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Register a new userCLAIR: A Contract-based Framework for Developing Resilient CPS Architectures
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Daniel Jun Xian Ng
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Industrial cyber-infrastructure is normally a multilayered architecture. The purpose of the layered architecture is to hide complexity and allow independent evolution of the layers. In this paper, we argue that this traditional strict layering results in poor transparency across layers affecting the ability to significantly improve resiliency. We propose a contract-based methodology where components across and within the layers of the cyber-infrastructure are associated with contracts and a light-weight resilience manager. This allows the system to detect faults (contract violation monitored using observers) and react (change contracts dynamically) effectively. It results in (1) improving transparency across layers; helps resiliency, (2) decoupling fault-handling code from application code; helps code maintenance, (3) systematically generate error-free fault handling code; reduces development time. Using an industrial case study, we demonstrate the proposed methodology.
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As the industrial cyber-infrastructure become increasingly important to realise the objectives of Industry~4.0, the consequence of disruption due to internal or external faults become increasingly severe. Thus there is a need for a resilient infrastructure. In this paper, we propose a contract-based methodology where components across layers of the cyber-infrastructure are associated with contracts and a light-weight resilience manager. This allows the system to detect faults (contract violation monitored using observers) and react (change contracts dynamically) effectively.
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Instilling resilience in critical infrastructure (CI) such as dams or power grids is a major challenge for tomorrows cities and communities. Resilience, here, pertains to a CIs ability to adapt or rapidly recover from disruptive events. In this paper, the problem of optimizing and managing the resilience of CIs is studied. In particular, a comprehensive two-fold framework is proposed to improve CI resilience by considering both the individual CIs and their collective contribution to an entire system of multiple CIs. To this end, a novel analytical resilience index is proposed to measure the effect of each CIs physical components on its probability of failure. In particular, a Markov chain defining each CIs performance state and a Bayesian network modeling the probability of failure are introduced to infer each CIs resilience index. Then, to maximize the resilience of a system of CIs, a novel approach for allocating resources, such as drones or maintenance personnel, is proposed. In particular, a comprehensive resource allocation framework, based on the tools of contract theory, is proposed enabling the system operator to optimally allocate resources, such as, redundant components or monitoring devices to each individual CI based on its economic contribution to the entire system. The optimal solution of the contract-based resilience resource allocation problem is analytically derived using dynamic programming. The proposed framework is then evaluated using a case study pertaining to hydropower dams and their interdependence to the power grid. Simulation results, within the case study, show that the system operator can economically benefit from allocating the resources while dams have a 60% average improvement over their initial resilience indices.
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