Optimizing routing in Wireless Sensor Networks (WSNs) is pivotal for minimizing energy consumption and extending network lifetime. This paper introduces a resourceefficient compilation method for distributed quantum circuits tailored to address large-scale WSN routing problems. Leveraging a hybrid classical-quantum framework, we employ spectral clustering for network partitioning and the Quantum Approximate Optimization Algorithm (QAOA) for optimizing routing within manageable subgraphs. We formulate the routing problem as a Quadratic Unconstrained Binary Optimization (QUBO) problem, providing comprehensive mathematical formulations and complexity analyses. Comparative evaluations against traditional classical algorithms demonstrate significant energy savings and enhanced scalability. Our approach underscores the potential of integrating quantum computing techniques into wireless communication networks, offering a scalable and efficient solution for future network optimization challenges

翻译：优化无线传感器网络（WSN）中的路由对于降低能耗和延长网络寿命至关重要。本文提出一种资源高效的分布式量子电路编译方法，专门用于解决大规模WSN路由问题。利用经典-量子混合框架，我们采用谱聚类进行网络分区，并利用量子近似优化算法（QAOA）在可管理的子图内优化路由。我们将路由问题建模为二次无约束二进制优化（QUBO）问题，提供了完整的数学公式和复杂度分析。与传统经典算法的对比评估显示出显著的节能效果和更强的可扩展性。我们的方法强调了将量子计算技术集成到无线通信网络中的潜力，为未来的网络优化挑战提供了一个可扩展且高效的解决方案。