Efficient Modelling of Workload Arrival and Offloading for Vehicular Edge Computing

Vehicular Edge Computing (VEC) technology has become promising in meeting the increasing need for information storage and computing power in vehicular networks. Ensuring the Quality of Service (QoS) may be achieved by efficiently handling many Workload Arrival (WA) jobs near automobiles. Nevertheless, the problem of determining the Workload Offloading (WO) approach under different resource and delay limitations remains unresolved. Furthermore, since WA is arbitrary, vehicles consistently exhibit a selfish preference for choosing VEC servers for WO. This behavior is unsatisfactory for the system's overall social benefit and may lead to the probability of task failures owing to VEC server overload. This study discusses the Efficient Modelling of Workload Arrival and Offloading (EM-WAO) for VEC. When WA was considered a combination of vehicle arrivals and workload generators, it was discovered that the WA model for VEC servers does not follow the conventional Poisson distribution. This contrasts with the commonly accepted assumption in many previous research. The experimental evaluations have confirmed the validity and effectiveness of the suggested EM-WAO approach. The suggested EM-WAO demonstrated reduced time and power usage compared to the present techniques.