State machine model-based middleware for control and processing in industrial wireless sensor and actuator networks
The advancements in communications and embedded systems have led to the proliferation of wireless sensor and actuator networks (WSANs) in a wide variety of application domains. One important key of many such WSAN applications is how to configure/program functionalities after deployment. Some application domains even require that sensor nodes be deployed in harsh environments (e.g., refineries), where they need to be configured over-the-air. Over-the-air programming takes more than 4 second to transmit an image code to a node where, typically, a single image has 40kB. With the proposed model, small code blocks (states and transitions) are generated (about 4kB) to upload to nodes. This methodology allows reducing the programming time to 5 times less, release bandwidth and keep battery on nodes. To support our approach we propose an architecture based on state machines model which provides an easy user-readable high-level representation of states and transitions. The communication time is reduced through the reduction of the code image size that it is needed to send to each node. We develop an architecture that allows users to define and program applications based on Markov techniques, to simultaneously facilitate the application design and take into account important requirements such as reliability. The experimental section shows a working deployment of this concept in an industrial refinery setting.