Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view
As a promising platform on the Internet of Things (IoT), the smart Internet of Vehicle (IoV) has emerged with the advent of the key connectivity to Industry 4.0, i.e. Fifth-Generation Mobile Communication (5G). However, problems with adequate battery life, powerful computing, and energy economy have...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier B.V.
2024
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/115580/ http://psasir.upm.edu.my/id/eprint/115580/1/115580.pdf |
| _version_ | 1848866815141216256 |
|---|---|
| author | Talebkhah, Marieh Sali, Aduwati Khodamoradi, Vahid Khodadadi, Touraj Gordan, Meisam |
| author_facet | Talebkhah, Marieh Sali, Aduwati Khodamoradi, Vahid Khodadadi, Touraj Gordan, Meisam |
| author_sort | Talebkhah, Marieh |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | As a promising platform on the Internet of Things (IoT), the smart Internet of Vehicle (IoV) has emerged with the advent of the key connectivity to Industry 4.0, i.e. Fifth-Generation Mobile Communication (5G). However, problems with adequate battery life, powerful computing, and energy economy have hampered the development of this technology in light of the enormous increase in data traffic in 5G and 6G mobile communication networks. To address these limitations, this study proposes an Internet of Vehicles (IoV) system empowered by Edge Computing (EC), wherein intelligent vehicle nodes interact with an anchor node integrated with an EC server for data upload and download. Rather than solely focusing on enhancing the central cloud infrastructure, the integration of EC and IoT enables real-time and efficient services, thereby bolstering the storage and processing capabilities of underlying networks. By employing an offloading strategy within the Edge Computing-based Internet of Vehicles (EC-IoV) framework, users can allocate their workloads to suitable EC servers, leading to improved resource management and computational capabilities. However, challenges persist in evaluating the impact of uncertain user-EC server connectivity on offloading decision-making and mitigating potential declines in offloading efficiency. |
| first_indexed | 2025-11-15T14:26:36Z |
| format | Article |
| id | upm-115580 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:26:36Z |
| publishDate | 2024 |
| publisher | Elsevier B.V. |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1155802025-03-07T01:38:56Z http://psasir.upm.edu.my/id/eprint/115580/ Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view Talebkhah, Marieh Sali, Aduwati Khodamoradi, Vahid Khodadadi, Touraj Gordan, Meisam As a promising platform on the Internet of Things (IoT), the smart Internet of Vehicle (IoV) has emerged with the advent of the key connectivity to Industry 4.0, i.e. Fifth-Generation Mobile Communication (5G). However, problems with adequate battery life, powerful computing, and energy economy have hampered the development of this technology in light of the enormous increase in data traffic in 5G and 6G mobile communication networks. To address these limitations, this study proposes an Internet of Vehicles (IoV) system empowered by Edge Computing (EC), wherein intelligent vehicle nodes interact with an anchor node integrated with an EC server for data upload and download. Rather than solely focusing on enhancing the central cloud infrastructure, the integration of EC and IoT enables real-time and efficient services, thereby bolstering the storage and processing capabilities of underlying networks. By employing an offloading strategy within the Edge Computing-based Internet of Vehicles (EC-IoV) framework, users can allocate their workloads to suitable EC servers, leading to improved resource management and computational capabilities. However, challenges persist in evaluating the impact of uncertain user-EC server connectivity on offloading decision-making and mitigating potential declines in offloading efficiency. Elsevier B.V. 2024 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/115580/1/115580.pdf Talebkhah, Marieh and Sali, Aduwati and Khodamoradi, Vahid and Khodadadi, Touraj and Gordan, Meisam (2024) Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view. Engineering Science and Technology, an International Journal, 54. art. no. 101699. pp. 1-40. ISSN 2215-0986; eISSN: 2215-0986 https://linkinghub.elsevier.com/retrieve/pii/S2215098624000855 10.1016/j.jestch.2024.101699 |
| spellingShingle | Talebkhah, Marieh Sali, Aduwati Khodamoradi, Vahid Khodadadi, Touraj Gordan, Meisam Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view |
| title | Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view |
| title_full | Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view |
| title_fullStr | Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view |
| title_full_unstemmed | Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view |
| title_short | Task offloading for edge-IoV networks in the industry 4.0 era and beyond: a high-level view |
| title_sort | task offloading for edge-iov networks in the industry 4.0 era and beyond: a high-level view |
| url | http://psasir.upm.edu.my/id/eprint/115580/ http://psasir.upm.edu.my/id/eprint/115580/ http://psasir.upm.edu.my/id/eprint/115580/ http://psasir.upm.edu.my/id/eprint/115580/1/115580.pdf |