Review Article

A Survey on Vehicular Edge Computing: Architecture, Applications, Technical Issues, and Future Directions

Table 3

VEC technical issues categorization I.

IssuesReferenceYearContributions

Latency RoutingLu. et. al. [64]2018Proposed a routing scheme (IGR) for the vehicles moving in a city environment.
Prasanth et. al. [65]2009Presented EBGR, which augments the packet behavior for the network whose mobility is high and to enhance the reliability of the delivered messages.
SDNTruong et. al. [25]2015Authors presented FSDN, which integrates SDN and Edge computing by considering various factors, e.g., physical medium, mobility, and capability.
Deng et. al. [67]2017Authors revealed an entire series of latency control mechanisms, from radio access steering to processing the caches at base stations.
Tomovic et. al. [66]2017Presented a model for IoT, which backs real-time data mobility and scalability.
5GGe et. al. [68]2017A multihop approach is adopted for the vehicular communication within the fog cell.
Khan et. al. [69]2018A 5G-VANET model with the integration of SDN, Cloud-RAN, and edge computing technologies is designed. This model provided better throughput and minimized delay.
Tao et. al. [70]20175G technologies are used to overcome the issue of extreme growth of the vehicular terminals and mobile data traffic.

Scheduling & Load balancingChen et. al. [71]2017Proposed a scheduling scheme established on queue length and response time. They also formulated a design for a vehicular cloud, based on a compositional approach (PEPA).
Lai et. al. [72]2018The PV system supports a heuristic insertion algorithm and a cooperative strategy between vehicle nodes, edge, and the cloud for sending requests as well as schedules routes for PVs.
Park et. al. [73]2017Proposed scheduling algorithm to recover the lost connection and continue the services in case of an edge server failure.
He et. al. [76]2016Presented an SDN based (MPSO-CO) centralized load balancing algorithm. This optimized the workload between the edge/fog networks so the latency can be efficiently minimized.

OffloadingZhang et. al. [77]2017Presented a computational offloading infrastructure, which stresses upon the computational effectiveness of the transfer frameworks of V2I and V2V modes of communication.
Saqib et. al. [78]2016Introduced a model for computation offloading as FogR. It could respond to any emergency with greater reliability in case of fog node failure.
Bi et. al. [79]2017Presented CVFH scheme in which, before entering the coverage area of the target AP, a vehicle takes relevant information from the qualified vehicle through its neighboring vehicle.

Resource ManagementMiao et. al. [82]2016Proposed an FLRM scheme, which determines each resource’s survival time by using the collected information with the help of fuzzy logic, which is based on popularity evaluation algorithm.
Li et. al. [83]2017They addressed the local resource management in the FeRAN. To support this, FRR and FRL schemes were introduced. The on-hop probability for real-time vehicular services is enhanced.
Brennand et. al. [84]2016Proposed FOX, which detects and manages traffic congestion in VANETS. Through this, the time of the trip, emission, and fuel consumption could also be reduced.

Security & PrivacyBasudan et. al. [85]2017Introduced CLASC, a privacy preserving protocol, which aims at improving security in a crowd-sensing based road condition monitoring system.
Fan et. al. [90]2018Proposed a data-sharing scheme, which analyzes a multiauthority CP-ABE by effective decryption, while protecting a CP-ABE system safe against the collusion attack.
Soleymani et. al. [91]2017Proposed a fuzzy trust model, which detects the defective nodes and unauthorized attackers and handles the uncertainty of data in the vehicular networks.
Huang et. al. [92]2017Analyzed DREAMS where edge server executes local management tasks by ensuring a trusted reputation. It optimizes resource allocation and detects and enhances the recognition rate of misbehaving vehicles.
Huang et. al. [94]2017Proposed Meet-Fog to accurately distribute negative messages such as CRL in VANET.
Alrawais et. al. [95]2018Presented a revocation architecture, which increases the effectiveness of the certificate status by using Edge and Merkle hash tree.