A survey on vehicular task offloading: Classification, issues, and challenges
Emerging vehicular applications with strict latency and reliability requirements pose high computing requirements, and current vehicles’ computational resources are not adequate to meet these demands. In this scenario, vehicles can get help to process tasks from other resource-rich computing platfor...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-07-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157822001653 |
| _version_ | 1811237761007484928 |
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| author | Manzoor Ahmed Salman Raza Muhammad Ayzed Mirza Abdul Aziz Manzoor Ahmed Khan Wali Ullah Khan Jianbo Li Zhu Han |
| author_facet | Manzoor Ahmed Salman Raza Muhammad Ayzed Mirza Abdul Aziz Manzoor Ahmed Khan Wali Ullah Khan Jianbo Li Zhu Han |
| author_sort | Manzoor Ahmed |
| collection | DOAJ |
| description | Emerging vehicular applications with strict latency and reliability requirements pose high computing requirements, and current vehicles’ computational resources are not adequate to meet these demands. In this scenario, vehicles can get help to process tasks from other resource-rich computing platforms, including nearby vehicles, fixed edge servers, and remote cloud servers. Nonetheless, different vehicular communication network (VCN) modes need to be utilized to access these computing resources, improving applications and networks’ performance and quality of service (QoS). In this paper, we present a comprehensive survey on the vehicular task offloading techniques under a communication perspective, i.e., vehicle to vehicle (V2V), vehicle to roadside infrastructure (V2I), and vehicle to everything (V2X). For the task/computation offloading, we present the classification of methods under the V2V, V2I, and V2X communication domains. Besides, the task/computation offloading categories are each sub-categorized according to their schemes’ objectives. Furthermore, the literature on vehicular task offloading is elaborated, compared, and analyzed from the perspectives of approaches, objectives, merits, demerits, etc. Finally, we highlight the open research challenges in this field and predict future research trends. |
| first_indexed | 2024-04-12T12:29:56Z |
| format | Article |
| id | doaj.art-9589fb7b805142878db9117962b41c67 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-12T12:29:56Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-9589fb7b805142878db9117962b41c672022-12-22T03:33:04ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782022-07-0134741354162A survey on vehicular task offloading: Classification, issues, and challengesManzoor Ahmed0Salman Raza1Muhammad Ayzed Mirza2Abdul Aziz3Manzoor Ahmed Khan4Wali Ullah Khan5Jianbo Li6Zhu Han7The College of Computer Science and Technology, Qingdao University, Qingdao 266071, China; Corresponding author.Department of Computer Science, National Textile University Faisalabad, PakistanThe BUPT-QMUL EM Theory and Application International Research Lab, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaDepartment of information and Communication Engineering, The Islamia University of Bahawalpur, Bahawalpur 63100, PakistanDepartment of Computer and Network Engineering, Collage of IT, UAE University (UAEU), Al Ain, United Arab EmiratesInterdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, 1855 Luxembourg City, Luxembourg 4365, LuxembourgThe College of Computer Science and Technology, Qingdao University, Qingdao 266071, ChinaUniversity of Houston, TX 77004, USA; Department of Computer Science and Engineering, Kyung Hee University, Seoul, South KoreaEmerging vehicular applications with strict latency and reliability requirements pose high computing requirements, and current vehicles’ computational resources are not adequate to meet these demands. In this scenario, vehicles can get help to process tasks from other resource-rich computing platforms, including nearby vehicles, fixed edge servers, and remote cloud servers. Nonetheless, different vehicular communication network (VCN) modes need to be utilized to access these computing resources, improving applications and networks’ performance and quality of service (QoS). In this paper, we present a comprehensive survey on the vehicular task offloading techniques under a communication perspective, i.e., vehicle to vehicle (V2V), vehicle to roadside infrastructure (V2I), and vehicle to everything (V2X). For the task/computation offloading, we present the classification of methods under the V2V, V2I, and V2X communication domains. Besides, the task/computation offloading categories are each sub-categorized according to their schemes’ objectives. Furthermore, the literature on vehicular task offloading is elaborated, compared, and analyzed from the perspectives of approaches, objectives, merits, demerits, etc. Finally, we highlight the open research challenges in this field and predict future research trends.http://www.sciencedirect.com/science/article/pii/S1319157822001653Vehicular task offloadingcloudEdgeCloudletNR V2X802.11bd |
| spellingShingle | Manzoor Ahmed Salman Raza Muhammad Ayzed Mirza Abdul Aziz Manzoor Ahmed Khan Wali Ullah Khan Jianbo Li Zhu Han A survey on vehicular task offloading: Classification, issues, and challenges Journal of King Saud University: Computer and Information Sciences Vehicular task offloading cloud Edge Cloudlet NR V2X 802.11bd |
| title | A survey on vehicular task offloading: Classification, issues, and challenges |
| title_full | A survey on vehicular task offloading: Classification, issues, and challenges |
| title_fullStr | A survey on vehicular task offloading: Classification, issues, and challenges |
| title_full_unstemmed | A survey on vehicular task offloading: Classification, issues, and challenges |
| title_short | A survey on vehicular task offloading: Classification, issues, and challenges |
| title_sort | survey on vehicular task offloading classification issues and challenges |
| topic | Vehicular task offloading cloud Edge Cloudlet NR V2X 802.11bd |
| url | http://www.sciencedirect.com/science/article/pii/S1319157822001653 |
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