HARP: Hierarchical Resource Partitioning in Dynamic Industrial Wireless Networks

Abstract

Industrial wireless networks (IWNs) are being increasingly deployed in the field to serve as the network fabrics for various industrial Internet-of-Things (IIoT) applications. Given that IWNs typically operate in noisy and harsh environments, frequently occurring network dynamics post huge challenges for IWN resource management especially when the network scales up. Existing centralized and distributed network management solutions either suffer from large communication overhead and time delay, or introduce schedule collisions which unnecessarily degrade the system performance. To address these problems, this work proposes a novel HierArchical Resource Partitioning framework (HARP), to provide dynamic resource management in IWNs. By hierarchically partitioning and allocating resources for the links in the network, HARP enables distributed collision-free resource allocation. HARP enables rapid adjustment of the partitions in the presence of network dynamics with modest communication overhead. The effectiveness of HARP is validated and evaluated through both simulation studies and testbed experiments on a 50-node multi-channel multi-hop 6TiSCH network.