Distributed system for time-sensitive applications with multiple execution options (MEO)

Cloud Computing is enabling the consolidation of millions of applications on shared infrastructures due to its wide application. So many applications share common resources, making it increasingly difficult to meet their quality of service (QoS) needs. Aside from that, the characteristics and worklo...

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Main Author: Lim, Jia En
Other Authors: Arvind Easwaran
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/162842
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1628422022-11-11T01:02:38Z Distributed system for time-sensitive applications with multiple execution options (MEO) Lim, Jia En Arvind Easwaran School of Computer Science and Engineering arvinde@ntu.edu.sg Engineering::Computer science and engineering::Computer systems organization::Computer system implementation Cloud Computing is enabling the consolidation of millions of applications on shared infrastructures due to its wide application. So many applications share common resources, making it increasingly difficult to meet their quality of service (QoS) needs. Aside from that, the characteristics and workload of different applications change over time, which further complicates the system. As part of this study, two online QoS aware adaptive task allocation schemes are developed and compared to demonstrate that the experimental system can exploit a variety of online QoS aware adaptive task allocation schemes. They are mainly, ‘Opportunistic Load Balancing’ and ‘Shortest Job First’ Virtual Machine (VM) Provisioning Scheme. They are allocation-driven algorithms that send jobs to subsystems that provide lower response times. After that, the algorithm divides the stream of job arrivals into sub-streams. The aim of these schemes is to achieve higher resource utilization and system benefits by carefully balancing resource usage efficiency, input workloads, & request deadlines. Bachelor of Engineering (Computer Science) 2022-11-11T01:02:38Z 2022-11-11T01:02:38Z 2022 Final Year Project (FYP) Lim, J. E. (2022). Distributed system for time-sensitive applications with multiple execution options (MEO). Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162842 https://hdl.handle.net/10356/162842 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 Engineering::Computer science and engineering::Computer systems organization::Computer system implementation
spellingShingle Engineering::Computer science and engineering::Computer systems organization::Computer system implementation
Lim, Jia En
Distributed system for time-sensitive applications with multiple execution options (MEO)
description Cloud Computing is enabling the consolidation of millions of applications on shared infrastructures due to its wide application. So many applications share common resources, making it increasingly difficult to meet their quality of service (QoS) needs. Aside from that, the characteristics and workload of different applications change over time, which further complicates the system. As part of this study, two online QoS aware adaptive task allocation schemes are developed and compared to demonstrate that the experimental system can exploit a variety of online QoS aware adaptive task allocation schemes. They are mainly, ‘Opportunistic Load Balancing’ and ‘Shortest Job First’ Virtual Machine (VM) Provisioning Scheme. They are allocation-driven algorithms that send jobs to subsystems that provide lower response times. After that, the algorithm divides the stream of job arrivals into sub-streams. The aim of these schemes is to achieve higher resource utilization and system benefits by carefully balancing resource usage efficiency, input workloads, & request deadlines.
author2 Arvind Easwaran
author_facet Arvind Easwaran
Lim, Jia En
format Final Year Project
author Lim, Jia En
author_sort Lim, Jia En
title Distributed system for time-sensitive applications with multiple execution options (MEO)
title_short Distributed system for time-sensitive applications with multiple execution options (MEO)
title_full Distributed system for time-sensitive applications with multiple execution options (MEO)
title_fullStr Distributed system for time-sensitive applications with multiple execution options (MEO)
title_full_unstemmed Distributed system for time-sensitive applications with multiple execution options (MEO)
title_sort distributed system for time-sensitive applications with multiple execution options (meo)
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/162842
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