Task offloading based on edge collaboration in MEC-enabled IoV networks

Benefiting from its abundant computing resources and low latency, mobile edge (MEC) is a promising approach for enhancing the capacity of 5G Internet vehicles (IoV). Because high mobility, handover frequent inevitable in IoV networks. In this paper, we investigate an collaborative task offloading splitting strategy MEC-enabled networks, which splitted on paralleling executed by each part several MEC servers when occured. Applications networks have flexible requirements latency energy consumption. To realize tradeoff between consumption, formulate as optimization problem with aim minimizing total cost consumption jointly optimizing ratio uplink transmit power vehicle terminal (VT). proposed non-smooth non-convex, divide original into two convex subproblems, apply alternate search (ACS) algorithm to obtain optimized solution computational complexity. Numerical simulation results show that method can adjust properly according preference, lower compared baseline algorithms.