Design and analysis of an Adaptive Workflow Scheduling Approach for QoS modeling over hybrid cloud using Bat optimization algorithm (AWSA)
Cloud computing provides tremendous infrastructure facility for the execution of multiple service workflows and commercial resource demandable applications by offering dynamic scalable, reliable and flexible computing platform. Analysis of performance execution of resource demandable services, which...
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| Veröffentlicht in: | NeuroQuantology 2022-01, Vol.20 (16), p.5056 |
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| creator | Katkam, Premnath Anbalagan, P V V S S S Balaram |
| description | Cloud computing provides tremendous infrastructure facility for the execution of multiple service workflows and commercial resource demandable applications by offering dynamic scalable, reliable and flexible computing platform. Analysis of performance execution of resource demandable services, which require optimal resources with minimum execution time with specified Quality of Service (QoS) suggests on need for design of scheduling algorithms. In this proposed work, a cost supported with energy based workflow scheduling algorithm is proposed whose performance is experimented over interactive AWSA framework whose results can be verified for metrics such as end to end delay, load balancing and throughput for variable tasks on execution using CloudSim. The performance of AWSA over end to end delay and processing time outperforms other approaches |
| doi_str_mv | 10.48047/NQ.2022.20.16.NQ880515 |
| format | Article |
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| ispartof | NeuroQuantology, 2022-01, Vol.20 (16), p.5056 |
| issn | 1303-5150 |
| language | eng |
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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Algorithms Cloud computing Computer science Energy consumption Heuristic Internet of Things Optimization Optimization algorithms Quality of service Scheduling Workflow |
| title | Design and analysis of an Adaptive Workflow Scheduling Approach for QoS modeling over hybrid cloud using Bat optimization algorithm (AWSA) |
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