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Title |
Supervised Machine Learning Algorithms for Priority Task Classification in the Cloud Computing Environment |
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Author |
Naoufal Er-raji, Faouzia Benabbou, Mirela Danubianu, Amal Zaouch |
| Citation |
Vol. 18 No. 11 pp. 176-181 |
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Abstract |
Nowadays, with the tremendous growth of request for the computing resources, the majority of the Information Technology (IT) companies start using new technologies which can give high performance resources with easy using. The cloud computing is one of the smart technologies of them. It is a new paradigm that can provide on demand services through a network (generally internet) such as servers, storage disk, platforms and applications to any Cloud Service Consumers (CSC). The CSCs focuses on minimizing response time of the service while the Cloud Service Provider (CSP) focus on efficient utilization of cloud resources in order to respect the Service Level Agreement (SLA). To satisfy both of themes, efficient methods for optimizing task scheduling have to be provided. This paper strives to use the Supervised Machine Learning Algorithms to classify the priority tasks into different tasks priority queue in order to improve the task scheduling response time. |
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Keywords |
Cloud Computing, Data-Mining, Priority Task Classification, Supervised Machine Learning Algorithms, Task Scheduling |
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