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Kanmani, P.
- Multi-Objective Fault Tolerance Model for Scientific Workflow Scheduling on Cloud Computing
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Authors
S. Anuradha
1,
P. Kanmani
2
Affiliations
1 Department of Computer Science, Shri Sakthikailassh Women’s college, Salem, Tamil Nadux, IN
2 Department of Computer Science, Thiruvalluvar Government Arts College, Namakkal, Tamil Nadu, IN
1 Department of Computer Science, Shri Sakthikailassh Women’s college, Salem, Tamil Nadux, IN
2 Department of Computer Science, Thiruvalluvar Government Arts College, Namakkal, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 9, No 4 (2022), Pagination: 438-450Abstract
Cloud computing is used for large-scale applications. Therefore, a lot of organizations and industries are moving their data to the cloud. Nevertheless, cloud computing might have maximum failure rates because of the great number of servers and parts with a high workload. Reducing the false in scheduling is a challenging task. Hence, in this study, an efficient multi-objective fault detector strategy using an improved Squirrel Optimization Algorithm (ISOA) in cloud computing is proposed. This method can effectively reduce energy consumption, makespan, and total cost, while also tolerating errors when planning scientific workflows. To increase the detection accuracy of failures, the Active Fault Tolerance Mechanism (PFTM) is used. Similarly, the reactive fault tolerance mechanism (RFTM) is used for processor failures. The efficiency of the proposed approach is analysed based on various measurements and performance compared to other approaches.Keywords
VM Failure, Overloaded, Under Load, Squirrel Optimization Algorithm, Pro-Active Fault Tolerance, Reactive Fault Tolerance, Scheduling, Migration.Full Text
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