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Pietrantuono R.,University of Naples Federico II | Russo S.,Complesso Universitario Monte SantAngelo | Trivedi K.S.,Duke University
EDCC-8 - Proceedings of the 8th European Dependable Computing Conference | Year: 2010

Reliability is one of the major concerns for software engineers. The increasing size of software systems and their inherent complexity - which is essentially related to the intricate interdependencies among many heterogeneous components - pose serious difficulties to its assessment and assurance. The actual system runtime behavior is difficult to forecast during the development phase, and just relying upon sound design and testing techniques is often not sufficient to deliver highly reliable systems. In order to guarantee high reliability, system behavior needs to be monitored at runtime and its reliability needs to be periodically estimated during operation, taking into account both structural/static and behavioral/dynamic information. In this paper, we propose an online reliability monitoring approach, which combines static reliability modeling and dynamic analysis to periodically evaluate system reliability trend during operation. Its usage is illustrated by a prototype implementation and a case-study. © 2010 IEEE. Source

Aviles A.,National Autonomous University of Mexico | Aviles A.,Instituto Nacional de Investigaciones Nucleares | Gruber C.,Free University of Berlin | Luongo O.,National Autonomous University of Mexico | And 5 more authors.
Physical Review D - Particles, Fields, Gravitation and Cosmology | Year: 2012

We use cosmography to present constraints on the kinematics of the Universe, without postulating any underlying theoretical model. To this end, we use a Monte Carlo Markov chain analysis to perform comparisons to the supernova Ia Union 2 compilation, combined with the Hubble Space Telescope measurements of the Hubble constant, and the Hubble parameter data sets. We introduce a sixth order cosmographic parameter and show that it does not enlarge considerably the posterior distribution when comparing to the fifth order results. We also propose a way to construct viable parameter variables to be used as alternatives of the redshift z. These can overcome both the problems of divergence and lack of accuracy associated with the use of z. Moreover, we show that it is possible to improve the numerical fits by reparametrizing the cosmological distances. In addition, we constrain the equation of state of the Universe as a whole by the use of cosmography. Thus, we derive expressions which can be directly used to fit the equation of state and the pressure derivatives up to fourth order. To this end, it is necessary to depart from a pure cosmographic analysis and to assume the Friedmann equations as valid. All our results are consistent with the ΛCDM model, although alternative fluid models, with nearly constant pressure and no cosmological constant, match the results accurately as well. © 2012 American Physical Society. Source

Cotroneo D.,University of Naples Federico II | Paudice A.,Complesso Universitario Monte SantAngelo | Pecchia A.,University of Naples Federico II
Future Generation Computer Systems | Year: 2016

The analysis of the security alerts collected during the system operations is a crucial task to initiate effective responses against attacks and intentional system misuse. A variety of monitors are today available to generate security alerts, such as intrusion detection systems, network audit, vulnerability scans, and event logs. While the amount of alerts generated by the security monitors represents a goldmine of information, the ever-increasing volume and heterogeneity of the collected alerts pose a major threat to timely security analysis and forensic activities conducted by the operations team. This paper proposes a framework consisting of a filter and a decision tree to address large volumes of security alerts and to support the automated identification of the root causes of the alerts. The framework adopts both term weighting and conceptual clustering approaches to fill the gap between the unstructured textual alerts and the formalization of the decision tree. We evaluated the framework by analyzing two security datasets in a production SaaS Cloud, which generates an average volume of 800 alerts/day. The framework significantly reduced the volume of alerts and inferred the root causes of around 98.8% of alerts with no human intervention with respect to the datasets available in this study. More important, we leveraged the output of the framework to provide a classification of the root causes of the alerts in the target SaaS Cloud. © 2015 Elsevier B.V. Source

Cotroneo D.,University of Naples Federico II | Natella R.,University of Naples Federico II | Pietrantuono R.,University of Naples Federico II | Russo S.,University of Naples Federico II | Russo S.,Complesso Universitario Monte SantAngelo
Proceedings - International Symposium on Software Reliability Engineering, ISSRE | Year: 2010

Software systems running continuously for a long time tend to show degrading performance and an increasing failure occurrence rate, due to error conditions that accrue over time and eventually lead the system to failure. This phenomenon is usually referred to as Software Aging. Several long-running mission and safety critical applications have been reported to experience catastrophic aging-related failures. Software aging sources (i.e., aging-related bugs) may be hidden in several layers of a complex software system, ranging from the Operating System (OS) to the user application level. This paper presents a software aging analysis at the Operating System level, investigating software aging sources inside the Linux kernel. Linux is increasingly being employed in critical scenarios; this analysis intends to shed light on its behaviour from the aging perspective. The study is based on an experimental campaign designed to investigate the kernel internal behaviour over long running executions. By means of a kernel tracing tool specifically developed for this study, we collected relevant parameters of several kernel subsystems. Statistical analysis of collected data allowed us to confirm the presence of aging sources in Linux and to relate the observed aging dynamics to the monitored subsystems behaviour. The analysis output allowed us to infer potential sources of aging in the kernel subsystems. © 2010 IEEE. Source

Bovenzi A.,University of Naples Federico II | Cotroneo D.,University of Naples Federico II | Pietrantuono R.,University of Naples Federico II | Russo S.,University of Naples Federico II | Russo S.,Complesso Universitario Monte SantAngelo
Proceedings - International Symposium on Software Reliability Engineering, ISSRE | Year: 2011

The phenomenon of software aging is increasingly recognized as a relevant problem of long-running systems. Numerous experiments have been carried out in the last decade to empirically analyze software aging. Such experiments, besides highlighting the relevance of the phenomenon, have shown that aging is tightly related to the applied workload. However, due to the differences among the experimented applications and among the experimental conditions, results of past studies are not comparable to each other. This prevent from drawing general conclusions (e.g., about the aging-workload relationship), and from comparing systems from the aging perspective. In this paper, we propose a procedure to carry out aging experiments in different applications for: i) assessing aging trend of the individual systems, as well as assessing differences among them (i.e., obtaining comparable results), ii) inferring workload-aging relationships from experiments performed on different applications, by highlighting the most relevant workload parameters. The procedure is applied, through a set of long-running experiments, to three real-scale software applications, namely Apache Web Server, James Mail Server, and CARDAMOM, a middleware for the development of air traffic control (ATC) systems. © 2011 IEEE. Source

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