Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm
Effective workflow scheduling in cloud computing is still a challenging problem as incoming workflows to cloud console having variable task processing capacities and dependencies as they will arise from various heterogeneous resources. Ineffective scheduling of workflows to virtual resources in clou...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
|
| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2023/4350615 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832546607088795648 |
|---|---|
| author | Babuli Sahu Sangram Keshari Swain Sudheer Mangalampalli Satyasis Mishra |
| author_facet | Babuli Sahu Sangram Keshari Swain Sudheer Mangalampalli Satyasis Mishra |
| author_sort | Babuli Sahu |
| collection | DOAJ |
| description | Effective workflow scheduling in cloud computing is still a challenging problem as incoming workflows to cloud console having variable task processing capacities and dependencies as they will arise from various heterogeneous resources. Ineffective scheduling of workflows to virtual resources in cloud environment leads to violations in service level agreements and high energy consumption, which impacts the quality of service of cloud provider. Many existing authors developed workflow scheduling algorithms addressing operational costs and makespan, but still, there is a provision to improve the scheduling process in cloud paradigm as it is an nondeterministic polynomial-hard problem. Therefore, in this research, a task-prioritized multiobjective workflow scheduling algorithm was developed by using cuckoo search algorithm to precisely map incoming workflows onto corresponding virtual resources. Extensive simulations were carried out on workflowsim using randomly generated workflows from simulator. For evaluating the efficacy of our proposed approach, we compared our proposed scheduling algorithm with existing approaches, i.e., Max–Min, first come first serve, minimum completion time, Min–Min, resource allocation security with efficient task scheduling in cloud computing-hybrid machine learning, and Round Robin. Our proposed approach is outperformed by minimizing energy consumption by 15% and reducing service level agreement violations by 22%. |
| format | Article |
| id | doaj-art-7fc4ff701293460ba42cc7dabdc38c23 |
| institution | Kabale University |
| issn | 1754-2103 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-7fc4ff701293460ba42cc7dabdc38c232025-02-03T06:47:43ZengWileyApplied Bionics and Biomechanics1754-21032023-01-01202310.1155/2023/4350615Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search AlgorithmBabuli Sahu0Sangram Keshari Swain1Sudheer Mangalampalli2Satyasis Mishra3Department of CSEDepartment of CSESchool of Computer Science and EngineeringAdama Science and Technology UniversityEffective workflow scheduling in cloud computing is still a challenging problem as incoming workflows to cloud console having variable task processing capacities and dependencies as they will arise from various heterogeneous resources. Ineffective scheduling of workflows to virtual resources in cloud environment leads to violations in service level agreements and high energy consumption, which impacts the quality of service of cloud provider. Many existing authors developed workflow scheduling algorithms addressing operational costs and makespan, but still, there is a provision to improve the scheduling process in cloud paradigm as it is an nondeterministic polynomial-hard problem. Therefore, in this research, a task-prioritized multiobjective workflow scheduling algorithm was developed by using cuckoo search algorithm to precisely map incoming workflows onto corresponding virtual resources. Extensive simulations were carried out on workflowsim using randomly generated workflows from simulator. For evaluating the efficacy of our proposed approach, we compared our proposed scheduling algorithm with existing approaches, i.e., Max–Min, first come first serve, minimum completion time, Min–Min, resource allocation security with efficient task scheduling in cloud computing-hybrid machine learning, and Round Robin. Our proposed approach is outperformed by minimizing energy consumption by 15% and reducing service level agreement violations by 22%.http://dx.doi.org/10.1155/2023/4350615 |
| spellingShingle | Babuli Sahu Sangram Keshari Swain Sudheer Mangalampalli Satyasis Mishra Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm Applied Bionics and Biomechanics |
| title | Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm |
| title_full | Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm |
| title_fullStr | Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm |
| title_full_unstemmed | Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm |
| title_short | Multiobjective Prioritized Workflow Scheduling in Cloud Computing Using Cuckoo Search Algorithm |
| title_sort | multiobjective prioritized workflow scheduling in cloud computing using cuckoo search algorithm |
| url | http://dx.doi.org/10.1155/2023/4350615 |
| work_keys_str_mv | AT babulisahu multiobjectiveprioritizedworkflowschedulingincloudcomputingusingcuckoosearchalgorithm AT sangramkeshariswain multiobjectiveprioritizedworkflowschedulingincloudcomputingusingcuckoosearchalgorithm AT sudheermangalampalli multiobjectiveprioritizedworkflowschedulingincloudcomputingusingcuckoosearchalgorithm AT satyasismishra multiobjectiveprioritizedworkflowschedulingincloudcomputingusingcuckoosearchalgorithm |