DVFS-Enabled Adaptive Offloading and Adjusting for High-Efficiency 5G Power MEC

5G Mobile edge computing (MEC) is a promising computing method to meet the low latency requirements of emerging power applications. By offloading computing intensive power applications from mobile devices to edge cloud servers, computing experience can be further improved in 5G power MEC systems. Based on 5G MEC, this paper proposes an adaptive offloading and allocating scheme (AOAS), which minimizes the response cost when the power application is constrained by the expected response delay. Specifically, this paper proposes a minimum consumption application offloading problem with corresponding delay, local CPU computing speed and other network resource constraints. Combined with variable replacement technology, this paper designs and proposes a resource control strategy integrating offload rate, local CPU computing speed and transmit power. Finally, the simulation results show that the system appearance of this scheme is better than that of local computing, full offloading and partial offloading with fixed computing speed.