Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing
Cloud computing is a distributed computing model which renders services for cloud users around the world. These services need to be rendered to customers with high availability and fault tolerance, but there are still chances of having single-point failures in the cloud paradigm, and one challenge t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/18/8009 |
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| author | Sudheer Mangalampalli Ganesh Reddy Karri Amit Gupta Tulika Chakrabarti Sri Hari Nallamala Prasun Chakrabarti Bhuvan Unhelkar Martin Margala |
| author_facet | Sudheer Mangalampalli Ganesh Reddy Karri Amit Gupta Tulika Chakrabarti Sri Hari Nallamala Prasun Chakrabarti Bhuvan Unhelkar Martin Margala |
| author_sort | Sudheer Mangalampalli |
| collection | DOAJ |
| description | Cloud computing is a distributed computing model which renders services for cloud users around the world. These services need to be rendered to customers with high availability and fault tolerance, but there are still chances of having single-point failures in the cloud paradigm, and one challenge to cloud providers is effectively scheduling tasks to avoid failures and acquire the trust of their cloud services by users. This research proposes a fault-tolerant trust-based task scheduling algorithm in which we carefully schedule tasks within precise virtual machines by calculating priorities for tasks and VMs. Harris hawks optimization was used as a methodology to design our scheduler. We used Cloudsim as a simulating tool for our entire experiment. For the entire simulation, we used synthetic fabricated data with different distributions and real-time supercomputer worklogs. Finally, we evaluated the proposed approach (FTTATS) with state-of-the-art approaches, i.e., ACO, PSO, and GA. From the simulation results, our proposed FTTATS greatly minimizes the makespan for ACO, PSO and GA algorithms by 24.3%, 33.31%, and 29.03%, respectively. The rate of failures for ACO, PSO, and GA were minimized by 65.31%, 65.4%, and 60.44%, respectively. Trust-based SLA parameters improved, i.e., availability improved for ACO, PSO, and GA by 33.38%, 35.71%, and 28.24%, respectively. The success rate improved for ACO, PSO, and GA by 52.69%, 39.41%, and 38.45%, respectively. Turnaround efficiency was minimized for ACO, PSO, and GA by 51.8%, 47.2%, and 33.6%, respectively. |
| first_indexed | 2024-03-10T22:01:04Z |
| format | Article |
| id | doaj.art-18d418fcfee646db9f0cc61b7a9b5170 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T22:01:04Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-18d418fcfee646db9f0cc61b7a9b51702023-11-19T12:57:26ZengMDPI AGSensors1424-82202023-09-012318800910.3390/s23188009Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud ComputingSudheer Mangalampalli0Ganesh Reddy Karri1Amit Gupta2Tulika Chakrabarti3Sri Hari Nallamala4Prasun Chakrabarti5Bhuvan Unhelkar6Martin Margala7School of Computer Science and Engineering, VIT-AP University, Amaravati 522237, IndiaSchool of Computer Science and Engineering, VIT-AP University, Amaravati 522237, IndiaDepartment of ECE, Nalla Malla Reddy Engineering College, Hyderabad 500088, IndiaDepartment of Chemistry, Sir Padampat Singhania University, Udaipur 313601, IndiaVasireddy Venkatadri Institute of Technology, Nambur 522510, IndiaDepartment of Computer Science and Engineering, Sir Padampat Singhania University, Udaipur 313601, IndiaMuma School of Business, University of South Florida, Sarasota-Manatee, FL 33620, USASchool of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, LA 70504, USACloud computing is a distributed computing model which renders services for cloud users around the world. These services need to be rendered to customers with high availability and fault tolerance, but there are still chances of having single-point failures in the cloud paradigm, and one challenge to cloud providers is effectively scheduling tasks to avoid failures and acquire the trust of their cloud services by users. This research proposes a fault-tolerant trust-based task scheduling algorithm in which we carefully schedule tasks within precise virtual machines by calculating priorities for tasks and VMs. Harris hawks optimization was used as a methodology to design our scheduler. We used Cloudsim as a simulating tool for our entire experiment. For the entire simulation, we used synthetic fabricated data with different distributions and real-time supercomputer worklogs. Finally, we evaluated the proposed approach (FTTATS) with state-of-the-art approaches, i.e., ACO, PSO, and GA. From the simulation results, our proposed FTTATS greatly minimizes the makespan for ACO, PSO and GA algorithms by 24.3%, 33.31%, and 29.03%, respectively. The rate of failures for ACO, PSO, and GA were minimized by 65.31%, 65.4%, and 60.44%, respectively. Trust-based SLA parameters improved, i.e., availability improved for ACO, PSO, and GA by 33.38%, 35.71%, and 28.24%, respectively. The success rate improved for ACO, PSO, and GA by 52.69%, 39.41%, and 38.45%, respectively. Turnaround efficiency was minimized for ACO, PSO, and GA by 51.8%, 47.2%, and 33.6%, respectively.https://www.mdpi.com/1424-8220/23/18/8009availabilityHarris hawks optimizationrate of failuresSLA-based trust parameterssuccess rate |
| spellingShingle | Sudheer Mangalampalli Ganesh Reddy Karri Amit Gupta Tulika Chakrabarti Sri Hari Nallamala Prasun Chakrabarti Bhuvan Unhelkar Martin Margala Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing Sensors availability Harris hawks optimization rate of failures SLA-based trust parameters success rate |
| title | Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing |
| title_full | Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing |
| title_fullStr | Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing |
| title_full_unstemmed | Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing |
| title_short | Fault-Tolerant Trust-Based Task Scheduling Algorithm Using Harris Hawks Optimization in Cloud Computing |
| title_sort | fault tolerant trust based task scheduling algorithm using harris hawks optimization in cloud computing |
| topic | availability Harris hawks optimization rate of failures SLA-based trust parameters success rate |
| url | https://www.mdpi.com/1424-8220/23/18/8009 |
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