Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA
Dynamic and flexible computing resources are offered by cloud computing (CC), which has gained popularity as a computing technology. Efficient task scheduling (TS) plays a critical role in CC by optimizing the distribution of tasks across available resources to achieve maximum performance. The alloc...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10304139/ |
| _version_ | 1797633984705855488 |
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| author | S. V. Aswin Kumer N. Prabakaran E. Mohan Balaji Natarajan G. Sambasivam Vaibhav Bhushan Tyagi |
| author_facet | S. V. Aswin Kumer N. Prabakaran E. Mohan Balaji Natarajan G. Sambasivam Vaibhav Bhushan Tyagi |
| author_sort | S. V. Aswin Kumer |
| collection | DOAJ |
| description | Dynamic and flexible computing resources are offered by cloud computing (CC), which has gained popularity as a computing technology. Efficient task scheduling (TS) plays a critical role in CC by optimizing the distribution of tasks across available resources to achieve maximum performance. The allocation of computational tasks in a cloud environment is a complicated process that is affected by multiple factors, such as available network bandwidth, make span, and cost considerations. Therefore, it is crucial to optimize available bandwidth for efficient TS in CC. In the present research, a novel pelican-based approach is introduced to optimize TS in the CC environment. The newly developed method also utilizes a security approach called Polymorphic Advanced Encryption Standard (P-AES) to encode cloud information during scheduling. The study evaluates the proposed algorithm’s performance in terms of the make span, resource utilization, cost, response time, throughput, latency, execution time, speed, and bandwidth utilization. The simulation is carried out using the Python tool, and it effectively handles a wide range of tasks from 1000 to 5000. The proposed algorithm offers a new perspective on utilizing pelican algorithms to optimize task scheduling in CC. The hybrid optimization enables the proposed algorithm to provide efficient task scheduling by exploiting the strengths of entire algorithms. The proposed approach offers an innovative solution to the challenges of scheduling tasks in cloud environments and provides a more effective and secure way of optimizing cloud services. Overall, this study provides valuable insights into task scheduling optimization in CC and offers an effective approach for enhancing the performance of CC services. |
| first_indexed | 2024-03-11T12:02:23Z |
| format | Article |
| id | doaj.art-2529c8a2713e40ac83431f88d8589190 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T12:02:23Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2529c8a2713e40ac83431f88d85891902023-11-08T00:00:44ZengIEEEIEEE Access2169-35362023-01-011112242612244510.1109/ACCESS.2023.332905210304139Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POAS. V. Aswin Kumer0https://orcid.org/0000-0002-0511-3085N. Prabakaran1E. Mohan2Balaji Natarajan3https://orcid.org/0000-0003-0040-9271G. Sambasivam4https://orcid.org/0000-0002-7407-4796Vaibhav Bhushan Tyagi5https://orcid.org/0000-0001-8153-3607Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, IndiaDepartment of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Vaddeswaram, Andhra Pradesh, IndiaDepartment of ECE, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, IndiaDepartment of Computer Science and Engineering, Sri Venkateshwaraa College of Engineering and Technology, Ariyur, Puducherry, IndiaSchool of Computing and Data Science, Xiamen University Malaysia, Sepang, Selangor Darul Ehsan, MalaysiaFaculty of Engineering, ISBAT University, Kampala, UgandaDynamic and flexible computing resources are offered by cloud computing (CC), which has gained popularity as a computing technology. Efficient task scheduling (TS) plays a critical role in CC by optimizing the distribution of tasks across available resources to achieve maximum performance. The allocation of computational tasks in a cloud environment is a complicated process that is affected by multiple factors, such as available network bandwidth, make span, and cost considerations. Therefore, it is crucial to optimize available bandwidth for efficient TS in CC. In the present research, a novel pelican-based approach is introduced to optimize TS in the CC environment. The newly developed method also utilizes a security approach called Polymorphic Advanced Encryption Standard (P-AES) to encode cloud information during scheduling. The study evaluates the proposed algorithm’s performance in terms of the make span, resource utilization, cost, response time, throughput, latency, execution time, speed, and bandwidth utilization. The simulation is carried out using the Python tool, and it effectively handles a wide range of tasks from 1000 to 5000. The proposed algorithm offers a new perspective on utilizing pelican algorithms to optimize task scheduling in CC. The hybrid optimization enables the proposed algorithm to provide efficient task scheduling by exploiting the strengths of entire algorithms. The proposed approach offers an innovative solution to the challenges of scheduling tasks in cloud environments and provides a more effective and secure way of optimizing cloud services. Overall, this study provides valuable insights into task scheduling optimization in CC and offers an effective approach for enhancing the performance of CC services.https://ieeexplore.ieee.org/document/10304139/Advanced encryption standardchameleon swarm algorithmcloud computinghybrid modelsecuritymoth swarm algorithm |
| spellingShingle | S. V. Aswin Kumer N. Prabakaran E. Mohan Balaji Natarajan G. Sambasivam Vaibhav Bhushan Tyagi Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA IEEE Access Advanced encryption standard chameleon swarm algorithm cloud computing hybrid model security moth swarm algorithm |
| title | Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA |
| title_full | Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA |
| title_fullStr | Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA |
| title_full_unstemmed | Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA |
| title_short | Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA |
| title_sort | enhancing cloud task scheduling with a robust security approach and optimized hybrid poa |
| topic | Advanced encryption standard chameleon swarm algorithm cloud computing hybrid model security moth swarm algorithm |
| url | https://ieeexplore.ieee.org/document/10304139/ |
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