Itoh, S. , & Sekiguchi, S. (2009, May). A live storage migration mechanism over wan for relocatable virtual machine services on clouds. In Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid (pp. 460-465). IEEE Computer Society.
35. Rani, A. , & Kaur, P. (2015). Migration Jobs in Cloud Computing. International Journal of Grid and Distributed Computing, 8(6), 151-160.
36. Choudhary, A. , Govil, M. C. , Singh, G. , Awasthi, L. K. , Pilli, E. S. , & Kapil, D. (2017). A critical survey of live virtual machine migration techniques. Journal of Cloud Computing, 6(1), 23.
37. Osanaiye, O. , Chen, S. , Yan, Z. , Lu, R. , Choo, K. K. R. , & Dlodlo, M. (2017). From cloud to fog computing: A review and a conceptual live VM migration framework. IEEE Access, 5, 8284-8300.
38. Aznoli, F. , & Navimipour, N. J. (2017). Cloud services recommendation: Reviewing the recent advances and suggesting the future research directions. Journal of Network and Computer Applications, 77, 73-86.

Load Balancing Task Migration Data Center Vm Cloud Computing Virtualization