A computation offloading scheme for energy consumption optimization in Internet of vehicles

Abstract

In Internet of vehicles (IoV), vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU), user vehicles, and mobile vehicles within the RSU service range, a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S2COS), aiming to optimize the overall system energy consumption.In addition, this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S2COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.

Keywords

• Internet of vehicles;computation offloading;node failure;sparrow search algorithm