Browse > Article
http://dx.doi.org/10.22937/IJCSNS.2021.21.2.18

Load Balancing Approach to Enhance the Performance in Cloud Computing  

Rassan, Iehab AL (Department of Computer Science, College of Computer and Information Sciences King Saud University)
Alarif, Noof (Department of Computer Science, College of Computer and Information Sciences King Saud University)
Publication Information
International Journal of Computer Science & Network Security / v.21, no.2, 2021 , pp. 158-170 More about this Journal
Abstract
Virtualization technologies are being adopted and broadly utilized in many fields and at different levels. In cloud computing, achieving load balancing across large distributed virtual machines is considered a complex optimization problem with an essential importance in cloud computing systems and data centers as the overloading or underloading of tasks on VMs may cause multiple issues in the cloud system like longer execution time, machine failure, high power consumption, etc. Therefore, load balancing mechanism is an important aspect in cloud computing that assist in overcoming different performance issues. In this research, we propose a new approach that combines the advantages of different task allocation algorithms like Round robin algorithm, and Random allocation with different threshold techniques like the VM utilization and the number of allocation counts using least connection mechanism. We performed extensive simulations and experiments that augment different scheduling policies to overcome the resource utilization problem without compromising other performance measures like makespan and execution time of the tasks. The proposed system provided better results compared to the original round robin as it takes into consideration the dynamic state of the system.
Keywords
Cloud Computing; Load Balancing; Round Robin; Virtual Machine;
Citations & Related Records
연도 인용수 순위
  • Reference
1 M. Mishra, S. Kumar, B. Sahoo and P. P. Parida, "Load balancing in cloud computing: A big picture," Journal of King Saud University-Computer and Information Sciences, 2018.
2 K. Li, G. Xu, G. Zhao, Y. Dong and D. Wang, "Cloud task scheduling based on load balancing ant colony optimization," In 2011 Sixth Annual ChinaGrid Conference, pp. 3-9, 2011.
3 M.-A. Vasile, F. Pop, R.-I. Tutueanu, V. Cristea and J. Kolodziej, "Resource-aware hybrid scheduling algorithm in heterogeneous distributed computing.," Future Generation Computer Systems, p. 51, 2014.
4 K. Ramana and M. Ponnavaikko, "AWSQ: an approximated web server queuing algorithm for heterogeneous web server cluster," International Journal of Electrical and Computer Engineering, vol. 9, no. 3, p. 2083, 2019.   DOI
5 S. Sharma, A. K. Luhach and S. S. Abdhullah, "An optimal load balancing technique for cloud computing environment using bat algorithm," lndian Journal of Science and Technology, vol. 9, no. 28, 2016.
6 M. H. Shirvani, A. M. Rahmani and A. Sahafi, "A survey study on virtual machine migration and server consolidation techniques in DVFS-enabled cloud datacenter: taxonomy and challenges," Journal of King Saud University-Computer and Information Sciences, 2018.
7 U. Singhal and S. Jain, "A new fuzzy logic and GSO based load balancing mechanism for public cloud," International Journal of Grid and Distributed Computing, vol. 7, no. 5, pp. 97-110, 2014.   DOI
8 K. Maheshwari and V. K. Gupta, " Load Balancing in VM in Cloud Computing Using CloudSim.," Cloud Computing, 2019.
9 Ray, S. and De Sarkar, A., 2012. Execution analysis of load balancing algorithms in cloud computing environment. International Journal on Cloud Computing: Services and Architecture (IJCCSA), 2(5), pp.1-13.   DOI
10 Z. M. Elngomi and K. Khanfar, "A Comparative Study of Load Balancing Algorithms: A Review Paper," International Journal of Computer Science and Mobile Computing, vol. 5, no. 6, pp. 448-458, 2016.
11 D. L. Eager, E. D. Lazowska and J. Zahorjan, "A comparison of receiver-initiated and sender-initiated adaptive load sharing," Performance evaluation, vol. 6, no. 1, pp. 53-68, 1986.   DOI