标题： 基于回压的多跳无线传感器网络调度广义型博弈 显示英文标题

标题： Backpressure-based Mean-field Type Game for Scheduling in Multi-Hop Wireless Sensor Networks

摘要： 我们提出了一种基于平均场型博弈（MFTG）的框架，用于多跳无线传感网络（WSN）中以背压作为性能标准的有效调度。 传统的背压算法利用队列差分来调节数据流并维持网络稳定性。 在这项工作中，我们通过在代价泛函中引入一个平均场项来扩展背压框架，捕捉系统整体行为与局部动态的结合。 由此产生的模型利用了非合作平均场型博弈的优势，使节点能够根据个体队列状态和系统平均场效应做出去中心化的决策，同时考虑随机网络交互。 通过利用背压动态与平均场耦合之间的相互作用，该方法在局部优化与全局效率之间实现了平衡。 数值模拟表明，所提出的方法在处理大规模WSN中的拥塞和调度问题上非常有效。 显示英文摘要

摘要： We propose a Mean-Field Type Game (MFTG) framework for effective scheduling in multi-hop wireless sensor networks (WSNs) using backpressure as a performance criterion. Traditional backpressure algorithms leverage queue differentials to regulate data flow and maintain network stability. In this work, we extend the backpressure framework by incorporating a mean-field term into the cost functional, capturing the global behavior of the system alongside local dynamics. The resulting model utilizes the strengths of non-cooperative mean-field type games, enabling nodes to make decentralized decisions based on both individual queue states and system mean-field effects while accounting for stochastic network interactions. By leveraging the interplay between backpressure dynamics and mean-field coupling, the approach balances local optimization with global efficiency. Numerical simulations demonstrate the efficacy of the proposed method in handling congestion and scheduling in large-scale WSNs.