Energy-Efficient Synchronization in Industrial Internet of Things: An Intelligent Neighbor-Knowledge Approach

Abstract

In the Industrial Internet of Things (IIoT), energy efficiency is a paramount concern as it directly affects operational longevity. Traditional approaches, like flooding for time synchronization, often result in redundant message transmissions, thereby wasting energy. This article introduces an intelligent neighbor-knowledge synchronization (INKS) method to mitigate this problem. The INKS algorithm leverages each node's understanding of its neighboring nodes to optimize the synchronization process, thereby reducing the total number of synchronization messages and conserving energy. The INKS is implemented and evaluated using real wireless sensor networks with varying configurations. The experimental results demonstrate their superior performance to existing techniques, such as rapid flooding multiple one-way broadcast time synchronization (RMTS). Additionally, the performance of INKS is evaluated through simulations conducted on large-scale networks. For the network topology of the four-way grid, the findings reveal that INKS reduces the number of transmitted messages by approximately 72% compared to RMTS. Moreover, INKS matches the efficiency of scheduling-based low-energy synchronization for IIoT.