Graph-Driven Resource Allocation Strategies in Satellite IoT: A Cooperative Game-Theoretic Approach
Huilong Fan, Chongxiang Sun, Jun Long, Ling Li, Yakun Huo, Shangpeng Wang
Abstract
Multi-satellite intelligent computing, aimed at autonomously generating resource allocation schemes without reliance on ground control, is a crucial technology for the intelligent and integrated Internet of Things (IoT) from space to ground. Existing work focuses on ground-based computation for scheduling schemes, and while some recent studies have adopted graph computing and distributed computing strategies on satellites, they have overlooked the frequent changes in satellite network topologies and the coupling relationships between various types of resources. The robustness advantage of game theory offers a possibility for reliable computation in resource allocation. We introduce a multi-satellite intelligent negotiation mechanism based on cooperative game theory, which for the first time, considers dynamic and autonomous negotiation methods for satellite agents with various types of resources. Subsequently, we propose an intelligent computing algorithm for resource allocation based on convex games and design heuristic strategies for adaptively updating resource allocation schemes. Our simulation results indicate that this method outperforms benchmark algorithms in different scenarios, reducing time consumption by at least 0.151%.