SCODA: Joint Optimization of Task Offloading and Resource Allocation in LEO-Assisted MEC System With Satellite Cooperation

Efficient offloading and resource management are critical for LEO satellite-assisted multi-access edge computing (MEC) systems. This letter introduces a collaborative model based on satellite groups that enables resource sharing between adjacent forward and backward satellites to address load distribution issues. We propose the satellite cooperation and optimization with differential evolution and Dinkelbach algorithm (SCODA), which minimizes the cost of task devices (TDs) by optimizing offloading decisions, resource allocation, and power control. Our scheme ensures flexible load balancing and enhances resource utilization through a multilayer computing framework. Simulation results show that SCODA outperforms benchmarks, reducing costs and improving efficiency.