Control Aware Communication System for Edge Cloud based Industrial Applications

Vorschau

Leseprobe, PDF (140 KB)
Inhaltsverzeichnis, PDF (41 KB)

The text discusses the growing need for reliable wireless communication in Industry 4.0, driven by increased data exchange between humans and machines as well as between machines themselves. With the rise of connected devices in industrial environments, wireless systems must match the performance of wired networks, especially for critical applications requiring ultra-reliable and low-latency communication (URLLC).

Because Industrial Internet of Things (IIoT) devices have limited energy and processing capacity, computational tasks are increasingly offloaded to edge clouds. This helps reduce device energy consumption while meeting strict latency requirements. However, wireless channels introduce challenges such as delays, fading, and additional energy costs.

The thesis focuses on optimizing computation offloading strategies to minimize energy consumption while considering factors like channel conditions, latency constraints, and cloud resources. It shows that efficient offloading depends heavily on wireless channel quality and system resources.

Additionally, the research examines wireless control of industrial systems, specifically Automated Guided Vehicles (AGVs). It finds that poor channel conditions increase instability and control errors, while factors like packet transmission rate and mobility influence system performance. The study identifies optimal communication strategies, such as transmission frequency and coding rates, to maintain stability and efficiency.

A key contribution is the development of control-aware communication methods that integrate control system requirements into communication design. This includes new performance metrics like the “probability of instability” and improved algorithms for resource allocation and scheduling.

Overall, the work advances energy-efficient, reliable, and control-aware wireless communication strategies for industrial systems, supporting the development of robust Industry 4.0 applications.