Evaluating job scheduling algorithm in clouds
In the past decade, Cloud computing has revolutionized the technological landscape, with Amazon's cloud services boasting millions of active users globally, highlighting its pivotal role in modern business operations. Thus, efficient resource allocation algorithms are needed in optimizing cloud...
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1756142024-05-03T15:38:39Z Evaluating job scheduling algorithm in clouds Juan Samuel Sugianto Lee Bu Sung, Francis Tang Xueyan School of Computer Science and Engineering ASXYTang@ntu.edu.sg, EBSLEE@ntu.edu.sg Computer and Information Science In the past decade, Cloud computing has revolutionized the technological landscape, with Amazon's cloud services boasting millions of active users globally, highlighting its pivotal role in modern business operations. Thus, efficient resource allocation algorithms are needed in optimizing cloud performance and minimizing costs. This study delves into the practical implementation and performance evaluation of the Stratus algorithm, designed to reduce execution costs by strategically allocating jobs to suitable resources based on cloud properties and runtime estimates. By analyzing real public cloud data under various conditions and comparing Stratus with classic algorithms, this research aims to uncover potential limitations and identify inefficiencies. Bachelor's degree 2024-04-30T08:55:27Z 2024-04-30T08:55:27Z 2024 Final Year Project (FYP) Juan Samuel Sugianto (2024). Evaluating job scheduling algorithm in clouds. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175614 https://hdl.handle.net/10356/175614 en application/pdf Nanyang Technological University |
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In the past decade, Cloud computing has revolutionized the technological landscape, with Amazon's cloud services boasting millions of active users globally, highlighting its pivotal role in modern business operations. Thus, efficient resource allocation algorithms are needed in optimizing cloud performance and minimizing costs. This study delves into the practical implementation and performance evaluation of the Stratus algorithm, designed to reduce execution costs by strategically allocating jobs to suitable resources based on cloud properties and runtime estimates. By analyzing real public cloud data under various conditions and comparing Stratus with classic algorithms, this research aims to uncover potential limitations and identify inefficiencies. |
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Lee Bu Sung, Francis |
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Lee Bu Sung, Francis Juan Samuel Sugianto |
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Final Year Project |
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Juan Samuel Sugianto |
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Juan Samuel Sugianto |
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Evaluating job scheduling algorithm in clouds |
title_short |
Evaluating job scheduling algorithm in clouds |
title_full |
Evaluating job scheduling algorithm in clouds |
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Evaluating job scheduling algorithm in clouds |
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Evaluating job scheduling algorithm in clouds |
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evaluating job scheduling algorithm in clouds |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/175614 |
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