Dynamic scheduling reduces maritime task delays by optimizing multi-layer networks
Dynamic Task and Resource Scheduling Towards Space-Air-Ground-Sea Integrated Network
Networking and Internet Architecture
Summary
Communication and computing services on the ocean are hard because of limited infrastructure and moving vessels. The authors designed a smart system that uses satellites, flying platforms, coastal stations, and drones to share and process tasks efficiently. Their method chooses the best places and ways to handle tasks to avoid delays and save drone energy. Tests show their approach cuts task delays by at least 23%, helping maritime activities run smoother.
What this means in practice
- •For maritime network operators: Optimize task processing and data flow on maritime communication networks to reduce delays and better use computing and communication resources.
- •For drone fleet managers: Manage drone routes, energy use, and task handoffs to maintain computing services in areas lacking infrastructure.
Authors
Yufei Ye, Shijian Gao, Xinhu Zheng, Liuqing Yang
Abstract
In the context of 6G ubiquitous connectivity, the space-air-ground-sea integrated network (SAGSIN) emerges as a new paradigm for pervasive service provisioning. To support expanding maritime activities in infrastructure-scarce ocean areas, we propose an innovative dynamic task and resource scheduling approach for SAGSIN to deliver computing services for vessels. It integrates broad-coverage satellites, relay-capable high-altitude platform (HAP), energy-sufficient coastal base station (BS), and flexibly deployed uncrewed aerial vehicles (UAVs) to accommodate wide-area, highly mobile, and sustained maritime services. To address the challenge of task scheduling across four layers, a dynamic task offloading algorithm is developed. It steers task flows toward servers with light loads, strong computing capabilities, and high-rate links based on real-time system states to reduce task execution delay, integrating an anticipatory satellite handover strategy to mitigate post-handover congestion and improving satellite resource utilization. Considering the limited endurance of UAVs, we impose residual energy constraints to ensure task backlog handover and safe return. Furthermore, the UAV-BS bandwidth allocation, UAV trajectories, and computing resource allocation are jointly optimized to enhance the connectivity among low-altitude devices and accelerate task completion. Simulation results validate the proposed method's superior adaptability to system resource variations during task execution in complex maritime environments, achieving at least a 23% reduction in average task delay over benchmarks.