DEFT: Decentralized Multiuser Computation Offloading in a Fog-Enabled IoV Environment

In this paper, we propose a mechanism - DEFT- to facilitate mobile Internet of Vehicles (IoV) user entities (UEs) with unit tasks to cooperate among one another and offload their tasks to nearby fog nodes (FNs)/roadside units (RSUs) in a decentralized and fair manner. While existing literature depends on offloading schemes based on centralized systems, DEFT provides near real-time computation offloading in a fog-enabled IoV using a two-level game-theoretic approach. Further, this approach allows the UEs to make their own decisions in a dynamic environment. In the first level, FNs play an Oligopoly game for determining the price of their services based on their computation capability and then broadcast the price to the UEs. Further, based on the price transmitted by the FNs, UEs play a non-cooperative Stackelberg game to map the offloading among the user and fog layer. We also ensure that no UE consumes all of the resources in an FN. Additionally, we prove our objective function's convexity and show that the proposed game always attains the Nash Equilibrium. Through extensive real-world emulations, we observe that DEFT minimizes the latency and power consumption, and improves throughput compared to the existing schemes. In the presence of 40, 80, and 120 UEs, the overhead for computation in the fog layer is minimized by 70-75% compared to the local computation overhead.