Enhancing Resource Allocation and Performance in Multilayer Industrial IoT Through Adjustable Strategy Integrating Cooperative Communication and Edge Computing

Reliable bidirectional communication between the control center and manufacturing devices (MDs) along with efficient resource allocation are critical for the Industrial Internet of Things (IIoT). However, due to the limited network resources of IIoT devices and the intertwined nature of communication and computation resources, achieving efficient optimization of these resources presents significant challenges. In this article, we propose a multilayer communication architecture for the IIoT based on edge computing and cooperative communication technologies, where resource-constrained MDs upload data to edge servers (ESs) for processing. To address the issues of resource scarcity and coupling, we establish a bandwidth release model to analyze and quantify the relationship between computation and communication resources. This elucidates the interaction mechanisms between “transmission-computation” performance. Furthermore, to prevent excessive data upload to ESs, which could lead to node overload and network congestion, we employ game theory to develop a pricing mechanism for resource allocation, where ESs charge for computation services. Specifically, we construct a Lagrangian framework to determine a resource allocation scheme, aiming to maximize the utility of the factory. Simulation results indicate that compared to common methods employed in existing works, our strategy enhances factory utility by 29.79%.