1,721,566 research outputs found
CSIM 19 User Story Computer Communication Systems Performance Evaluation: A Discrete Event Simulation with CSIM 19
No full textI am a PhD student in Electrical and Computer Engineering at Duke University. I work with Dr. Kishor S. Trivedi, and our research interests focus on reliability and performance assessment of computer and communication systems. Ou
Online Reliability Monitoring: a Hybrid Approach
No full textAssuring high reliability levels in complex software systems is difficult. The spread of component-based paradigm brought, along with many advantages, new thorny problems and challenges. Various approaches have been proposed to guarantee high reliability and cope with such problems – among these, proactive policies are particularly effective and inexpensive. The ability to monitor the system at runtime and to give online estimations about the trend of dependability attribute of interest, is the key to implement strategies aiming at forecasting, and thus proactively preventing, the system failure occurrence. In this paper, an online reliability monitoring approach is proposed. It combines benefits of architecture- based reliability model and dynamic analysis, so as to integrate static modeling power with representative operational data. Its usage is illustrated by a prototype implementation, a case-study and preliminary results
Dynamic aspects and behaviors of complex systems in performance and reliability assessment
No full textSpecial Section on Cloud Computing Assessment: Metrics, Algorithms, Policies, Models, and Evaluation Techniques - Part A: Security
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Software Reliability and Testing Time Allocation: An Architecture-Based Approach
No full textWith software systems increasingly being employed in critical contexts, assuring high reliability levels for large, complex systems can incur huge verification costs. Existing standards usually assign predefined risk levels to components in the design phase, to provide some guidelines for the verification. It is a rough-grained assignment that does not consider the costs and does not provide sufficient modeling basis to let engineers quantitatively optimize resources usage. Software reliability allocation models partially address such issues, but they usually make so many assumptions on the input parameters that their application is difficult in practice. In this paper, we try to reduce this gap, proposing a reliability and testing resources allocation model that is able to provide solutions at various levels of detail, depending upon the information the engineer has about the system. The model aims to quantitatively identify the most critical components of software architecture in order to best assign the testing resources to them. A tool for the solution of the model is also developed. The model is applied to an empirical case study, a program developed for the European Space Agency, to verify model's prediction abilities and evaluate the impact of the parameter estimation errors on the prediction accuracy
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