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A New Optimized Distributed Scheduling Service using Genetic Computing |
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PP: 279-285 |
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doi:10.18576/amis/13S131
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Author(s) |
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A. Sandana Karuppan,
N. Bhalaji,
N. Ramaraj,
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Abstract |
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| Cloud computing is a paradigm to perform distributed processing and open computing environment. It hides the need of high-cost dedicated expensive hardware, space and dedicated software to minimal interaction and management. Enormous growth of data or big-data generated by cloud system has been recognized. Recently cloud computing is delivering on-demand services like software, memory, data, network-bandwidth and IT related services on Internet. The reliable performance of cloud-services can be related to various key-factors like task-scheduling. Scheduling can be done in different levels like job level or infrastructure level or process level. In this research work focus mainly on task scheduling method. End-user sends the request to the main data-center for jobs to be computing, tasks are named. A task means piece of work or process that can be executed within the deadline. Tasks are divided into critical and non-critical where critical tasks are executed with in the given time period, and non-critical consider as low priority work in the cloud system. Scheduling dispatches the all user tasks provided by the users of cloud system to the cloud service provider for available resources in the cloud.
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