IMPROVING RESOURCE UTILIZATION USING QoS BASED LOAD BALANCING ALGORITHM FOR MULTIPLE WORKFLOWS IN IAAS CLOUD COMPUTING ENVIRONMENT

Abstract
Cloud computing is the extension of parallel computing, distributed computing and grid computing. It provides secure, quick, convenient data storage and net computing services through the internet. The services are available to user in pay per-use-on-demand model. The main aim of using resources from cloud is to reduce the cost and to increase the performance in terms of request response time. Thus, optimizing the resource usage through efficient load balancing strategy is crucial. The main aim of this paper is to develop and implement an Optimized Load balancing algorithm in IaaS virtual cloud environment that aims to utilize the virtual cloud resources efficiently. It minimizes the cost of the applications by effectively using cloud resources and identifies the virtual cloud resources that must be suitable for all the applications. The web application is created with many modules. These modules are considered as tasks and these tasks are submitted to the load balancing server. The server which consists our load balancing policies redirect the tasks to the corresponding virtual machines created by KVM virtual machine manager as per the load balancing algorithm. If the size of the database inside the machine exceeds then the load balancing algorithm uses the other virtual machines for further incoming request. The load balancing strategy are evaluated for various QoS performance metrics like cost, average execution times, throughput, CPU usage, disk space, memory usage, network transmission and reception rate, resource utilization rate and scheduling success rate for the number of virtual machines and it improves the scalability among resources using load balancing techniques.

Authors
L. Shakkeera, Latha Tamilselvan, Mohamed Imran
B.S. Abdur Rahman University, India

Keywords
Cloud Computing, Infrastructure as a Service (IaaS), Load Balancing, Assignment Approach, Round Robin Scheduling, KVM
Published By :
ICTACT
Published In :
ICTACT Journal on Communication Technology
( Volume: 4 , Issue: 2 )
Date of Publication :
June 2013

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