A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms
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| Formato: | Artículo científico |
| Lenguaje: | en |
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Universidade Federal de Santa Maria
2015
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| _version_ | 1876456773797281792 |
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| author | Minoo Soltanshahi |
| author_facet | Minoo Soltanshahi |
| contents | A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms Minoo Soltanshahi Aliakbar Niknafs Estudios Ambientales deadline cost constraint fault tolerance balanced loading Scheduling algorithm Cloud computing is the latest distributed technology providing a rich environment of dynamically shared resources through virtualization, w hich can fulfill the requirements of users by allocating resources to programs. Any program in a cloud environment is delivered by workflows which are a series of interlinked tasks to accomplish a goal. One of the most important tasks in cloud computing is correct mapping of tasks onto resources. It is essential to schedule processes in distributed systems such as cloud, since it leaves a tremendous impact on the system performance. This is done by scheduling algorithms. Therefore, it is crucial to present and adopt an efficient algorithm in the cloud environment. This article attempted to examine the parameters effective in the efficiency of scheduling algorith ms including deadline, cost constraint, balanced loading, power consumption and fault tolerance. A dditionally, the performances of several algorithms were briefly discussed. 2015 artículo científico 0100-8307 https://www.redalyc.org/articulo.oa?id=467547683055 en http://www.redalyc.org/revista.oa?id=4675 Ciência e Natura application/pdf Universidade Federal de Santa Maria Ciência e Natura (Brasil) Num.6-2 Vol.37 |
| format | Artículo científico |
| id | redalyc_467547683055 |
| institution | Redalyc |
| language | en |
| publishDate | 2015 |
| publisher | Universidade Federal de Santa Maria |
| spellingShingle | A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms Minoo Soltanshahi Estudios Ambientales deadline cost constraint fault tolerance balanced loading Scheduling algorithm A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms Minoo Soltanshahi Aliakbar Niknafs Estudios Ambientales deadline cost constraint fault tolerance balanced loading Scheduling algorithm Cloud computing is the latest distributed technology providing a rich environment of dynamically shared resources through virtualization, w hich can fulfill the requirements of users by allocating resources to programs. Any program in a cloud environment is delivered by workflows which are a series of interlinked tasks to accomplish a goal. One of the most important tasks in cloud computing is correct mapping of tasks onto resources. It is essential to schedule processes in distributed systems such as cloud, since it leaves a tremendous impact on the system performance. This is done by scheduling algorithms. Therefore, it is crucial to present and adopt an efficient algorithm in the cloud environment. This article attempted to examine the parameters effective in the efficiency of scheduling algorith ms including deadline, cost constraint, balanced loading, power consumption and fault tolerance. A dditionally, the performances of several algorithms were briefly discussed. 2015 artículo científico 0100-8307 https://www.redalyc.org/articulo.oa?id=467547683055 en http://www.redalyc.org/revista.oa?id=4675 Ciência e Natura application/pdf Universidade Federal de Santa Maria Ciência e Natura (Brasil) Num.6-2 Vol.37 |
| title | A Study on Factors Contributing to Efficiency of Scheduling Algorithms in a Cloud Computing Environment; Overview of Several Algorithms |
| topic | Estudios Ambientales deadline cost constraint fault tolerance balanced loading Scheduling algorithm |
| url | https://www.redalyc.org/articulo.oa?id=467547683055 |