Joint Scheduling of Communication and Computation Resources for Efficient Computation Offloading in MEC-based V2X Systems

In the context of Multi-Access Edge Computing (MEC) Vehicle-to-Everything (V2X) systems, efficient resource allocation is crucial for minimizing computation and communication delays while improving offloading success. This paper proposes efficient computation offloading through a joint scheduling algorithm of computation and communication resources in the MEC V2X system. The algorithm leverages Ant Colony Optimization(ACO) to find an optimized offloading path for each computation task, considering the computation capacities of vehicles and MEC servers, communication bandwidths, and the probability of successful offloading. Simulations conducted in MATLAB evaluate the performance of the proposed algorithm, demonstrating its effectiveness in achieving lower delay, higher offloading success, and efficient resource utilization. The results showcase the practicality and advantages of the proposed algorithm in the MEC V2X system.