A Learning-based Distributed Algorithm for Scheduling in Multi-hop Wireless Networks

Daehyun Park, Sunjung Kang, and Changhee Joo

10.23919/JCN.2021.000030

Abstract : We address the joint problem of learning and scheduling in multi-hop wireless network without a prior knowledge on link rates. Previous scheduling algorithms need the link rate information, and learning algorithms often require a centralized entity and polynomial complexity. These become a major obstacle to develop an efficient learning-based distributed scheme for resource allocation in large-scale multi-hop networks. In this work, by incorporating with learning algorithm, we develop provably efficient scheduling scheme under packet arrival dynamics without a priori link rate information. We extend the results to distributed implementation and evaluation their performance through simulations. 

Index terms : Distributed algorithm, learning, multi-hop networks, provable efficiency, wireless scheduling.