An optimal tasks scheduling algorithm based on QoS in cloud computing network
Cloud Computing has emerged as a service model that offers online accessible resources to the clients. These resources contain storage, servers, and other applications and it provides security, flexibility, and sealability. In Max-Min algorithm where the large tasks have their priority to be schedul...
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| 格式: | Thesis |
| 语言: | English |
| 出版: |
2017
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| 在线阅读: | http://psasir.upm.edu.my/id/eprint/91947/1/FSKTM%202018%2036%20IR.pdf |
| _version_ | 1825937122532524032 |
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| author | Alhakimi, Mohammed Ameen Mohammed Abdo |
| author_facet | Alhakimi, Mohammed Ameen Mohammed Abdo |
| author_sort | Alhakimi, Mohammed Ameen Mohammed Abdo |
| collection | UPM |
| description | Cloud Computing has emerged as a service model that offers online accessible resources to the clients. These resources contain storage, servers, and other applications and it provides security, flexibility, and sealability. In Max-Min algorithm where the large tasks have their priority to be scheduled first, this leads small tasks to stay longer in the queue until all large length tasks finished their execution. This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. Our proposed algorithm isolates the resources into two different groups where the first group contains the resources with maximum execution time while the second group contains the resources with minimum execution time. The main idea here is to choose the resource that takes less time to execute the selected job/task. Therefore, if the resource is from the first group then map the average length task to it and if the choosing resource is from the second group, then map the largest length task to it. The simulation tool used for testing the algorithm is WorkflowSim. We tested averages of execution time span of the proposed algorithm for 10 running times with 200-1000 tasks in 50 or 100 VMs. Test results show that the proposed algorithm represents enhanced resource utilization with better execution time. |
| first_indexed | 2024-03-06T10:54:41Z |
| format | Thesis |
| id | upm.eprints-91947 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:54:41Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | upm.eprints-919472022-03-01T02:27:45Z http://psasir.upm.edu.my/id/eprint/91947/ An optimal tasks scheduling algorithm based on QoS in cloud computing network Alhakimi, Mohammed Ameen Mohammed Abdo Cloud Computing has emerged as a service model that offers online accessible resources to the clients. These resources contain storage, servers, and other applications and it provides security, flexibility, and sealability. In Max-Min algorithm where the large tasks have their priority to be scheduled first, this leads small tasks to stay longer in the queue until all large length tasks finished their execution. This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. Our proposed algorithm isolates the resources into two different groups where the first group contains the resources with maximum execution time while the second group contains the resources with minimum execution time. The main idea here is to choose the resource that takes less time to execute the selected job/task. Therefore, if the resource is from the first group then map the average length task to it and if the choosing resource is from the second group, then map the largest length task to it. The simulation tool used for testing the algorithm is WorkflowSim. We tested averages of execution time span of the proposed algorithm for 10 running times with 200-1000 tasks in 50 or 100 VMs. Test results show that the proposed algorithm represents enhanced resource utilization with better execution time. 2017 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/91947/1/FSKTM%202018%2036%20IR.pdf Alhakimi, Mohammed Ameen Mohammed Abdo (2017) An optimal tasks scheduling algorithm based on QoS in cloud computing network. Masters thesis, Universiti Putra Malaysia. Cloud computing Computer networks |
| spellingShingle | Cloud computing Computer networks Alhakimi, Mohammed Ameen Mohammed Abdo An optimal tasks scheduling algorithm based on QoS in cloud computing network |
| title | An optimal tasks scheduling algorithm based on QoS in cloud computing network |
| title_full | An optimal tasks scheduling algorithm based on QoS in cloud computing network |
| title_fullStr | An optimal tasks scheduling algorithm based on QoS in cloud computing network |
| title_full_unstemmed | An optimal tasks scheduling algorithm based on QoS in cloud computing network |
| title_short | An optimal tasks scheduling algorithm based on QoS in cloud computing network |
| title_sort | optimal tasks scheduling algorithm based on qos in cloud computing network |
| topic | Cloud computing Computer networks |
| url | http://psasir.upm.edu.my/id/eprint/91947/1/FSKTM%202018%2036%20IR.pdf |
| work_keys_str_mv | AT alhakimimohammedameenmohammedabdo anoptimaltasksschedulingalgorithmbasedonqosincloudcomputingnetwork AT alhakimimohammedameenmohammedabdo optimaltasksschedulingalgorithmbasedonqosincloudcomputingnetwork |