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Data centres increase their size and complexity due to the increasing amount of heterogeneous work loads and patterns to be served. Such a mix of various purpose workloads makes the optimisation of resource management systems according to temporal or application-level patterns difficult. Data centre operators have developed multiple resource-management models to improve scheduling perfor mance in controlled scenarios. However, the constant evolution of the workloads makes the utilisation of only one resource-management model sub-optimal in some scenarios. In this work, we propose: (a) a machine learning regression model based on gradient boosting to pre dict the time a resource manager needs to schedule incoming jobs for a given period; and (b) a resource management model, Boost, that takes advantage of this regression model to predict the scheduling time of a catalogue of resource managers so that the most performant can be used for a time span. The benefits of the proposed resource-management model are analysed by comparing its scheduling performance KPIs to those provided by the two most popular resource-management models: two level, used by Apache Mesos, and shared-state, employed by Google Borg. Such gains are empirically eval uated by simulating a hyper-scale data centre that executes a realistic synthetically generated workload that follows real-world trace patterns Ministerio de Ciencia e Innovación RTI2018-098062-A-I00

Achieving efficiency both in terms of resource utilisation and energy consumption is acomplex challenge, especially in large-scale wide-purpose data centers that serve cloud- computing services. Simulation presents an appropriate solution for the development andtesting of strategies that aim to improve efficiency problems before their applications inproduction environments. Various cloud simulators have been proposed to cover differentaspects of the operation environment of cloud-computing systems. In this paper, we define the SCORE tool, which is dedicated to the simulation of energy-efficient monolithicand parallel-scheduling models and for the execution of heterogeneous, realistic and synthetic workloads. The simulator has been evaluated through empirical tests. The results ofthe experiments confirm that SCORE is a performant and reliable tool for testing energy- efficiency, security, and scheduling strategies in cloud-computing environments. European Cooperation in Science and Technology (COST) COST Action IC1406

This paper presents the architecture of an eco driving assistant. The assistant evaluates the fulfil ment of classic eco-driving advices such as: main tain a constant speed, driving at high gear, slow down smoothly and so on. In addition, the assistant issues advices based on the anticipation. Anticipa tion is the key of eco-driving. The assistant is ca pable of detecting traffic signs beforehand and it checks if the speed is suitable for not having to slow down sharply. In addition, the system propos es an optimal average speed according to the con ditions of the road. To model the environment where the vehicle is moving, we use an Android mobile device. These devices are ideal due to to their multiple network connections (Bluetooth, UTMS and WIFI) and sen sors (camera, acceleration sensor, GPS and so on). To obtain the vehicle’s parameters (speed, fuel consumption, RPM, etc.), we use the diagnostic port (OBD2). The proposed system can improve fuel consump tion and safety. In addition, it is independent of the type of vehicle. Ministerio de Ciencia e Innovación TIN2009-14378-C02-02 European Union REA FP7/2007-2013 n° 286533 Ministerio de Ciencia e Innovación HAUS IPT-2011-1049-430000

Energy saving involves two direct benefits: sustainability and cost reduction, both of which Information Technologies must be aware. In this context, clusters, grids and data centres represent the hungriest con sumers of energy. Energy-saving policies for these infrastructures must be applied in order to maximize their resources. The aim of this paper is to compare how efficient these policies are in each location of a grid infrastructure. By identifying efficient policies in each location and the slack in inputs and outputs of the inefficient locations, Data Envelopment Analysis presents a very useful technique for comparing and improving efficiency level. This work enables managers to uncover any misuse of resources so that cor rective action can be taken. Ministerio de Economía y Competitividad TIN2009-14378-C02-01 (ARTEMISA) Junta de Andalucía TIC-8052 (Simon)

This article is focused on adapting lighting conditions to user lighting preferences. A theoretical analysis of lighting conditions is carried out, and a case study is shown by means of the setup of an experimental environment and an empirical analysis of lighting conditions. Finally, a methodology for saving energy, which adjusts luminance to user preferences, is presented, and a study of the consump-tion results is given. Ministerio de Educación y Ciencia TSI2006-13390-C02-02 Junta de Andalucía TIC-2141

Although computer science and telecommunications have evolved from the 90’s to nowadays, the way people communicate each other through electronic devices has stuck since the appearance of the videoconference. The audiovisual interaction seems enough, but we think the sensation of presence gets higher when we allow the person who we are talking to, taking part in our environment using and enriching it. In that way, the interaction is improved with new sensations which come from outside of our device. In this article, we propose a communication service which provides not only videoconference, but manages the smart environment where the interlocutor of the communication is, allowing him to access to any device connected through domotic and/or wireless network. The application is developed under the OSGi open specification and it almost doesn’t imply any cost increase over the bandwidth used during communication. Once explaining the technical foundations, its diverse applications in ubiquitous meetings and on-line games will be commented.