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DYNAMIC WEB WORKLOAD MIGRATION TO CLOUD ENVIRONMENT

K. V. Nithyasundari

II year M.E. (CSE), Shree Venkateshwara HI-Tech Engg College, Gobi

Dr. T. Senthil Prakash

Professor & HOD, Shree Venkateshwara HI-Tech Engg College, Gobi

P. M. Manochitra

II year M.E. (CSE), Shree Venkateshwara HI-Tech Engg College, Gobi

R. Senthil Kumar

II year M.E. (CSE), Shree Venkateshwara HI-Tech Engg College, Gobi

50-58

Vol: 6, Issue: 1, 2016

Receiving Date: 2015-11-22 Acceptance Date:

2015-12-20

Publication Date:

2016-01-16

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Abstract

Web applications are accessed by million of users over the internet via a common web browser software. Traditional web application hosting model requires additional hardware to handle peak loads. Traffic uncertainty faces low utilization rates of hardware components. Cloud based virtualized services are used to support resources for web applications. Cloud services are provided in three layers such as infrastructure, platform and software services. Web application workloads are migrated to cloud environment to utilize the resources. Web/application server, load-balancer and database are transferred from the local data center to the selected cloud infrastructure. Price, Service Level Agreement (SLA), network latency, data center location and support quality factors are considered in the migration process.Cloud service provider’s offers computational services and Virtual Machine (VM) images for information systems. Throughput and cost factors are considered in the service selection process. CloudGenius framework is constructed to handle process migration from web applications into public cloud resources. CloudGenius provides migration support for multi-component web applications. Evolutionary migration process for web application clusters is distributed over multiple locations. A multi-criteria-based selection algorithm on Analytic Hierarchy Process (AHP) is employed in CloudGenius model. Parallel Genetic Algorithm (PGA) is applied to select migration solutions. CumulusGenius is an implementation support for CloudGenius framework.

Keywords: Cloud computing, parallel workloads, public clouds and Virtualization.

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