News

Cuándo:  martes 19 de junio a las 16:00

Dónde: sala B-225 de la ETSIT (UPM).

Ponente: Jürgen Dunkel

Título: Learning Complex Event Processing Rules with Genetic Programming

Resumen: Complex Event Processing (CEP) is an established software technology to extract relevant information from massive data streams. Currently, domain experts have to determine manually CEP rules that define a situation of interest. However, often CEP rules cannot be formulated by experts, because the relevant interdependencies and relations between the data are not explicitly known, but inherently hidden in the data streams. To cope with this problem, we present a new learning approach for CEP rules, which is based on Genetic Programming. We discuss in detail the different building blocks of Genetic Programming and how to adjust them to CEP rule learning. The extensive experiments, with synthetic data as well a real world data, show, that Genetic Programming has a high potential for learning CEP rules. In most of our experiments we could derive CEP rules with a nearly perfect recall and precision. 

During 13th and 14th of June, Trivalent consortium is holding the 1st year meeting in Rome. The main goals of this meeting  are: i)  sharing the progress of every task and work package; ii)  look for collaborations across work packages and iii) plan and schedule next steps

The main results of GSI are published here: http://www.gsi.dit.upm.es/index.php/es/trivalent

Este viernes 15 de junio se leen varios trabajos fin de titulación en la B-225, estáis todos invitados. Si estáis interesados, podéis encontrar las memorias y vídeos en la web.

The paper Towards an Autonomic Bayesian Fault Diagnosis Service for SDN Environments based on a Big Data Infrastructure, by Fernando Benayas, Álvaro Carrera and Carlos A. Iglesias, has been presented at the The Fifth IEEE International Conference on Software Defined Systems (SDS-2018).

The SDS 2018 aims to investigate the opportunities and in all aspects of Software Defined Systems (SDS). In addition, it seeks for novel contributions that help mitigating SDS challenges. That is, the objective of SDS 2018 is to provide a forum for scientists, engineers, and researchers to discuss and exchange new ideas, novel results and experience on all aspects of Software Defined Systems.

Abstract. Software Defined Networks (SDN) are gaining momentum as a solution for current and future networking issues. Its programmability and centralised control enables a more dynamic management of the network. But this feature introduces the cost of a potential increase in failures, since every modification introduced on the control plane is a new possibility for failures to appear and cause a decrement of the quality for the offered service. Following a classical approach, this kind of problems could be solved increasing the number of high skilled human operators, which would dramatically increase network operation cost. Our approach is to apply Machine Learning and Data Analysis for monitoring and diagnosis SDN networks with the goal of automating these tasks. In this paper, we present an architecture for a self-diagnosis service which is deployed on top of a SDN management platform. In addition, a prototype of the proposed service with different diagnosis models for SDN networks has been developed. The evaluation shows encouraging results which will be explored in future works.

The SDS-2018 conference was held April 23-26, at Barcelona, Spain.

The article "An Emotion Aware Task Automation Architecture Based on Semantic Technologies for Smart Offices" by Sergio Muñoz, Óscar Araque, J. Fernando Sánchez-Rada y Carlos A. Iglesias has been published in Sensors, indexed by JCR Q1.

Abstract. The evolution of the Internet of Things leads to new opportunities for the contemporary notion of smart offices, where employees can benefit from automation to maximize their productivity and performance. However, although extensive research has been dedicated to analyze the impact of workers’ emotions on their job performance, there is still a lack of pervasive environments that take into account emotional behaviour. In addition, integrating new components in smart environments is not straightforward. To face these challenges, this article proposes an architecture for emotion aware automation platforms based on semantic event-driven rules to automate the adaptation of the workplace to the employee’s needs. The main contributions of this paper are: (i) the design of an emotion aware automation platform architecture for smart offices; (ii) the semantic modelling of the system; and (iii) the implementation and evaluation of the proposed architecture in a real scenario.

The article is available at: http://www.mdpi.com/1424-8220/18/5/1499