Improving Load Distribution in Throttled Algorithm by Dynamic Threshold Based Load Balancing

Shalini Joshi*, Uma Kumari**
* Department of Computer Science and Engineering, Mody University of Science and Technology, Lakshmangarh, Rajasthan, India.
**Department of Computer Science and Engineering, Mody University of Science and Technology, Lakshmangarh, Rajasthan, India.
Periodicity:June - August'2017
DOI : https://doi.org/10.26634/jit.6.3.13783

Abstract

Cloud Computing (CC) is a buzzword, which came into existence after decades of research using existing technologies like parallel computing, grid computing, peer to peer technology, distributing computing, and virtualization. Now-adays, the most approved applications are based on internet services with a large number of users. Therefore, as the size of cloud scales up, cloud computing service providers make it necessary to handle massive requests. Load balancing is one of the main challenges in cloud computing which distributes the dynamic workload across multiple nodes to ensure that no single resource is either overburdened or under used (idle). Therefore, several load balancing algorithms have been designed, which reduces the response time of different tasks and also improve the resource utilization. So, a Dynamic threshold based load balancing algorithm has been developed in this paper. This algorithm distributes the load among different virtual machine as well as improves the response time. Thus the proposed algorithm improves the precision of load prediction. Additionally, Cloud Analyst tool is used to simulate this work and then compare with AMLB (Active Monitoring) and Throttled load balancing algorithms. Results demonstrate that the performance of proposed algorithm is better than AMLB and Throttled load balancing algorithm in terms of load and response time.

Keywords

Load Balancing, Load and Response Time, Cloud Analyst.

How to Cite this Article?

Joshi, S. and Kumari, U. (2017). Improving Load Distribution in Throttled Algorithm by Dynamic Threshold Based Load Balancing. i-manager’s Journal on Information Technology, 6(3), 36-43. https://doi.org/10.26634/jit.6.3.13783

References

[1]. Adhikari, J., & Patil, S. (2013, July). Double threshold energy aware load balancing in cloud computing. In Computing, Communications and Networking Technologies (ICCCNT), 2013 Fourth International Conference on (pp. 1-6). IEEE.
[2]. Domanal, S. G., & Reddy, G. R. M. (2013, October). Load balancing in cloud computing using modified throttled algorithm. In Cloud Computing in Emerging Markets (CCEM), 2013 IEEE International Conference on (pp. 1-5). IEEE.
[3]. Domanal, S. G., & Reddy, G. R. M. (2014, January). Optimal load balancing in cloud computing by efficient utilization of virtual machines. In Communication Systems and Networks (COMSNETS), 2014 Sixth International Conference on (pp. 1-4). IEEE.
[4]. Gopinath, P. G., & Vasudevan, S. K. (2015). An indepth analysis and study of Load balancing techniques in the cloud computing environment. Procedia Computer Science, 50, 427-432.
[5]. Katyal, M., & Mishra, A. (2014). A comparative study of load balancing algorithms in cloud computing environment. arXiv preprint arXiv:1403.6918.
[6]. Kumar, A., & Kalra, M. (2016, April). Load balancing in cloud data center using modified active monitoring load balancer. In Advances in Computing, Communication, & Automation (ICACCA) (Spring), International Conference on (pp. 1-5). IEEE.
[7]. Mao, Y., Ren, D., & Chen, X. (2013, December). Adaptive load balancing algorithm based on prediction model in cloud computing. In Proceedings of the Second International Conference on Innovative Computing and Cloud Computing (p. 165). ACM.
[8]. Mesbahi, M., & Rahmani, A. M. (2016). Load balancing in cloud computing: A state of the art survey. International Journal of Modern Education and Computer Science, 8(3), 64.
[9]. Moharana, S. S., Ramesh, R. D., & Powar, D. (2013). Analysis of load balancers in cloud computing. International Journal of Computer Science and Engineering, 2(2), 101-108.
[10]. More, N. S., & Hiray, S. R. (2012, September). Load balancing and resource monitoring in cloud. In Proceedings of the CUBE International Information Technology Conference (pp. 552-556). ACM.
[11]. Nitika, M., Shaveta, M., & Raj, M. G. (2012). Comparative analysis of load balancing algorithms in cloud computing. International Journal of Advanced Research in Computer Engineering & Technology, 1(3), 120-124.
[12]. Panwar, R., & Mallick, B. (2015). A comparative study of load balancing algorithms in cloud computing. International Journal of Computer Applications, 117(24).
[13]. Patel, J., Thaker, C. S., & Chaudhari, H. (2014, November). Task Execution Efficiency Enrichment in Cloud Based Load Balancing Approaches. In Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies (p. 64). ACM.
[14]. Raghava, N. S., & Singh, D. (2014). Comparative study on load balancing techniques in cloud computing. Open Journal of Mobile Computing and Cloud Computing, 1(1).
[15]. Rajeshkannan, R., & Aramudhan, M. (2016). Comparative study of load balancing algorithms in Cloud Computing environment. Indian Journal of Science and Technology, 9(20).
[16]. Ray, S., & 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), 1-13.
[17]. Shah, M. M. D., Kariyani, M. A. A., & Agrawal, M. D. L. (2013). Allocation of virtual machines in cloud computing using load balancing algorithm. International Journal of Computer Science and Information Technology & Security (IJCSITS), 3(1), 2249-9555.
[18]. Soni, G., & Kalra, M. (2014, February). A novel approach for load balancing in cloud data center. In Advance Computing Conference (IACC), 2014 IEEE International (pp. 807-812). IEEE.
[19]. Wickremasinghe, B., & Buyya, R. (2009). CloudAnalyst: A CloudSim-based tool for modelling and analysis of large scale cloud computing environments. MEDC Project Report, 22(6), 433-659.
[20]. Wickremasinghe, B., Calheiros, R. N., & Buyya, R. (2010, April). Cloudanalyst: A cloudsim-based visual modeller for analysing cloud computing environments and applications. In Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on (pp. 446-452). IEEE.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Online 15 15

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.