About this Research Topic
To solve such a problem, handling data processing and storage closer to the data source is an efficient approach giving rise to edge computing-based IIoT. Thus, edge computing has been recognized as a core component of IIoT for resource management. However, there are still numerous challenges such as the emergence of diverse IoT sensors, massive-scale deployment, and constrained resources, that need to be tackled to develop an efficient IIoT network. Motivated by the success of machine learning in various fields such as robotics, natural language processing, and computer vision. It is envisioned that machine learning can be helpful in addressing the challenge of resource management in large-scale networks. In a large-scale network, it can aid in accomplishing the smart routing and intelligent MAC layer resources allocation specially for IIoT applications. Cross-layer based resource management for IIoT applications can also be achieved efficiently with machine learning. Similarly, machine learning is also vital in realizing the full potential of edge computing-based IIoT. Machine learning-based edge nodes can reduce processing time, i.e., the actions can happen faster based on learned information instead of transmitting data back and forth.
Similarly, predictive maintenance can be achieved efficiently for IIoT with the integration of machine learning and edge computing. This Research Topic solicits high-quality original research papers that provide recent technical advances, potential use cases, open research problems, and promising solutions with regards to machine learning, resource management, and edge computing-based IIoT.
Topics of interest to this special issue include but are not limited to the following:
- MAC layer resource management for IoT applications
- Network Layer resources management for IoT applications
- Cross-layer resource management for IoT applications
- Intelligent data processing for edge nodes in IoT
- Automation and optimization in edge-computing based IoT
- Big data processing and modeling of IoT
- Management and storage of data for IIoT applications
- Energy efficiently in IIoT network operation
- Security, privacy, and trust management in IIoT
- Applications of machine learning and edge computing in IIoT scenarios
Keywords: Internet of Things, Resource Management, Machine Learning, IoT Applications, Industrial IoT
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.