Resource Scheduling in cloud Computing Using Genetic Algorithm

Authors: Kiran Chhabra, Prof. Kapil Sahu

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Abstract

Cloud computing is a distributed environment where various efficient computing engines are help to execute the clients request. Due to the unpredictable nature of work load in the cloud servers load balancing techniques are help to manage the work load and handle the request. The proposed work is intended to find the most appropriate algorithm for handling the work load on these servers. Therefore a comparative study is conducted in this proposed work. For performing the comparative study the data center load is evaluated using by modified Genetic algorithm distributed load scheduling scheme and implementation is in Cloud Simulator with performance evaluation

Introduction

Cloud computing is a computing paradigm, where a large pool of systems are connected in private or public networks, to provide dynamically scalable infrastructure for application, data and file storage. With the advent of this technology, the cost of computation, application hosting, content storage and delivery is reduced significantly. Cloud computing is a practical approach to experience direct cost benefits and it has the potential to transform a data center from a capital-intensive set up to a variable priced environment. An example of a Cloud Computing provider is Google's Gmail. Gmail users can access files and applications hosted by Google via the internet from any device [1]. Cloud computing is in grid computing based on a new calculation model, is the next generation network computing platforms core technologies, It builds virtualization super computer, with on demand rent way which provides data storage, analysis and scientific computing services through the distributed computing model and the resource pool technology. Cloud computing is also a kind of distributed computing, Through the virtualization technology will be distributed in the network computer resources of idle which combined into one huge resource pool, which is constituted as a super computing capacity of the computer. [2].

Conclusion

Cloud Computing along with research challenges in load balancing. Major thrust is given on the study of Resource Scheduling algorithm, followed by a comparative survey of these above mentioned algorithms in cloud computing with respect to stability, resource utilization, static or dynamicity, cooperative or non-cooperativeness and process migration.