A study on performance measures for auto-scaling CPU-intensive containerized applications

Autoscaling of containers can leverage performance measures from the different layers of the computational stack. This paper investigate the problem of selecting the most appropriate performance measure to activate auto-scaling actions aiming at guaranteeing QoS constraints. First, the correlation between absolute and relative usage measures and how a resource allocation decision can be influenced by them is analyzed in different workload scenarios. Absolute and relative measures could assume quite different values. The former account for the actual utilization of resources in the host system, while the latter account for the share that each container has of the resources used. Then, the performance of a variant of Kubernetes’ auto-scaling algorithm, that transparently uses the absolute usage measures to scale-in/out containers, is evaluated through a wide set of experiments. Finally, a detailed analysis of the state-of-the-art is presented

A Fiber Optical Sensor For Non-Contact Vibration Measurements

This paper describes an intensity based optical sensor for the evaluation of accelerations from non-contact displacement measurements. Plastic optical fibers are used to collect the reflected light from several points on the vibrating surface, allowing the reconstruction of the vibration distribution. Two compensation techniques to reduce systematic effects due to the target reflectivity are also described and compared: one is based on the spectral analysis of the received optical signal and the other takes advantage of a reference displacement sensor. Experimental results in real conditions during vibration tests have demonstrated the capability to measure sub-micrometer vibration amplitudes up to about 40 kH

Optimal mobility-aware admission control in content delivery networks

This paper addresses the problem of mobility management in Content Delivery Networks (CDN). We introduce a CDN architecture where admission control is performed at mobility aware access routers. We formulate a Markov Modulated Poisson Decision Process for access control that captures the bursty nature of data and packetized traffic together with the heterogeneity of multimedia services. The optimization of performance parameters, like the blocking probabilities and the overall utilization, is conducted and the structural properties of the optimal solutions are also studied. Heuristics are proposed to encompass the computational difficulties of the optimal solution when several classes of multimedia traffic are considered

Agent-based modeling of interdependent critical infrastructures

Critical interdependent infrastructures are complex systems, that if damaged or disrupted can seriously compromise the welfare of our society. This research, part of the CRESCO project, deal with the problem of interdependent critical infrastructures analysis, proposing an agent-based modelling and simulation solution. The approach we put forward, named Federated-ABMS, relies on discrete agent-based modelling and simulation and federated simulation. Federated-ABMS provides a formalism to model compound complex systems, composed of interacting systems, as federation of interacting agents and sector specific simulation models. This paper describes the formal model as well it outlines the steps that characterise the Federated-ABMS methodology, here applied to a target system, composed of a communication network and of a power grid. Moreover we conclude the paper with a thorough discussion of implementation issues

Multilabel Classification with R Package mlr

We implemented several multilabel classification algorithms in the machine learning package mlr. The implemented methods are binary relevance, classifier chains, nested stacking, dependent binary relevance and stacking, which can be used with any base learner that is accessible in mlr. Moreover, there is access to the multilabel classification versions of randomForestSRC and rFerns. All these methods can be easily compared by different implemented multilabel performance measures and resampling methods in the standardized mlr framework. In a benchmark experiment with several multilabel datasets, the performance of the different methods is evaluated.Comment: 18 pages, 2 figures, to be published in R Journal; reference correcte

Assessment of a Dual-Wavelength Compensation Technique for Displacement Sensors Using Plastic Optical Fibers

The paper analyzes the performance of a dual-wavelength technique devised to compensate power fluctuations in intensity-modulated plastic optical fiber sensors, which were specifically conceived for the measurement of displacements in industrial and civil applications. These sensors retrieve the displacement from the variation of the attenuation along the light path and use two signals at different wavelengths to compensate for the effects of parasitic quantities, such as temperature and strains along the fiber. The theoretical behavior of the compensation technique is presented, and the results of experiments carried out with different combinations of signal wavelengths and plastic fibers are reported. The experimental setup has proved that, by proper choice of the compensation signal wavelength, it is possible to monitor displacements in the range (0 to 10) mm, even for low received power and under severe perturbation conditions, thus significantly improving the long-term stability of the sensor

A syntactic analysis of the subject clitic a in the Friulian variety of Campone

This article presents a syntactic analysis of the third person subject clitic a in Camponese, a heretofore unstudied Friulian variety. Following Poletto's (2000) map of subject clitics, we argue that it bears [+third person] features, and is, in fact, the spell-out of the functional head Subj°, located in the highest projection of TP (following Rizzi & Shlonsky 2007). In the first part of the article, we offer a detailed description of the distribution and syntactic properties of the subject clitic a, identifying its position in relation to the other elements that occur in the CP and TP. In the second part we discuss two proposals put forward to account for split clitics like a-l in the related variety of Forni di Sotto, where a and l are held to be part of a single clitic al (Manzini & Savoia 2009, Calabrese & Pescarini 2014). We show that such an account is incompatible with the case of Campone, where the clitics a and l are clearly separate: l is a [uφ]-clitic (Roberts 2010) and is located lower in the TP than the clitic a. We conclude with an analysis, which proposes the integration of Poletto's (2000) typology with a fifth type, corresponding to the clitic a of Campone

Displacement and acceleration measurements in vibration tests using a fiber optic sensor

This paper discusses the evaluation of displacements and accelerations from noncontact displacement measurements using a low-cost plastic fiber-optic sensor. Issues about sensor calibration in the presence of nonuniform targets, which is a situation occurring in many practical applications such as vibration tests of printed circuit board assemblies, are analyzed. Furthermore, a procedure to contemporaneously calibrate several optical sensors to allow mapping the vibration amplitude and acceleration distributions in a simple and low-cost way is also disclosed. The proposed calibration procedure is particularly effective since it requires just one reference accelerometer, which is actually already available in typical vibration test facilities. Experimental results obtained under real conditions during a sinusoidal vibration test are also provide

Subject-specific Bradley-Terry-Luce Models with Implicit Variable Selection

The Bradley-Terry-Luce (BTL) model for paired comparison data is able to obtain a ranking of the objects that are compared pairwise by subjects. The task of each subject is to make preference decisions in favor of one of the objects. This decision is binary when subjects prefer either the first object or the second object, but can also be ordinal when subjects make their decisions on a Likert scale. Since subject-specific covariates, which reflect characteristics of the subject, may affect the preference decision, it is essential to incorporate subject-specific covariates into the model. However, the inclusion of subject-specific covariates yields a model that contains many parameters and thus estimation becomes challenging. To overcome this problem, we propose a procedure that is able to select and estimate only relevant variables