32,869 research outputs found
A direct path to dependable software
What would it take to make software more dependable? Until now, most approaches have been indirect: some practices – processes, tools or techniques – are used that are believed to yield dependable software, and the argument for dependability rests on the extent to which the developers have adhered to them. This article argues instead that developers should produce direct evidence that the software satisfies its dependability claims. The potential advantages of this approach are greater credibility (since the argument is not contingent on the effectiveness of the practices) and reduced cost (since development resources can be focused where they have the most impact)
Techniques for the Fast Simulation of Models of Highly dependable Systems
With the ever-increasing complexity and requirements of highly dependable systems, their evaluation during design and operation is becoming more crucial. Realistic models of such systems are often not amenable to analysis using conventional analytic or numerical methods. Therefore, analysts and designers turn to simulation to evaluate these models. However, accurate estimation of dependability measures of these models requires that the simulation frequently observes system failures, which are rare events in highly dependable systems. This renders ordinary Simulation impractical for evaluating such systems. To overcome this problem, simulation techniques based on importance sampling have been developed, and are very effective in certain settings. When importance sampling works well, simulation run lengths can be reduced by several orders of magnitude when estimating transient as well as steady-state dependability measures. This paper reviews some of the importance-sampling techniques that have been developed in recent years to estimate dependability measures efficiently in Markov and nonMarkov models of highly dependable system
A methodology for the generation of efficient error detection mechanisms
A dependable software system must contain error detection mechanisms and error recovery mechanisms. Software components for the detection of errors are typically designed based on a system specification or the experience of software engineers, with their efficiency typically being measured using fault injection and metrics such as coverage and latency. In this paper, we introduce a methodology for the design of highly efficient error detection mechanisms. The proposed methodology combines fault injection analysis and data mining techniques in order to generate predicates for efficient error detection mechanisms. The results presented demonstrate the viability of the methodology as an approach for the development of efficient error detection mechanisms, as the predicates generated yield a true positive rate of almost 100% and a false positive rate very close to 0% for the detection of failure-inducing states. The main advantage of the proposed methodology over current state-of-the-art approaches is that efficient detectors are obtained by design, rather than by using specification-based detector design or the experience of software engineers
Multi-Layer Cyber-Physical Security and Resilience for Smart Grid
The smart grid is a large-scale complex system that integrates communication
technologies with the physical layer operation of the energy systems. Security
and resilience mechanisms by design are important to provide guarantee
operations for the system. This chapter provides a layered perspective of the
smart grid security and discusses game and decision theory as a tool to model
the interactions among system components and the interaction between attackers
and the system. We discuss game-theoretic applications and challenges in the
design of cross-layer robust and resilient controller, secure network routing
protocol at the data communication and networking layers, and the challenges of
the information security at the management layer of the grid. The chapter will
discuss the future directions of using game-theoretic tools in addressing
multi-layer security issues in the smart grid.Comment: 16 page
Reconfiguration of Distributed Information Fusion System ? A case study
Information Fusion Systems are now widely used in different fusion contexts,
like scientific processing, sensor networks, video and image processing. One of
the current trends in this area is to cope with distributed systems. In this
context, we have defined and implemented a Dynamic Distributed Information
Fusion System runtime model. It allows us to cope with dynamic execution
supports while trying to maintain the functionalities of a given Dynamic
Distributed Information Fusion System. The paper presents our system, the
reconfiguration problems we are faced with and our solutions.Comment: 6 pages - Preprint versio
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