APPLICATION OF ENGANCED WRR AS LOAD BALANCING ALGORITHM IN CLOUD COMPUTING

Abstract

The recent emerging framework for cloud computing is set in the exchange of data resources in a decentralized dais, a technology based on clouds. Consequently, the requirements of clients are meeting with the widespread boom of technological developments. Furthermore it involves sellers that extend their approval as well as introduction of the new high performance computing model. The primary questions concerning the distributed computing framework, nevertheless, are the effective distribution of resources, task scheduling as well as load balancing. The paradigm of cloud / use computing includes a complex cloud-site function, in order to accomplish the productivity and control of demands as deliberately as it can be. Effective load management and appropriate resource distribution are critical mechanisms for optimizing the efficiency of various resources and for allowing reasonable use of current cloud storage properties. The cloud-based architecture therefore has many types of load issues, for example CPU loading, server loading, memory dump, network loading etc. This helps to achieve failure, reduce the backlog issues, ability to adapt, utilization of resources appropriately, increase reliability and customer performance and so on in the cloud environments by an effective load balancing model. This thesis studied different popular algorithms for load balancing in cloud computing. Revised round robin models are typically used for scheduling problems as well as load balancing by multiple big corporations to overcome the said issues. A EWRR algorithm has been implemented in this thesis concentrating on effective load balancing and efficient resource management as well as task scheduling problems.