Dynamic Task and Resource Scheduling Towards Green Space-Air-Ground-Sea Integrated Network

TL;DR

This paper presents a dynamic task and resource scheduling method for green space-air-ground-sea networks in 6G, improving efficiency and reducing task delay through adaptive algorithms and joint optimization.

Contribution

It introduces a novel multi-layer task offloading algorithm with anticipatory handover and joint resource optimization tailored for SAGSIN in 6G environments.

Findings

Achieves at least 23% reduction in average task delay.

Effectively adapts to real-time system dynamics.

Enhances satellite resource utilization and network connectivity.

Abstract

In the context of 6G ubiquitous connectivity, the space-air-ground-sea integrated network (SAGSIN) emerges as a new paradigm to provide critical services for resource-limited ocean environments. To realize this paradigm efficiently, we propose an innovative dynamic task and resource scheduling approach for green SAGSIN that delivers computing support for vessels while minimizing overall task execution delay. To address the challenge of multi-layer task scheduling, a layer-wise task offloading algorithm is developed specifically for SAGSIN. It adapts to real-time, multi-dimensional system dynamics and integrates an anticipatory handover strategy that adaptively controls the amount of data offloaded to the satellite, thereby preventing post-handover congestion while improving satellite resource utilization. Furthermore, the bandwidth allocation of uncrewed aerial vehicles and base station, UAV trajectories, and computing resource allocation are jointly optimized to enhance connectivity among low-altitude devices and facilitate demand-driven resource allocation for green network development. Simulation results verify that the proposed method better adapts to dynamic system resources and achieves at least a 23% reduction in average task delay compared with benchmarks.