Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm
Applications for the internet of things (IoT) have grown significantly in popularity in recent years, and this has caused a huge increase in the use of cloud services (CSs). In addition, cloud computing (CC) efficiently processes and stores generated application data, which is evident in the lengthe...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2024-01-01
|
| Series: | AIMS Mathematics |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.2024043https://www.aimspress.com/article/doi/10.3934/math.2024043 |
| _version_ | 1797360116492664832 |
|---|---|
| author | Ibrahim Attiya Mohammed A. A. Al-qaness Mohamed Abd Elaziz Ahmad O. Aseeri |
| author_facet | Ibrahim Attiya Mohammed A. A. Al-qaness Mohamed Abd Elaziz Ahmad O. Aseeri |
| author_sort | Ibrahim Attiya |
| collection | DOAJ |
| description | Applications for the internet of things (IoT) have grown significantly in popularity in recent years, and this has caused a huge increase in the use of cloud services (CSs). In addition, cloud computing (CC) efficiently processes and stores generated application data, which is evident in the lengthened response times of sensitive applications. Moreover, CC bandwidth limitations and power consumption are still unresolved issues. In order to balance CC, fog computing (FC) has been developed. FC broadens its offering of CSs to target end users and edge devices. Due to its low processing capability, FC only handles light activities; jobs that require more time will be done via CC. This study presents an alternative task scheduling in an IoT environment based on improving the performance of the golden jackal optimization (GJO) using the artificial hummingbird algorithm (AHA). To test the effectiveness of the developed task scheduling technique named golden jackal artificial hummingbird (GJAH), we conducted a large number of experiments on two separate datasets with varying data sizing. The GJAH algorithm provides better performance than those competitive task scheduling methods. In particular, GJAH can schedule and carry out activities more effectively than other algorithms to reduce the makespan time and energy consumption in a cloud-fog computing environment. |
| first_indexed | 2024-03-08T15:34:43Z |
| format | Article |
| id | doaj.art-8e50060877694daba3fd8608989737cd |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-03-08T15:34:43Z |
| publishDate | 2024-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-8e50060877694daba3fd8608989737cd2024-01-10T01:29:31ZengAIMS PressAIMS Mathematics2473-69882024-01-019184786710.3934/math.2024043Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithmIbrahim Attiya0Mohammed A. A. Al-qaness1Mohamed Abd Elaziz2Ahmad O. Aseeri31. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt 2. Faculty of Computer Science and Engineering, New Mansoura University, New Mansoura, Egypt3. College of Physics and Electronic Information Engineering, Zhejiang Normal University, Jinhua 321004, China 4. Zhejiang Optoelectronics Research Institute, Jinhua 321004, China1. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt5. Artificial Intelligence Research Center (AIRC), Ajman University, Ajman 346, United Arab Emirates 6. MEU Research Unit, Middle East University, Amman 11831, Jordan 7. Department of Electrical and Computer Engineering, Lebanese American University, Byblos 13-5053, Lebanon8. Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi ArabiaApplications for the internet of things (IoT) have grown significantly in popularity in recent years, and this has caused a huge increase in the use of cloud services (CSs). In addition, cloud computing (CC) efficiently processes and stores generated application data, which is evident in the lengthened response times of sensitive applications. Moreover, CC bandwidth limitations and power consumption are still unresolved issues. In order to balance CC, fog computing (FC) has been developed. FC broadens its offering of CSs to target end users and edge devices. Due to its low processing capability, FC only handles light activities; jobs that require more time will be done via CC. This study presents an alternative task scheduling in an IoT environment based on improving the performance of the golden jackal optimization (GJO) using the artificial hummingbird algorithm (AHA). To test the effectiveness of the developed task scheduling technique named golden jackal artificial hummingbird (GJAH), we conducted a large number of experiments on two separate datasets with varying data sizing. The GJAH algorithm provides better performance than those competitive task scheduling methods. In particular, GJAH can schedule and carry out activities more effectively than other algorithms to reduce the makespan time and energy consumption in a cloud-fog computing environment.https://www.aimspress.com/article/doi/10.3934/math.2024043https://www.aimspress.com/article/doi/10.3934/math.2024043internet of things (iot)golden jackal optimization (gjo)artificial hummingbird algorithm (aha)energy consumptioncloud computing |
| spellingShingle | Ibrahim Attiya Mohammed A. A. Al-qaness Mohamed Abd Elaziz Ahmad O. Aseeri Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm AIMS Mathematics internet of things (iot) golden jackal optimization (gjo) artificial hummingbird algorithm (aha) energy consumption cloud computing |
| title | Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm |
| title_full | Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm |
| title_fullStr | Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm |
| title_full_unstemmed | Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm |
| title_short | Boosting task scheduling in IoT environments using an improved golden jackal optimization and artificial hummingbird algorithm |
| title_sort | boosting task scheduling in iot environments using an improved golden jackal optimization and artificial hummingbird algorithm |
| topic | internet of things (iot) golden jackal optimization (gjo) artificial hummingbird algorithm (aha) energy consumption cloud computing |
| url | https://www.aimspress.com/article/doi/10.3934/math.2024043https://www.aimspress.com/article/doi/10.3934/math.2024043 |
| work_keys_str_mv | AT ibrahimattiya boostingtaskschedulinginiotenvironmentsusinganimprovedgoldenjackaloptimizationandartificialhummingbirdalgorithm AT mohammedaaalqaness boostingtaskschedulinginiotenvironmentsusinganimprovedgoldenjackaloptimizationandartificialhummingbirdalgorithm AT mohamedabdelaziz boostingtaskschedulinginiotenvironmentsusinganimprovedgoldenjackaloptimizationandartificialhummingbirdalgorithm AT ahmadoaseeri boostingtaskschedulinginiotenvironmentsusinganimprovedgoldenjackaloptimizationandartificialhummingbirdalgorithm |