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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Main Author: Juan Samuel Sugianto
Other Authors: Lee Bu Sung, Francis
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175614
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Institution: Nanyang Technological University
Language: English
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spelling 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
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
spellingShingle Computer and Information Science
Juan Samuel Sugianto
Evaluating job scheduling algorithm in clouds
description 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.
author2 Lee Bu Sung, Francis
author_facet Lee Bu Sung, Francis
Juan Samuel Sugianto
format Final Year Project
author Juan Samuel Sugianto
author_sort Juan Samuel Sugianto
title Evaluating job scheduling algorithm in clouds
title_short Evaluating job scheduling algorithm in clouds
title_full Evaluating job scheduling algorithm in clouds
title_fullStr Evaluating job scheduling algorithm in clouds
title_full_unstemmed Evaluating job scheduling algorithm in clouds
title_sort evaluating job scheduling algorithm in clouds
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175614
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