Please use this identifier to cite or link to this item:
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16113
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DC Field | Value | Language |
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dc.contributor.author | Singh, Akshiti | - |
dc.contributor.author | Ganguly, Sagnik | - |
dc.contributor.author | Peesapati, Pavan Seshu V V | - |
dc.contributor.author | Jayavadivel, R | - |
dc.date.accessioned | 2024-07-22T03:50:51Z | - |
dc.date.available | 2024-07-22T03:50:51Z | - |
dc.date.issued | 2024-05-01 | - |
dc.identifier.citation | 80p. | en_US |
dc.identifier.uri | https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16113 | - |
dc.description.abstract | Task scheduling on cloud computing platform.. is crucial for ripaimiting resource utilization and maximizing the performance of application. and workloads. In this abstract. we explore the challenges and strategies involved in achieving optimal resource utilization through effective task scheduling on cloud computing environments. The shared nature of cloud infrastructure introduces complexities in resource allocation and management. requiring sophisticated scheduling algorithms and optimization techniques to balance competing object is es such as minimizing task completion limes, maximizing resource utilization. and ensuring fairness among user. One of the prominent algorithms used for task scheduling in cloud computing is the Heterogeneous Earliest Finish Time WEFT/ algorithm. which aims to minimize task conviction time by exploiting task dependencies and heterogeneity in resource capabilities. By considering task execution times. data transfer costs, and resource availability. HEFT makes informed scheduling decisions that optimize resource allocation and minimize overall task completion time. To achieve optimal resource utilization, organizations must also consider factors such as workload characteristics. resource availability. network latency, and system constraints when designing task scheduling algorithms and strategies. Furthermore, the integration of containerization platforms and distributed tile systems enables efficient deployment and management of task scheduling applications. reducing overhead and improving scalability. Overall. effective task scheduling on cloud computing platforms requires a holistic approach that considers the interplay between workload characteristics. system dynamics. scheduling algorithms. and optimization techniques to achieve optimal resource utilization and maximize the performance of cloud•based applications and workloads. By leveraging advanced scheduling algorithms. simulation frameworks, and cloud management tools. organizations can design and deploy efficient task scheduling systems that meet the demands of modem cloud computing environments. resulting in improved efficiency. scalability. and cost-effectiveness. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Alliance College of Engineering and Design, Alliance University | en_US |
dc.relation.ispartofseries | CSE_G03_2024 [19030141CSE050; 19030141CSE092; L19030141CSE100] | - |
dc.subject | Cloud Computing | en_US |
dc.subject | Computer Science | en_US |
dc.title | Task Scheduling On Cloud Computing to Achieve Optical Resource Utilization | en_US |
dc.type | Other | en_US |
Appears in Collections: | Dissertations - Alliance College of Engineering & Design |
Files in This Item:
File | Size | Format | |
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CSE_G03_2024.pdf Restricted Access | 5.84 MB | Adobe PDF | View/Open Request a copy |
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