| Type of Material: | Thesis |
| Title: | Studies On Metaheuristic Based Multi Objective Workflow Scheduling Schemes In Infrastructure As A Service IaaS Cloud |
| Researcher: | Jabir, K V T |
| Guide: | Preetha Mathew, K and David Peter, S |
| Department: | Department of Computer Science |
| Publisher: | Cochin University of Science & Technology, Cochin |
| Place: | Cochin |
| Year: | 2022 |
| Language: | English |
| Subject: | Cloud computing | Computer Science | Engineering and Technology | Metaheuristic algorithms | Optimization | Workflow scheduling | Computer Science and Information Technology | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Department of Computer Science, Cochin University of Science & Technology, Cochin, Cochin; 2022 |
| Fulltext: | Shodhganga |
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| 003 | IN-AhILN | |
| 005 | 2024-10-09 14:54:39 | |
| 008 | __ | 241009t2022||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_456364 |
| 040 | __ | |aCUST_682022|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aJabir, K V T|eResearcher |
| 110 | __ | |aDepartment of Computer Science|bCochin University of Science & Technology, Cochin|dCochin|ein|0U-0253 |
| 245 | __ | |aStudies On Metaheuristic Based Multi Objective Workflow Scheduling Schemes In Infrastructure As A Service IaaS Cloud |
| 260 | __ | |aCochin|bCochin University of Science & Technology, Cochin|c2022 |
| 300 | __ | |aix,215|dDVD |
| 502 | __ | |cDepartment of Computer Science, Cochin University of Science & Technology, Cochin, Cochin|d2022|bPhD |
| 518 | __ | |d2023|oDate of Award |
| 518 | __ | |oDate of Registration|d2017 |
| 520 | __ | |aHuge scientific problems and business applications that require extensive computing can be modeled as workflow applications. Workflows are composed of dependent computational tasks. The efficient scheduling and execution of workflows in a distributed environment is a significant research issue on account of its ever-increasing computation and data requirements. Cloud computing, the recently evolved distributed computing paradigm, offers several advantages for the deployment of workflow applications with its large scale scalable and elastic virtualized resources, which are available on demand. However, the heterogeneous and dynamic characteristics of the cloud environment and the complex structure of workflows make the scheduling of workflow tasks a challenging job. Many QoS (Quality of Service) constraints are to be addressed and also the optimal use of computing resources needs to be ensured for efficient workflow scheduling in the cloud. Hence, efficient algorithms are required for the optimised schedulin |
| 650 | __ | |aComputer Science and Information Technology|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aCloud computing |
| 653 | __ | |aComputer Science |
| 653 | __ | |aEngineering and Technology |
| 653 | __ | |aMetaheuristic algorithms |
| 653 | __ | |aOptimization |
| 653 | __ | |aWorkflow scheduling |
| 700 | __ | |eGuide|aPreetha Mathew, K and David Peter, S |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/528809|yShodhganga |
| 905 | __ | |afromsg |
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