Software dependability modeling using an industry-standard architecture description language

Performing dependability evaluation along with other analyses at architectural level allows both making architectural tradeoffs and predicting the effects of architectural decisions on the dependability of an application. This paper gives guidelines for building architectural dependability models for software systems using the AADL (Architecture Analysis and Design Language). It presents reusable modeling patterns for fault-tolerant applications and shows how the presented patterns can be used in the context of a subsystem of a real-life application

Towards a Security, Privacy, Dependability, Interoperability Framework for the Internet of Things

A popular application of ambient intelligence systems constitutes of assisting living services on smart buildings. As intelligence is imported in embedded equipment, the system becomes able to provide smart services (e.g. control lights, airconditioning, provide energy management services etc.). IoT is the main enabler of such environments. However, the interconnection of these cyber-physical systems and the processing of personal data raise serious security and privacy issues. In this paper we present a framework that can guarantee Security, Privacy, Dependability and Interoperability (SPDI) in IoT. Taking advantage of the underlying IoT deployment, the proposed framework not only implements the requested smart functionality but also provide modelling and administration that can guarantee those SPDI properties. Moreover, we provide an application example of the framework in a smart building scenario

A survey on online monitoring approaches of computer-based systems

This report surveys forms of online data collection that are in current use (as well as being the subject of research to adapt them to changing technology and demands), and can be used as inputs to assessment of dependability and resilience, although they are not primarily meant for this use

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Context-aware adaptation in DySCAS

DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met

An architecture-based dependability modeling framework using AADL

For efficiency reasons, the software system designers' will is to use an integrated set of methods and tools to describe specifications and designs, and also to perform analyses such as dependability, schedulability and performance. AADL (Architecture Analysis and Design Language) has proved to be efficient for software architecture modeling. In addition, AADL was designed to accommodate several types of analyses. This paper presents an iterative dependency-driven approach for dependability modeling using AADL. It is illustrated on a small example. This approach is part of a complete framework that allows the generation of dependability analysis and evaluation models from AADL models to support the analysis of software and system architectures, in critical application domains

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