Resource Allocation and Task Migration in DIMA-Oriented Mobile Edge Computing Systems

Avionics systems are evolving from Integrated Modular Avionics (IMA) to Distributed Integrated Modular Avionics (DIMA), where distributed computing nodes are interconnected through real-time networks to support flexible resource sharing and latency-critical services. This architecture is highly consistent with the paradigm of Mobile Edge Computing (MEC), in which distributed edge resources collaboratively process computation workloads close to users to meet stringent real-time requirements. However, efficient task scheduling and migration remain key challenges in such distributed MEC platforms, since many existing approaches are designed for traditional centralized architectures and lack effective support for runtime workload dynamics and migration overheads. In this paper, we abstract the computing resource and task models for DIMA-oriented MEC systems and propose two algorithms: an Efficient Workload Scheduling Algorithm (EWSA) for workload placement and a Workload Migration Algorithm (WMA) for adaptive task relocation. CloudSim-based simulations show that the proposed methods significantly outperform the benchmark JIT-C approach in scheduling performance and migration efficiency, demonstrating their effectiveness for real-time distributed edge computing environments.