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Dive into the research topics where Antonio Sánchez-Esguevillas is active.

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Featured researches published by Antonio Sánchez-Esguevillas.


IEEE Communications Surveys and Tutorials | 2014

A Survey on Electric Power Demand Forecasting: Future Trends in Smart Grids, Microgrids and Smart Buildings

Luis Hernández; Carlos Baladrón; Javier M. Aguiar; Belén Carro; Antonio Sánchez-Esguevillas; Jaime Lloret; Joaquim Massana

Recently there has been a significant proliferation in the use of forecasting techniques, mainly due to the increased availability and power of computation systems and, in particular, to the usage of personal computers. This is also true for power network systems, where energy demand forecasting has been an important field in order to allow generation planning and adaptation. Apart from the quantitative progression, there has also been a change in the type of models proposed and used. In the `70s, the usage of non-linear techniques was generally not popular among scientists and engineers. However, in the last two decades they have become very important techniques in solving complex problems which would be very difficult to tackle otherwise. With the recent emergence of smart grids, new environments have appeared capable of integrating demand, generation, and storage. These employ intelligent and adaptive elements that require more advanced techniques for accurate and precise demand and generation forecasting in order to work optimally. This review discusses the most relevant studies on electric demand prediction over the last 40 years, and presents the different models used as well as the future trends. Additionally, it analyzes the latest studies on demand forecasting in the future environments that emerge from the usage of smart grids.


IEEE Communications Magazine | 2013

A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants

Luis Hernández; Carlos Baladrón; Javier M. Aguiar; Belén Carro; Antonio Sánchez-Esguevillas; Jaime Lloret; David Chinarro; Jorge Gómez-Sanz; Diane J. Cook

Recent technological advances in the power generation and information technologies areas are helping to change the modern electricity supply system in order to comply with higher energy efficiency and sustainability standards. Smart grids are an emerging trend that introduce intelligence in the power grid to optimize resource usage. In order for this intelligence to be effective, it is necessary to retrieve enough information about the grid operation together with other context data such as environmental variables, and intelligently modify the behavior of the network elements accordingly. This article presents a multi-agent system model for virtual power plants, a new power plant concept in which generation no longer occurs in big installations, but is the result of the cooperation of smaller and more intelligent elements. The proposed model is not only focused on the management of the different elements, but includes a set of agents embedded with artificial neural networks for collaborative forecasting of disaggregated energy demand of domestic end users, the results of which are also shown in this article.


Sensors | 2012

A Semantic Autonomous Video Surveillance System for Dense Camera Networks in Smart Cities

Lorena Calavia; Carlos Baladrón; Javier M. Aguiar; Belén Carro; Antonio Sánchez-Esguevillas

This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.


Proceedings of the IEEE | 2013

IMS: The New Generation of Internet-Protocol-Based Multimedia Services

Antonio Sánchez-Esguevillas; Belén Carro; Gonzalo Camarillo; Yi-Bing Lin; Miguel A. García‐Martín; Lajos Hanzo

Legacy networks, both fixed and mobile, which were originally designed for voice communications, are progressively migrating to new infrastructures that promise to revolutionize the services offered. In this paper, we will cover this new generation of personal communication services, with an emphasis on the family of Internet protocol (IP)-based multimedia subsystem (IMS)-aided infrastructure that relies on the session initiation protocol (SIP). As a benefit, the end users will enjoy a new generation of personal communications services that are accessible anywhere and anytime. These services are directly related to the end users rather than to their diverse devices. It is anticipated that the new deployments of next-generation networks (all-IP based) will accelerate the adoption of the IMS technology.


Network Protocols and Algorithms | 2011

QoS Traffic Mapping between WiMAX and DiffServ Networks

Lorena Calavia; Carlos Baladrón; Javier M. Aguiar; Belén Carro; Antonio Sánchez-Esguevillas

Even when data communications are made inside an all-IP domain, in a hybrid network different mechanisms and policies for the management of Quality of Service (QoS) could coexist in the different access networks and nodes involved. Specifically, in the scenario considered along this work, a WiMAX segment is included inside an IP network using the DiffServ protocol for QoS management. The conflict arises due to the different ways to handle and label traffic flows provided by the DiffServ protocol and the native Medium Access Control (MAC) layer QoS mechanism implemented, and the lack of a one-to-one correspondence between the different classes of traffic defined in both domains. Along this work, a solution to this problem in the form of a traffic mapping system for QoS purposes is presented.


IEEE Access | 2017

Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things

Manuel Lopez-Martin; Belén Carro; Antonio Sánchez-Esguevillas; Jaime Lloret

A network traffic classifier (NTC) is an important part of current network monitoring systems, being its task to infer the network service that is currently used by a communication flow (e.g., HTTP and SIP). The detection is based on a number of features associated with the communication flow, for example, source and destination ports and bytes transmitted per packet. NTC is important, because much information about a current network flow can be learned and anticipated just by knowing its network service (required latency, traffic volume, and possible duration). This is of particular interest for the management and monitoring of Internet of Things (IoT) networks, where NTC will help to segregate traffic and behavior of heterogeneous devices and services. In this paper, we present a new technique for NTC based on a combination of deep learning models that can be used for IoT traffic. We show that a recurrent neural network (RNN) combined with a convolutional neural network (CNN) provides best detection results. The natural domain for a CNN, which is image processing, has been extended to NTC in an easy and natural way. We show that the proposed method provides better detection results than alternative algorithms without requiring any feature engineering, which is usual when applying other models. A complete study is presented on several architectures that integrate a CNN and an RNN, including the impact of the features chosen and the length of the network flows used for training.


Eurasip Journal on Wireless Communications and Networking | 2013

Innovative DAMA algorithm for multimedia DVB-RCS system

Borja de la Cuesta; Lorena Albiol; Javier M. Aguiar; Carlos Baladrón; Belén Carro; Antonio Sánchez-Esguevillas

Satellite is often used as an access network in the Next Generation Networks landscape, where multimedia and real-time services are supported by return channels. However, these satellite return channels are a very limited resource with many terminal stations competing for its use, making its efficient assignation one of the key problems to solve in order to increase network performance. This article presents an innovative implementation of the resource allocation mechanism demand assigned multiple access (DAMA) applied to satellite return channel assignment, which provides support for dynamic allocation and quality-of-service. This resource allocation mechanism has been validated with the special purpose advanced Internet network emulator, using the test lab implementation to optimize traffic mapping and queue parameters directly in the field. The numerical results for the different test cases considered are presented, showing that the DAMA algorithm provided is an efficient way of assigning resources, and also helping in the comparison of the different capacity request mechanisms described in the standard.


Computer Networks | 2017

Ensemble network traffic classification: Algorithm comparison and novel ensemble scheme proposal

Santiago Egea Gómez; Belén Carro Martínez; Antonio Sánchez-Esguevillas; Luis Hernández Callejo

Abstract Network Traffic Classification (NTC) is a key piece for network monitoring, Quality-of-Service management and network security. Machine Learning algorithms have drawn the attention of many researchers during the last few years as a promising solution for network traffic classification. In Machine Learning, ensemble algorithms are classifiers formed by a set of base estimators that cooperate to build more complex models according to given training and classification strategies. Resulting models normally exhibit significant accuracy improvements compared to single estimators, but also extra time cost, which may obstruct the application of these methods to online NTC. This paper studies and compares the performance of seven popular ensemble algorithms based on Decision Trees, focusing on model accuracy, byte accuracy, and latency to determine whether ensemble learning can be properly applied to this modeling task. We show that some of the studied algorithms overcome single Decision Tree in terms of model accuracy and byte accuracy. However, the notable latency increase hinders the application of these methods in real time contexts. Additionally, we introduce a novel ensemble classifier that exploits the imbalanced populations presented in traffic networks datasets to achieve faster classifications. The experimental results show that our scheme retains the accuracy improvements of ensemble methods but with low latency punishment, enhancing the prospect of ensembles methods for online network traffic classification.


IEEE Communications Magazine | 2011

Future convergent telecommunications services: creation, context, P2P, QoS, and charging [Guest Editorial]

Antonio Sánchez-Esguevillas; Belén Carro-Martínez; Vishy Poosala

his series is an attempt to provide a holistic view of telecommunications services (having covered previously both enterprise [1] and residential [2] segments). The current issue is the second part of the New Converged Telecommunications Applications for the End User feature topic. In the previous issue ([3]), two published articles described services that rely on IP Multimedia Subsystem (IMS) infrastructure (which is progressively being deployed by telcos), related to lookup services and vehicular technology. In this second part a total of eight articles complete the selection of material fulfilling the call for papers intention of providing an update and new insights into the applications and services a converged world is bringing, concentrating on application-only topics in the field of services for mass market users.


IEEE Communications Magazine | 2010

Guest editorial: new converged telecommunications applications for the end user

Antonio Sánchez-Esguevillas; Belén Carro-Martínez; Vishy Poosala

The very first and most universal telecommunication application is voice, or, in other words, the telephone. Let us start this article by highlighting an important milestone in the industry. In mid-July 2010 (the time of this writing) it was announced (by the GSMA Association) that global mobile connections surpass 5 billion (18 months after the 4 billion connection milestone, with predictions for 6 billion in the first half of 2012), meaning 74 percent penetration. Is that not impressive? Think of other technologies like TV, or other sectors like banks, automotive? that do not have those universality rates. It is astonishing that in a few years (almost) every citizen of the world will use (mobile) telecommunications services. This success story is not only a privilege but certainly a responsibility for the advance of the world society. Innovation in telecommunications services for all these billions of users is certainly a rewarding challenge.

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Belén Carro

University of Valladolid

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Jaime Lloret

Polytechnic University of Valencia

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Luis Hernández

Complutense University of Madrid

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Lorena Calavia

University of Valladolid

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Albert Rego Mañez

Polytechnic University of Valencia

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