Authors: Anurag Jain; Rajneesh Kumar
Addresses: Department of Computer Science and Engineering, Chandigarh Engineering College, Landran, Mohali, Punjab, India ' Department of Computer Science and Engineering, Maharishi Markandeshwar Engineering College, Maharishi Markandeshwar University, Mullana, Ambala, India
Abstract: Future of cloud computing depends on effective installation of infrastructure, efficient utilisation of resources and dynamic transformation of load. Due to inundation of tasks at the data centre there is a need for load balancing strategy. This will help in achieving better fault tolerance ratio and higher customer satisfaction. Load balancing strategy plays an important role in he distribution of the workload dynamically across multiple nodes so that no server is either underutilised or overwhelmed. Also, due to data proliferation nature of data sources such as social media sites, geographical information systems and the weather forecasting system, there is an exponential growth of structured and unstructured data which is called big data. The present data models are not capable enough to handle big data. To process the data efficiently, there is also a need of load balancing strategy at the data centre level. In this paper, the authors experimentally analyse some popular approaches for load balancing of tasks in a cloud environment using the cloud analyst simulator.
Keywords: cloud computing; cloud analyst; load balancing; task scheduling; load balancing algorithm; big data.
International Journal of Communication Networks and Distributed Systems, 2017 Vol.18 No.3/4, pp.213 - 234
Received: 21 Oct 2015
Accepted: 28 Jun 2016
Published online: 18 Apr 2017 *