TY - JOUR
T1 - A survey on vehicular task offloading
T2 - Classification, issues, and challenges
AU - Ahmed, Manzoor
AU - Raza, Salman
AU - Mirza, Muhammad Ayzed
AU - Aziz, Abdul
AU - Khan, Manzoor Ahmed
AU - Khan, Wali Ullah
AU - Li, Jianbo
AU - Han, Zhu
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - 802.11bd
KW - Cloudlet
KW - Edge
KW - NR V2X
KW - Vehicular task offloading
KW - cloud
UR - http://www.scopus.com/inward/record.url?scp=85132434614&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85132434614&partnerID=8YFLogxK
U2 - 10.1016/j.jksuci.2022.05.016
DO - 10.1016/j.jksuci.2022.05.016
M3 - Review article
AN - SCOPUS:85132434614
SN - 1319-1578
VL - 34
SP - 4135
EP - 4162
JO - Journal of King Saud University - Computer and Information Sciences
JF - Journal of King Saud University - Computer and Information Sciences
IS - 7
ER -