Ayala Rodrigo, José Luis

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First Name
José Luis
Last Name
Ayala Rodrigo
Universidad Complutense de Madrid
Faculty / Institute
Arquitectura de Computadores y Automática
Arquitectura y Tecnología de Computadores
UCM identifierScopus Author IDDialnet IDGoogle Scholar ID

Search Results

Now showing 1 - 10 of 14
  • Publication
    Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments
    (MDPI, 2012-08-03) Zapater, Marina; Sanchez, Cesar; Ayala Rodrigo, José Luis; Moya, Jose M.; Risco Martín, José Luis
    Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.
  • Publication
    Receptor Software de bajo coste e Interfaz Computerizada para el Estudio Práctico de las Comunicaciones Radioeléctricas
    (2015-01-19) Del Barrio García, Alberto Antonio; Ayala Rodrigo, José Luis; Hermida Correa, Román
    En este proyecto se ha desarrollado una plataforma de bajo coste de Software Defined Radio (SDR, Receptor Radio Software) que consta de una componente hardware y otra software, ambas libres. El uso de la interfaz software nos ha permitido modificar distintos parámetros de transmisión de la señal (filtrado de armónicos, frecuencia de muestreo, demodulador, etc.) y estudiar su impacto en la calidad de la señal mediante la síntesis audible a través del altavoz del PC.
  • Publication
    A Link Quality Estimator for Power-Efficient Communication over On-Body Channels
    (2014) Recas Piorno, Joaquín; Ayala Rodrigo, José Luis; Vallejo, Mónica
    The human body has an important effect on the performance of on-body wireless communication systems. Given the dynamic and complex nature of the on-body channels, link quality estimation models are crucial in the design of mobility management protocols and power control protocols. In order to achieve a good estimation of link quality in WBSNs, we combine multiple body-related factors into a model that includes: the transmission power, the body position, the body shape and composition characteristics and the received signal strength indicator (RSSI) as an indicator of link quality. In this paper, we propose the Anfis Link Quality Estimator (A-LQE) that has been trained with RSSI values measured at different transmission power levels in a sample of 37 human subjects. Once the accuracy and reliability of our proposed model have been analysed, we apply the model to adapt the transmission power to the link characteristics for energy optimization. The obtained average energy savings reach the 26% in comparison with the maximum transmission power mode.
  • Publication
    Leakage-Aware Cooling Management for Improving Server Energy Efficiency
    (IEEE Computer Soc., 2015-10) Zapater Sancho, Marina; Ayala Rodrigo, José Luis; Tuncer, Ozan; Moya, José M.; Vaidyanathan, Kalyan; Gross, Kenny; Coskun, Ayse K.
    The computational and cooling power demands of enterprise servers are increasing at an unsustainable rate. Understanding the relationship between computational power, temperature, leakage, and cooling power is crucial to enable energy-efficient operation at the server and data center levels. This paper develops empirical models to estimate the contributions of static and dynamic power consumption in enterprise servers for a wide range of workloads, and analyzes the interactions between temperature, leakage, and cooling power for various workload allocation policies. We propose a cooling management policy that minimizes the server energy consumption by setting the optimum fan speed during runtime. Our experimental results on a presently shipping enterprise server demonstrate that including leakage awareness in workload and cooling management provides additional energy savings without any impact on performance.
  • Publication
    Support System to Improve Reading Activity in Parkinson’s Disease and Essential Tremor Patients
    (MDPI, 2017-05-03) Parrales Bravo, Franklin; Barrio García, Alberto Antonio del; Gallego de la Sacristana, Mercedes; López Manzanares, Lydia; Vivancos, José; Ayala Rodrigo, José Luis
    The use of information and communication technologies (ICTs) to improve the quality of life of people with chronic and degenerative diseases is a topic receiving much attention nowadays. We can observe that new technologies have driven numerous scientific projects in e-Health, encompassing Smart and Mobile Health, in order to address all the matters related to data processing and health. Our work focuses on helping to improve the quality of life of people with Parkinson’s Disease (PD) and Essential Tremor (ET) by means of a low-cost platform that enables them to read books in an easy manner. Our system is composed of two robotic arms and a graphical interface developed for Android platforms. After several tests, our proposal has achieved a 96.5% accuracy for A4 80 gr non-glossy paper. Moreover, our system has outperformed the state-of-the-art platforms considering different types of paper and inclined surfaces. The feedback from ET and PD patients was collected at “La Princesa” University Hospital in Madrid and was used to study the user experience. Several features such as ease of use, speed, correct behavior or confidence were measured via patient feedback, and a high level of satisfaction was awarded to most of them. According to the patients, our system is a promising tool for facilitating the activity of reading.
  • Publication
    Arquitecturas dinámica de redes inalámbricas en banda libre para la ejemplificación de conceptos de transmisión en aplicaciones de “Internet Of Things”
    (2016-01) Ayala Rodrigo, José Luis; Pagán Ortiz, Josué; Zapater Sancho, Marina; Del Barrio García, Alberto; Hermida Correa, Román
    Este proyecto de innovación educativa propone una metodología práctica y un equipamiento novedoso para la docencia de la asignatura de Redes y Servicios de Telecomunicación II impartida en tercer curso del Grado en Ingeniería Electrónica de Comunicaciones. Mediante la incorporación de elementos prácticos a la docencia como los recogidos en este proyecto, se pretende ahondar en los conceptos de uso espectral, acceso a un canal compartido, enrutamiento, topología de red, relación consumo vs. potencia de transmisión, etc. desde una perspectiva práctica que facilite el aprendizaje y despierte la curiosidad del alumnado. Para ello, se propondrá un despliegue de nodos inalámbricos, y un entorno de programación de éstos, que permita la evaluación de los contenidos antes descritos.
  • Publication
    Server Power Modeling for Run-time Energy Optimization of Cloud Computing Facilities.
    (Elsevier Science BV, 2014) Arroba, Patricia; Risco Martín, José Luis; Zapater Sancho, Marina; Moya, José Manuel; Ayala Rodrigo, José Luis; Olcoz Herrero, Katzalin
    As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simultaneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.
  • Publication
    Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data
    (MDPI, 2015-06-30) Pagán, Josué; De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco Martín, José Luis; Vivancos Mora, J.; Moya, José M.; Ayala Rodrigo, José Luis
    Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives.
  • Publication
    Runtime data center temperature prediction using Grammatical Evolution techniques
    (Elsevier Science BV, 2016-08-16) Zapater, Marina; Risco Martín, José Luis; Arroba, Patricia; Ayala Rodrigo, José Luis; Moya, José M.; Hermida Correa, Román
  • Publication
    Energy-aware task scheduling in data centers using an application signature
    (Elsevier, 2021-12-08) Salinas Hilburg, Juan Carlos; Zapater, Marina; Moya, José M.; Ayala Rodrigo, José Luis
    Data centers are power hungry facilities. Energy-aware task scheduling approaches are of utmost importance to improve energy savings in data centers, although they need to know beforehand the energy consumption of the applications that will run in the servers. This is usually done through a full profiling of the applications, which is not feasible in long-running application scenarios due to the long execution times. In the present work we use an application signature that allows to estimate the energy without the need to execute the application completely. We use different scheduling approaches together with the information of the application signature to improve the makespan of the scheduling process and therefore improve the energy savings in data centers. We evaluate the accuracy of using the application signature by means of comparing against an oracle method obtaining an error below 1.5%, and Compression Ratios around 39.7 to 45.8.