A Multi-hop Control Network (MCN) consists of a plant where the communication between sensor, actuator and computational unit is supported by a wireless multi-hop communication network, and data flow is performed using scheduling and routing of sensing and actuation data. We address the problem of characterizing controllability and observability of a MCN, by means of necessary and sufficient conditions on the plant dynamics and on the communication scheduling and routing. We provide a methodology to design scheduling and routing, in order to satisfy controllability and observability of a MCN for any fault occurrence in a given set of configurations of failures.
However, what is needed for modeling and analyzing control protocols on multi hop control networks is an integrated framework for analysing co-designing network topology, scheduling, routing, transmission errors and control. To the best of our knowledge, the only formal model of multi-hop wireless sensor and actuator networks is reported in @cite_9 . In this paper, a simulation environment that facilitates simulation of computer nodes and communication networks interacting with the continuous-time dynamics of the real world is presented. The main difference between the work presented in @cite_9 and this work is that here we provide results on a formal mathematical model that takes into account plant dynamics and scheduling-routing dynamics.
@cite_9
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Embedded systems are becoming increasingly networked and are deployed in application areas that require close interaction with their physical environment. Examples include distributed mobileagents and wireless sensor ac tuator networks. The complexity of these applic ations make co- simulation a necessary tool during system development. This paper presents a simulation environment that facilitates simu- lation of computer nodes and communic ation networks inter- acting with the continuous-time dynamics of the real world. Features of the simulator include interrupt handling, task scheduling, wired and wireless communication, local clocks, dynamic voltage scaling, and battery-driven operation. Two simulation case studies are presented: a simple communication scenario and a mobile robot soccer game.