On cost-effective reuse of components in the design of complex reconfigurable systems

Design strategies that benefit from the reuse of system components can reduce costs while maintaining or increasing dependability—we use the term dependability to tie together reliability and availability. D3H2 (aDaptive Dependable Design for systems with Homogeneous and Heterogeneous redundancies) is a methodology that supports the design of complex systems with a focus on reconfiguration and component reuse. D3H2 systematizes the identification of heterogeneous redundancies and optimizes the design of fault detection and reconfiguration mechanisms, by enabling the analysis of design alternatives with respect to dependability and cost. In this paper, we extend D3H2 for application to repairable systems. The method is extended with analysis capabilities allowing dependability assessment of complex reconfigurable systems. Analysed scenarios include time-dependencies between failure events and the corresponding reconfiguration actions. We demonstrate how D3H2 can support decisions about fault detection and reconfiguration that seek to improve dependability while reducing costs via application to a realistic railway case study

Application of the D3H2 Methodology for the Cost-Effective Design of Dependable Systems

The use of dedicated components as a means of achieving desirable levels of fault tolerancein a system may result in high costs. A cost effective way of restoring failed functions is to use heterogeneous redundancies: components that, besides performing their primary intended design function, can also restore compatible functions of other components. In this paper, we apply a novel design methodology called D3H2 (aDaptive Dependable Design for systems with Homogeneous and Heterogeneous redundancies) to assist in the systematic identification of heterogeneous redundancies, the design of hardware/software architectures including fault detection and reconfiguration, and the systematic dependability and cost assessments of the system. D3H2 integrates parameter uncertainty and criticality analyses to model inexact failure data in dependability assessment. The application to a railway case study is presented with a focus on analysing different reconfiguration strategies as well as types and levels of redundancies

Model-based dependability analysis : state-of-the-art, challenges and future outlook

Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis

Guidance of architectural changes in technical systems with varying operational modes

Technical systems often rely on redundant platforms. One way to increase dependability is to define various QoS modes, applied to different hardware resources. Switching between modes is limited by resource availability and causes costs for structural changes. Hence, selecting appropriate system architectures for specific resource sets and defining cost-efficient mode sequences is challenging. This short paper proposes an approach to support reconfiguration decisions for varying modes. We extend our decision graphs for traversing architectures towards multi-purpose applicability. We optimise reconfigurations within individual modes while reducing costs of mode changes simultaneously. Graph-based differentiations lead to most efficient mode sequences, transition configurations and visualisations. To respect high reconfigurability, we particularly inspect impacts of resource faults. For evaluation, we apply a subsystem of a micro satellite with multiple operational modes

Comparisons of Robustness and Sensitivity between Cancer and Normal Cells by Microarray Data

Robustness is defined as the ability to uphold performance in face of perturbations and uncertainties, and sensitivity is a measure of the system deviations generated by perturbations to the system. While cancer appears as a robust but fragile system, few computational and quantitative evidences demonstrate robustness tradeoffs in cancer. Microarrays have been widely applied to decipher gene expression signatures in human cancer research, and quantification of global gene expression profiles facilitates precise prediction and modeling of cancer in systems biology. We provide several efficient computational methods based on system and control theory to compare robustness and sensitivity between cancer and normal cells by microarray data. Measurement of robustness and sensitivity by linear stochastic model is introduced in this study, which shows oscillations in feedback loops of p53 and demonstrates robustness tradeoffs that cancer is a robust system with some extreme fragilities. In addition, we measure sensitivity of gene expression to perturbations in other gene expression and kinetic parameters, discuss nonlinear effects in feedback loops of p53 and extend our method to robustness-based cancer drug design

Entwurfsoptimierung von selbst-adaptiven Wartungsmechanismen für software-intensive technische Systeme

Diese Arbeit stellt neuartige Konzepte zur effizienten Entscheidungsunterstützung in der Rekonfiguration software-intensiver technischer Systeme mit limitiertem Wartungszugriff vor. Entgegen rein redundanzorientierter Ansätze, basiert die verfolgte Methodik auf der prädiktiven Vorausberechnung adäquater Konfigurationsalternativen im relevanten Lösungsraum. Das Wissen über Konfigurationsbeziehung wird frühzeitig manifestiert und zur autarken kosteneffizienten Abwägung der Alternativen eingesetzt