Analysis of Different Load Balancing Techniques
DOI:
https://doi.org/10.18486/ijcsnt/13.1.170Keywords:
Cloud Computing, Load Balancing Algorithms, Task SchedulingAbstract
Cloud computing is a popular paradigm which provides on-demand services to the user. As needs of the user changes dynamically, it is the responsibility of the cloud service provider to handle the requests efficiently and to satisfy the demands of end user by ensuring quality of service. Cloud computing suffers from umpteen critical problems which needs to be explored. One such problem is Load Balancing. It distributes the load evenly among the nodes with a condition that no overloading of the node occurs. So, it is better to schedule the tasks in an intelligent manner to utilize the resources efficiently. Task Scheduling is an important research area in cloud computing. It deals with the NP-hard problems. To find the near optimal solution, meta-heuristic techniques are used. In this paper, an in-depth review of different task scheduling algorithms based on load balancing have been discussed. We have compared these algorithms on the basis of pros and cons.
References
Zhang, Qi, Lu Cheng, and Raouf Boutaba. "Cloud computing: state-of-the-art and research challenges." Journal of internet services and applications 1.1 (2010): 7-18. DOI: https://doi.org/10.1007/s13174-010-0007-6
Manvi, Sunilkumar S., and Gopal Krishna Shyam. "Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey." Journal of Network and Computer Applications 41 (2014): 424-440. DOI: https://doi.org/10.1016/j.jnca.2013.10.004
Liu, Lixia, Hong Mei, and Bing Xie. "Towards a multi-QoS human-centric cloud computing load balance resource allocation method." The Journal of Supercomputing (2015): 1-14. DOI: https://doi.org/10.1007/s11227-015-1472-2
Pan, Jeng-Shyang, et al. "Interaction Artificial Bee Colony Based Load Balance Method in Cloud Computing." Genetic and Evolutionary Computing. Springer International Publishing, 2015. 49-57. DOI: https://doi.org/10.1007/978-3-319-12286-1_6
Fang, Yiqiu, Fei Wang, and Junwei Ge. "A task scheduling algorithm based on load balancing in cloud computing." Web Information Systems and Mining. Springer Berlin Heidelberg, 2010. 271-277. DOI: https://doi.org/10.1007/978-3-642-16515-3_34
Dasgupta, Kousik, et al. "A genetic algorithm (ga) based load balancing strategy for cloud computing." Procedia Technology 10 (2013): 340-347. DOI: https://doi.org/10.1016/j.protcy.2013.12.369
Krishna, P. Venkata. "Honey bee behavior inspired load balancing of tasks in cloud computing environments." Applied Soft Computing 13.5 (2013): 2292-2303. DOI: https://doi.org/10.1016/j.asoc.2013.01.025
Mao, Yingchi, Xi Chen, and Xiaofang Li. "Max–min task scheduling algorithm for load balance in cloud computing." Proceedings of International Conference on Computer Science and Information Technology. Springer India, 2014. DOI: https://doi.org/10.1007/978-81-322-1759-6_53
Domanal, Shridhar G., and G. Ram Mohana Reddy. "Load Balancing in Cloud Computingusing Modified Throttled Algorithm." Cloud Computing in Emerging Markets (CCEM), 2013 IEEE International Conference on. IEEE, 2013. DOI: https://doi.org/10.1109/CCEM.2013.6684434
Soni, Gaurav, and Mala Kalra. "A novel approach for load balancing in cloud data center." Advance Computing Conference (IACC), 2014 IEEE International. IEEE, 2014. DOI: https://doi.org/10.1109/IAdCC.2014.6779427
Laxmi Shrivastava, G S Tomar, and S S Bhadoria, “A Load-Balancing Approach for Congestion Adaptivity in MANET”, IEEE International Conference on Computational Intelligence and Communication Networks (CICN), pp 32-36, Oct 2011. DOI- 10.1109/CICN.2011.7 DOI: https://doi.org/10.1109/CICN.2011.7
Domanal, Shridhar G., and G. Ram Mohana Reddy. "Optimal load balancing in cloud computing by efficient utilization of virtual machines." Communication Systems and Networks (COMSNETS), 2014 Sixth International Conference on. IEEE, 2014. DOI: https://doi.org/10.1109/COMSNETS.2014.6734930
Singh, Aarti, Dimple Juneja, and Manisha Malhotra. "Autonomous Agent Based Load Balancing Algorithm in Cloud Computing." Procedia Computer Science 45 (2015): 832-841. DOI: https://doi.org/10.1016/j.procs.2015.03.168
Pan, Jengshyang, Pingfei Ren, and Linlin Tang. "Research on Heuristic Based Load Balancing Algorithms in Cloud Computing." Intelligent Data Analysis and Applications. Springer International Publishing, 2015. 417-426. DOI: https://doi.org/10.1007/978-3-319-21206-7_35
Ramezani, Fahimeh, Jie Lu, and Farookh Khadeer Hussain. "Task-based system load balancing in cloud computing using particle swarm optimization." International Journal of Parallel Programming 42.5 (2014): 739-754. DOI: https://doi.org/10.1007/s10766-013-0275-4
Banerjee, Sourav, et al. "Development and Analysis of a New Cloudlet Allocation Strategy for QoS Improvement in Cloud." Arabian Journal for Science and Engineering 40.5 (2015): 1409-1425. DOI: https://doi.org/10.1007/s13369-015-1626-9
L. Shrivastava, SS Bhadoria, GS Tomar, BK Chaurasia, “Effect of number of CBR Connections on the performance of a Load Balanced Congestion Adaptive Routing for MANET”, IEEE International Conference (CICN), pp 112-116, 3-5 Nov 2012. DOI: 10.1109/CICN.2012.104 DOI: https://doi.org/10.1109/CICN.2012.104
Laxmi Shrivastava, G.S. Tomar, Sarita S. Bhadoria, “A Secure Congestion Adaptive Routing with Load Balancing”, International Journal of Communication Systems and Network Technologies, Vol.1, No.3, pp.143-156, 2012. DOI- 10.18486/ijcsnt/1.3.012 DOI: https://doi.org/10.18486/ijcsnt/1.3.012
Leelipushpam, P. Getzi Jeba, and J. Sharmila. "Live VM migration techniques in cloud environment—a survey." Information & Communication Technologies (ICT), 2013 IEEE Conference on. IEEE, 2013.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Gundipika Kaur, Kiranbir Kaur, Prabhsimran Singh
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
