On the economics of energy consumption in 4G networks: the case of Spain

Reducing energy consumption is one of the main challenges in most countries. For example, European Member States agreed to reduce greenhouse gas (GHG) emissions by 20% in 2020 compared to 1990 levels (EC 2008). Considering each sector separately, ICTs account nowadays for 2% of total carbon emissions. This percentage will increase as the demand of communication services and applications steps up. At the same time, the expected evolution of ICT-based developments - smart buildings, smart grids and smart transportation systems among others - could result in the creation of energy-saving opportunities leading to global emission reductions (Labouze et al. 2008), although the amount of these savings is under debate (Falch 2010). The main development required in telecommunication networks ?one of the three major blocks of energy consumption in ICTs together with data centers and consumer equipment (Sutherland 2009) ? is the evolution of existing infrastructures into ultra-broadband networks, the so-called Next Generation Networks (NGN). Fourth generation (4G) mobile communications are the technology of choice to complete -or supplement- the ubiquitous deployment of NGN. The risk and opportunities involved in NGN roll-out are currently in the forefront of the economic and policy debate. However, the issue of which is the role of energy consumption in 4G networks seems absent, despite the fact that the economic impact of energy consumption arises as a key element in the cost analysis of this type of networks. Precisely, the aim of this research is to provide deeper insight on the energy consumption involved in the usage of a 4G network, its relationship with network main design features, and the general economic impact this would have in the capital and operational expenditures related with network deployment and usage.

Techno-economics of ICT infrastructures: The impact of (user, network) requirements

- Towards a methodology for prospective deployment of ICT infrastructures - (Technologies & Architectures) - Key deployment parameters (network requirements) - User requirements - A proposal for Cost‐Benefit Analysis

Sistema regional de innovación para el fortalecimiento de la I+D+i, en el sector industrial del estado Bolívar, Venezuela

El Estado Bolívar cuenta con excelentes recursos de materias primas tales como el mineral de hierro y bauxita, y de profesionales especializados, los cuales representan oportunidades para mejorar las ventajas competitivas de una de las zonas industriales más grande de Latinoamérica. Para aprovechar tales ventajas se debe cambiar el modelos de política industrial actual de exportar en el mayor porcentaje productos primarios y semielaborados a través de las empresa básicas instaladas en la zona, a otro modelo económico basado en política de innovación para la diversificación de nuevos productos, soportados en la transformación de las Pequeñas y Medianas Industrias (PYMIS) del estado Bolívar, consolidando las empresas en organizaciones innovadoras que generen, aporten o adapten los conocimientos científicos y tecnológicos, obteniendo nuevos productos o mejoras de procesos con un alto contenido de valor agregado. Estos cambios avanzarán en la medida que se logren articular e integrar los actores que forman parte del Sistema Regional de Innovación (SRI). El presente proyecto se planteo como objetivo diseñar estrategias para desarrollar y articular las capacidades de los actores del SRI para el fortalecimiento de la I+D+i en el sector industrial de las cadenas siderúrgicas y del aluminio del estado Bolívar.

Efficient parallelization of a regional ocean model for the western Mediterranean Sea

This paper focuses on the parallelization of an ocean model applying current multicore processor-based cluster architectures to an irregular computational mesh. The aim is to maximize the efficiency of the computational resources used. To make the best use of the resources offered by these architectures, this parallelization has been addressed at all the hardware levels of modern supercomputers: firstly, exploiting the internal parallelism of the CPU through vectorization; secondly, taking advantage of the multiple cores of each node using OpenMP; and finally, using the cluster nodes to distribute the computational mesh, using MPI for communication within the nodes. The speedup obtained with each parallelization technique as well as the combined overall speedup have been measured for the western Mediterranean Sea for different cluster configurations, achieving a speedup factor of 73.3 using 256 processors. The results also show the efficiency achieved in the different cluster nodes and the advantages obtained by combining OpenMP and MPI versus using only OpenMP or MPI. Finally, the scalability of the model has been analysed by examining computation and communication times as well as the communication and synchronization overhead due to parallelization.