In the age of globalization and international collaboration, collaborative data sharing is crucial for computer-aided research. There is a growing demand for spontaneous, short-lived, and fine-grained collaboration acts that could be satisfied by a decentralized platform for the management of entities (users, groups, datasets). Our research is based on a pre-existing concept of such a decentralized platform, called the decentralized entity persistence layer (DEPL). We describe a novel architecture extending DEPL, called DEPL-DA, which introduces an idea of decentralized authority, allowing entities to be managed collectively by multiple organizations, at the same time ensuring fault tolerance and improving availability. Our proposal utilizes a synergy between consensus and atomic commitment protocols (AC&C) providing decentralization of authority over entities, at the same time providing means to perform atomic modifications of entities spanning across multiple authoritative domains. We propose two approaches to the integration of AC&C: competitive and cooperative, and implement them based on several existing AC&C protocols. The evaluation shows the differences between approaches and protocols used, as well as the fact that both approaches are viable and offer latencies acceptable by operations related to entity management.

In order to realize collaboration on a global scale, academic research requires often large quantities of data to be shared between geographically dispersed organizations.The requirement to protect and govern data in a network of loosely coupled, autonomous institutions is an incentive for decentralized solutions, where the participants are in full control of their data without trusting a third-party provider to store and process the data.In order to increase data availability and fault tolerance in decentralized collaborative systems, we propose a layer, which is based on replication and decentralized authority over the data.The solution consists of an idea of peer-sets, which are groups of peers implementing collective data management, a consensus protocol which synchronizes a distributed ledger between peers, and an atomic commitment protocol used to implement optional two-way references between documents.This architecture may be utilized in various decentralized collaborative data-sharing systems, such as Onedata.

Background and Objective. Paul Ekman has demonstrated that we can estimate emotions on the basis of individual facial muscles movements. However, there is a lack of information in the literature about correlation between eye movements and facial emotions. Our objective was to find out whether emotion could be also visible in the dynamical properties of the eye movements. Methods. We have performed our experiment in two sessions related to different video presentations: 1) a reference session with all emotions presentation, and 2) the main session showing presentation of some specific emotions. During both sessions, we have video recordings of the subjects’ face expressions (FE) and eye movements (EM). We have calculated parameters of FE and EM dynamical changes and content of the noise. On this basis, by using time changes of EM, we have predicted 6 different face emotions. Results. We have recorded face expressions of 49 subjects who had the strongest responses to Happiness and Contempt facial emotions. We found statistically significant differences in parameters’ values describing FE and EM between the reference and the main sessions trials. Parameters connected to the Chaos showed highly positive correlations with Happiness, while both the Linear and the Noise components were mostly negatively correlated with this emotion. We achieved highest results with help of the K-Nearest Neighbors algorithm obtaining: Accuracy of 0.89 (+/- 0.01) with the ROC-AUC score of 0.88 (F1 = 0.89), Precision = 0.85, Sensitivity / Recall = 0.93, Specificity = 0.82. Conclusions. We have observed that when the intensity of the Happiness increases, the eye movements become more chaotic and behave less noisy. We see possibilities for use of presented methods as a support for predictions in face expressions, when the lower part of the face is partially hidden, e.g. by a protective mask worn during the COVID epidemic. This could also be a method of confirming the authenticity of the Happiness mimicry, because it would be difficult to voluntarily correlate eye movements with certain levels of the Chaos.

The observation of current trends in data access, especially in the field of scientific computations, shows that global data access that crosses federation boundaries is highly desirable. However, administrative constraints require that data centers remain autonomous, which effectively eliminates the possibility of cooperation. To overcome this, we plan to establish an open network of cooperating data providers. In this paper, we address the issue of data access control for such network. Our proposition is to use a synergy of hybrid peer-to-peer architecture, decentralized identity and access management, metadata synchronization protocol and trust driven authorization flow. The proposed solution is discussed using real-life use-cases concerning cross-federation data access.

Summary Sensitivity analysis is widely used in numerical simulations applied in industry. The robustness of such applications is crucial, which means they have to be fast and precise at the same time. However, the conventional approach to sensitivity analysis assumes realization of multiple execution of computationally intensive simulations to discover input/output dependencies. In this paper, we present a novel computational approach for performing large‐scale sensitivity analysis integrated with an extended platform for parameter studies – Scalarm – to make use of modern e‐infrastructures for distribution and parallelization purposes, profitable for complicated industrial problems. Copyright © 2016 John Wiley & Sons, Ltd.

Using multiple Clouds as a single environment to conduct simulation-based virtual experiments at a large-scale is a challenging problem. This paper describes how this can be achieved with the Scalarm platform in the context of data farming. In particular, a use case with a private Cloud combined with public, commercial Clouds is studied. We discuss the current architecture and implementation of Scalarm in terms of supporting different infrastructures, and propose how it can be extended in order to attain a unification of different Clouds usage. We discuss different aspects of the Cloud usage unification including: scheduling virtual machines, authentication, and virtual machine state monitoring. An experimental evaluation of the presented solution is conducted with a genetic algorithm solving the well-known Travel Salesman Problem. The evaluation uses three different resource configurations: using only public Cloud, using only private Cloud, and using both public and private Clouds.

Growing role of the cooperation between companies around the world causes the rise of meaning of the SLA agreements which are negotiated among companies. These agreements usually require a reliable and robust monitoring process, since their fulfilment is crucial for the coherence of the cooperation. In this paper we present the application of the ESB integration architecture in the specialized distributed monitoring system-the FiVO SLA monitoring system-which is used to monitor the resources and services shared among the cooperating companies. Different deployment models of this system are proposed and the results from their performance tests are presented.

Benefits of using ontologies for automatic composition of workflow application, become evident when considering knowledge evolution influencing possibility of new workflows composition. The evolution of knowledge in the case of ontology descriptionmeans both evolution of the instance registries as well as evolution of schemas to which the instance descriptions conform. An approach to semi-automated knowledge evolution referred to ontology schemas applied to the process of new Grid service registration is introduced in the paper. The presented study makes extensive use of ontology alignment methods.