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

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