Cooperative mobile edge computing‐cloud computing in Internet of vehicle: Architecture and energy‐efficient workload allocation

Abstract

Abstract With the increasing number of vehicles, the generating vehicular data exceeds the capacity of mobile edge computing (MEC). Therefore, studying the interaction and collaboration of edge computing and cloud computing is of significance to provide vehicular users with low‐latency high‐rate services. This paper first proposes a MEC‐cloud computing collaboration architecture for Internet of vehicles, then designs the interconnection/interaction framework between MEC and cloud computing. We consider reducing computation delay and power consumption, and formulate an energy‐efficient workload allocation problem with load balancing and dynamic voltage frequency scaling technology, to obtain the optimal workload allocations of MEC and cloud computing. We then present the overall distribution optimization algorithm to solve this problem. The simulation and numerical results show that by saving communication bandwidth and reducing transmission delay, MEC significantly enhances the performance of cloud computing. Besides, the proposed workload balance scheme is better than the benchmark schemes in terms of power consumption and latency.