Biblio
The supervisory control and data acquisition (SCADA) network in a smart grid requires to be reliable and efficient to transmit real-time data to the controller. Introducing SDN into a SCADA network helps in deploying novel grid control operations, as well as, their management. As the overall network cannot be transformed to have only SDN-enabled devices overnight because of budget constraints, a systematic deployment methodology is needed. In this work, we present a framework, named SDNSynth, that can design a hybrid network consisting of both legacy forwarding devices and programmable SDN-enabled switches. The design satisfies the resiliency requirements of the SCADA network, which are specified with respect to a set of identified threat vectors. The deployment plan primarily includes the best placements of the SDN-enabled switches. The plan may include one or more links to be installed newly. We model and implement the SDNSynth framework that includes the satisfaction of several requirements and constraints involved in resilient operation of the SCADA. It uses satisfiability modulo theories (SMT) for encoding the synthesis model and solving it. We demonstrate SDNSynth on a case study and evaluate its performance on different synthetic SCADA systems.
We develop a novel model-based hardware-in-the-loop (HIL) framework for optimising energy consumption of embedded software controllers. Controller and plant models are specified as networks of parameterised timed input/output automata and translated into executable code. The controller is encoded into the target embedded hardware, which is connected to a power monitor and interacts with the simulation of the plant model. The framework then generates a power consumption model that maps controller transitions to distributions over power measurements, and is used to optimise the timing parameters of the controller, without compromising a given safety requirement. The novelty of our approach is that we measure the real power consumption of the controller and use thus obtained data for energy optimisation. We employ timed Petri nets as an intermediate representation of the executable specification, which facilitates efficient code generation and fast simulations. Our framework uniquely combines the advantages of rigorous specifications with accurate power measurements and methods for online model estimation, thus enabling automated design of correct and energy-efficient controllers.