Network Resource Management for Cloud based Networked Control Systems via Adaptive Sampling

A recent advancement in computing technology, referred to as cloud computing, enables control systems to access computational and storage resources over communication networks. Motivated by the benefits of using the cloud, several research efforts are going on to incorporate cloud into the traditional control system. However, signals, including control actions, are transmitted over a communication link which is associated with bandwidth limitation that could cause delay, packet drops which ultimately affects the performance and stability of the underlying control system. In this paper, we propose a real-time network resource management strategy to manage network resources to overcome such drawbacks. The proposed fuzzy based algorithms are implemented in an experimental platform to demonstrate the effectiveness of maintaining the successful operation of the plant under limited network resources.