Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitorin

Mathematical modelling of operating cycles for road vehicles

Difficulties that commercial vehicles are facing in meeting regulation standards require ad-hoc solutions. Emissions can be dramatically lowered if the characteristics of the transport application are known in advance. To tailor the vehicle\u27s specification towards the use-case, however, a representative description of the mission, together with the surroundings, is needed.Where many conventional approaches fail, the operating cycle format (OC) has shown promising results in describing road operations in a way which is completely independent of both vehicle and driver.More specifically, the framework consists of three levels of representation. The first, called the bird\u27s eye view, serves mainly as a classification tool, and makes use of metrics and labels to completely characterise the overall application of a vehicle during its lifetime. The second description, the stochastic operating cycle (sOC), condenses the main properties of a road operation using elementary statistics. It is conceived as an intermediate representation with a higher degree of accuracy. Finally, the deterministic operating cycle (dOC) is the most detailed description of a transport mission, and collects deterministic models to be used in simulation.In previous studies, the OC format was demonstrated to work in theory, but some margins for improvement could still be identified. Furthermore, the utility and benefits deriving from the use of the OC in concrete situations was explored only partially.The main objective of this thesis consists in extending the OC representation to include stochastic models for weather and traffic, which were missing in the original formulation. The new models are built to be parsimonious and to allow ease of parametrisation and implementation starting from real data. This enables to reproduce and simulate realistic environments where a transport mission can take place, with a substantial gain in accuracy.The second purpose of this work is to showcase how the OC concept can be used in practical applications involving real customers. A case study is presented to exemplify the advantages connected with the use of the OC description in product selection, prospecting a potential reduction of fuel consumption and emission of about 10%

Chemical evolution in a model for the joint formation of quasars and spheroids

Direct and indirect pieces of observational evidence point to a strong connection between high-redshift quasars and their host galaxies. In the framework of a model where the shining of the quasar is the episode that stops the formation of the galactic spheroid inside a virialized halo, it has been proven possible to explain the submillimetre source counts together with their related statistics and the local luminosity function of spheroidal galaxies. The time delay between the virialization and the quasar manifestation required to fit the counts is short and incresing with decresing the host galaxy mass. In this paper we compute the detailed chemical evolution of gas and stars inside virialized haloes in the framework of the same model, taking into account the combined effects of cooling and stellar feedback. Under the assumption of negligible angular momentum, we are able to reproduce the main observed chemical properties of local ellipticals. In particular, by using the same duration of the bursts which are required in order to fit the submillimetre source counts, we recover the observed increase of the Mg/Fe ratio with galactic mass. Since for the most massive objects the assumed duration of the burst is Tburst < 0.6 Gyr, we end up with a picture for elliptical galaxy formation in which massive spheroids complete their assembly at early times, thus resembling a monolithic collapse, whereas smaller galaxies are allowed for a more prolonged star formation, thus allowing for a more complicated evolutionary history.Comment: 17 pages, 11 figures, accepted for publication in MNRA

An Approach for Securing Cloud-Based Wide Area Monitoring of Smart Grid Systems

Computing power and flexibility provided by cloud technologies represent an opportunity for Smart Grid applications, in general, and for Wide Area Monitoring Systems, in particular. Even though the cloud model is considered efficient for Smart Grids, it has stringent constraints in terms of security and reliability. An attack to the integrity or confidentiality of data may have a devastating impact for the system itself and for the surrounding environment. The main security risk is represented by malicious insiders, i.e., malevolent employees having privileged access to the hosting machines. In this paper, we evaluate a powerful hardening approach that could be leveraged to protect synchrophasor data processed at cloud level. In particular, we propose the use of homomorphic encryption to address risks related to malicious insiders. Our goal is to estimate the feasibility of such a security solution by verifying the compliance with frame rate requirements typical of synchrophasor standards

Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures

The Dempster-Shafer (DS) theory of evidence has significant weaknesses when dealing with conflicting information sources, as demonstrated by preeminent mathematicians. This problem may invalidate its effectiveness when it is used to implement decision-making tools that monitor a great number of parameters and metrics. Indeed, in this case, very different estimations are likely to happen and can produce unfair and biased results. In order to solve these flaws, a number of amendments and extensions of the initial DS model have been proposed in literature. In this work, we present a Fraud Detection System that classifies transactions in a Mobile Money Transfer infrastructure by using the data fusion algorithms derived from these new models. We tested it in a simulated environment that closely mimics a real Mobile Money Transfer infrastructure and its actors. Results show substantial improvements of the performance in terms of true positive and false positive rates with respect to the classical DS theory

Runtime model checking for sla compliance monitoring and qos prediction

Sophisticated workflows, where multiple parties cooperate towards the achievement of a shared goal are today common. In a market-oriented setup, it is key that effective mechanisms be available for providing accountability within the business process. The challenge is to be able to continuously monitor the progress of the business process, ideally,anticipating contract breaches and triggering corrective actions. In this paper we propose a novel QoS prediction approach which combines runtime monitoring of the real system with probabilistic model-checking on a parametric system model. To cope with the huge amount of data generated by the monitored system, while ensuring that parameters are extracted in a timing fashion, we relied on big data analytics solutions. To validate the proposed approach, a prototype of the QoS prediction framework has been developed, and an experimental campaign has been conducted with respect to a case study in the field of Smart Grids

Transient wheel-rail rolling contact theories

This paper provides an overview of different theories to analyse unsteady rolling contact phenomena between wheel and rail: the exact formulation by Kalker, the simplified model based on the Winkler approximation, and the recent two-regime model. The classic solution to the transient problem derived by Kalker using the complete theory of elasticity is first recalled. The more involved situation of combined creepages and spin is analysed using Kalker’s simplified model. Analytical solutions are reported in integral form concerning the time-varying and constant creepages. Qualitative results are additionally provided for the case of a time-varying contact patch. Finally, a novel theory, which describes the transient evolution of the force-creepage characteristics using a system of ordinary differential equations (ODEs), is introduced

Rolling of a cylinder with slip-dependent friction: The Carter solution revisited

The problem of a wheel under tractive rolling of Carter is revisited here by assuming a slip-dependent friction force. By assuming a change from static to dynamic friction coefficient occurs over a small distance, we develop effectively a fracture mechanics solution for the shear tractions, which describes some aspects of “falling friction” creepage forces which are commonly observed experimentally. Possible agreement with experiments is discussed, suggesting that friction may include also rate-dependent effects. A simple strip theory is used to estimate 3D effects, which reduce the strength of the singularity at the edges being the peak pressure lower there