ACCESS AND STABILITY ISSUES IN SPECTRUM COMMONS

Ph.DDOCTOR OF PHILOSOPH

Resource allocation in networks via coalitional games

The main goal of this dissertation is to manage resource allocation in network engineering problems and to introduce efficient cooperative algorithms to obtain high performance, ensuring fairness and stability. Specifically, this dissertation introduces new approaches for resource allocation in Orthogonal Frequency Division Multiple Access (OFDMA) wireless networks and in smart power grids by casting the problems to the coalitional game framework and by providing a constructive iterative algorithm based on dynamic learning theory.  Software Engineering (Software)Algorithms and the Foundations of Software technolog

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Network coding-aided MAC protocols for cooperative wireless networks

The introduction of third generation (3G) technologies has caused a vast proliferation of wireless devices and networks, generating an increasing demand for high level Quality of Service (QoS). The wide spread of mobile applications has further reinforced the user need for communication, motivating at the same time the concepts of user cooperation and data dissemination. However, this trend towards continuous exchange of information and ubiquitous connectivity is inherently restricted by the energy-greedy functionalities of high-end devices. These limitations, along with the pressure exerted on the Information and Communications Technology (ICT) industry towards energy awareness, have induced the design of novel energy efficient schemes and algorithms. In this context, the Medium Access Control (MAC) layer plays a key role, since it is mainly responsible for the channel access regulation, the transmission scheduling and the resource allocation, thus constituting an appropriate point to effectively address energy efficiency issues that arise due to the users overcrowding. This dissertation provides a contribution to the design, analysis and evaluation of novel MAC protocols for cooperative wireless networks. In our attempt to design energy efficient MAC schemes, we were extensively assisted by the introduction of new techniques, such as Network Coding (NC), that intrinsically bring considerable gains in system performance. The main thesis contributions are divided into two parts. The first part presents NCCARQ, a novel NC-aided Cooperative Automatic Repeat reQuest (ARQ) MAC protocol for wireless networks. NCCARQ introduces a new access paradigm for cooperative ARQ schemes, exploiting NC benefits in bidirectional communication among wireless users. The NCCARQ performance in terms of QoS and energy efficiency is assessed by means of analytical probabilistic models and extensive computer-based simulations, revealing the significant gains we can achieve compared to standardized MAC solutions. In addition, the impact of realistic wireless channel conditions on the MAC protocol operation further motivated us to study the NCCARQ performance in wireless links affected by correlated shadowing, showing that the channel correlation may adversely affect the distributed cooperation benefits. The second part of the thesis is dedicated to the investigation of MAC issues in wireless data dissemination scenarios. In particular, the existence of multiple source nodes in such scenarios generates conflicting situations, considering the selfish behavior of the wireless devices that want to maximize their battery lifetime. Bearing in mind the energy efficiency importance, we propose game theoretic medium access strategies, applying energy-based utility functions which inherently imply energy awareness. In addition, Random Linear NC (RLNC) techniques are adopted to eliminate the need of exchanging excessive control packets, while Analog NC (ANC) is employed to efface the impact of collisions throughout the communication. During the elaboration of this thesis, two general key conclusions have been extracted. First, there is a fundamental requirement for implementation of new MAC protocols in order to effectively deal with state-of-the-art techniques (e.g., NC), recently introduced to enhance both the performance and the energy efficiency of the network. Second, we highlight the importance of designing novel energy efficient MAC protocols, taking into account that traditional approaches - designed mainly to assist the collision avoidance in wireless networks - tend to be obsolete.La presente tesis doctoral contribuye al diseño, análisis y evaluación de nuevos protocolos MAC cooperativos para redes inalámbricas. La introducción de nuevas técnicas, tales como la codificación de red (NC), que intrínsecamente llevan un considerable aumento en el rendimiento del sistema, nos ayudó ampliamente durante el diseño de protocolos MAC energéticamente eficientes. Las principales contribuciones de esta tesis se dividen en dos partes. La primera parte presenta el NCCARQ, un protocolo cooperativo de retransmisión automática (ARQ), asistido por NC para redes inalámbricas. La segunda parte de la tesis se centra en el diseño de protocolos de capa MAC en escenarios inalámbricos de difusión de datos. Teniendo en cuenta la importancia de la eficiencia energética, se proponen técnicas de acceso al medio basadas en teoría de juegos dónde las funciones objetivo están motivadas por el consumo energético. Las soluciones propuestas son evaluadas por medio de modelos analíticos y simulaciones por ordenador

Advances in analytical models and applications for RFID, WSN and AmI systems

Experimentos llevados a cabo con el equipo de división de honor UCAM Volleyball Murcia.[SPA] Internet de las cosas (IoT) integra distintos elementos que actúan tanto como fuentes, como sumideros de información, a diferencia de la percepción que se ha tenido hasta ahora de Internet, centrado en las personas. Los avances en IoT engloban un amplio número de áreas y tecnologías, desde la adquisición de información hasta el desarrollo de nuevos protocolos y aplicaciones. Un concepto clave que subyace en el concepto de IoT, es el procesamiento de forma inteligente y autónoma de los flujos de información que se dispone. En este trabajo, estudiamos tres aspectos diferentes de IoT. En primer lugar, nos centraremos en la infraestructura de obtención de datos. Entre las diferentes tecnologías de obtención de datos disponibles en los sistemas IoT, la Identificación por Radio Frecuencia (RFID) es considerada como una de las tecnologías predominantes. RFID es la tecnología detrás de aplicaciones tales como control de acceso, seguimiento y rastreo de contenedores, gestión de archivos, clasificación de equipaje o localización de equipos. Con el auge de la tecnología RFID, muchas instalaciones empiezan a requerir la presencia de múltiples lectores RFID que operan próximos entre sí y conjuntamente. A estos escenarios se les conoce como dense reader environments (DREs). La coexistencia de varios lectores operando simultáneamente puede causar graves problemas de interferencias en el proceso de identificación. Uno de los aspectos claves a resolver en los RFID DREs consiste en lograr la coordinación entre los lectores. Estos problemas de coordinación son tratados en detalle en esta tesis doctoral. Además, dentro del área de obtención de datos relativa a IoT, las Redes de Sensores Inalámbricas (WSNs) desempeñan un papel fundamental. Durante la última década, las WSNs han sido estudiadas ampliamente de forma teórica, y la mayoría de problemas relacionados con la comunicación en este tipo de redes se han conseguido resolver de forma favorable. Sin embargo, con la implementación de WSNs en proyectos reales, han surgido nuevos problemas, siendo uno de ellos el desarrollo de estrategias realistas para desplegar las WSN. En este trabajo se estudian diferentes métodos que resuelven este problema, centrándonos en distintos criterios de optimización, y analizando las diferentes ventajas e inconvenientes que se producen al buscar una solución equilibrada. Por último, la Inteligencia Ambiental (AmI) forma parte del desarrollo de aplicaciones inteligentes en IoT. Hasta ahora, han sido las personas quienes han tenido que adaptarse al entorno, en cambio, AmI persigue crear entornos de obtención de datos capaces de anticipar y apoyar las acciones de las personas. AmI se está introduciendo progresivamente en diversos entornos reales tales como el sector de la educación y la salud, en viviendas, etc. En esta tesis se introduce un sistema AmI orientado al deporte que busca mejorar el entrenamiento de los atletas, siendo el objetivo prioritario el desarrollo de un asistente capaz de proporcionar órdenes de entrenamiento, basadas tanto en el entorno como en el rendimiento de los atletas. [ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.[ENG] Internet of Things (IoT) is being built upon many different elements acting as sources and sinks of information, rather than the previous human-centric Internet conception. Developments in IoT include a vast set of fields ranging from data sensing, to development of new protocols and applications. Indeed, a key concept underlying in the conception of IoT is the smart and autonomous processing of the new huge data flows available. In this work, we aim to study three different aspects within IoT. First, we will focus on the sensing infrastructure. Among the different kind of sensing technologies available to IoT systems, Radio Frequency Identification (RFID) is widely considered one of the leading technologies. RFID is the enabling technology behind applications such as access control, tracking and tracing of containers, file management, baggage sorting or equipment location. With the grow up of RFID, many facilities require multiple RFID readers usually operating close to each other. These are known as Dense Reader Environments (DREs). The co-existence of several readers operating concurrently is known to cause severe interferences on the identification process. One of the key aspects to solve in RFID DREs is achieving proper coordination among readers. This is the focus of the first part of this doctoral thesis. Unlike previous works based on heuristics, we address this problem through an optimization-based approach. The goal is identifying the maximum mean number of tags while network constraints are met. To be able to formulate these optimization problems, we have obtained analytically the mean number of identifications in a bounded -discrete or continuous- time period, an additional novel contribution of our work. Results show that our approach is overwhelmingly better than previous known methods. Along sensing technologies of IoT, Wireless Sensor Networks (WSNs) plays a fundamental role. WSNs have been largely and theoretically studied in the past decade, and many of their initial problems related to communication aspects have been successfully solved. However, with the adoption of WSNs in real-life projects, new issues have arisen, being one of them the development of realistic strategies to deploy WSNs. We have studied different ways of solving this aspect by focusing on different optimality criteria and evaluating the different trade-offs that occur when a balanced solution must be selected. On the one hand, deterministic placements subject to conflicting goals have been addressed. Results can be obtained in the form of Pareto-frontiers, allowing proper solution selection. On the other hand, a number of situations correspond to deployments were the nodes¿ position is inherently random. We have analyzed these situations leading first to a theoretical model, which later has been particularized to a Moon WSN survey. Our work is the first considering a full model with realistic properties such as 3D topography, propellant consumptions or network lifetime and mass limitations. Furthermore, development of smart applications within IoT is the focus of the Ambient Intelligence (AmI) field. Rather than having people adapting to the surrounding environment, AmI pursues the development of sensitive environments able to anticipate support in people¿s actions. AmI is progressively being introduced in many real-life environments like education, homes, health and so forth. In this thesis we develop a sport-oriented AmI system designed to improve athletes training. The goal is developing an assistant able to provide real-time training orders based on both environment and athletes¿ biometry, which is aimed to control the aerobic and the technical-tactical training. Validation experiments with the honor league UCAM Volleyball Murcia team have shown the suitability of this approach.Universidad Politécnica de CartagenaPrograma de doctorado en Tecnología de la Información y de las Comunicacione

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Learning for Cross-layer Resource Allocation in the Framework of Cognitive Wireless Networks

The framework of cognitive wireless networks is expected to endow wireless devices with a cognition-intelligence ability with which they can efficiently learn and respond to the dynamic wireless environment. In this dissertation, we focus on the problem of developing cognitive network control mechanisms without knowing in advance an accurate network model. We study a series of cross-layer resource allocation problems in cognitive wireless networks. Based on model-free learning, optimization and game theory, we propose a framework of self-organized, adaptive strategy learning for wireless devices to (implicitly) build the understanding of the network dynamics through trial-and-error. The work of this dissertation is divided into three parts. In the first part, we investigate a distributed, single-agent decision-making problem for real-time video streaming over a time-varying wireless channel between a single pair of transmitter and receiver. By modeling the joint source-channel resource allocation process for video streaming as a constrained Markov decision process, we propose a reinforcement learning scheme to search for the optimal transmission policy without the need to know in advance the details of network dynamics. In the second part of this work, we extend our study from the single-agent to a multi-agent decision-making scenario, and study the energy-efficient power allocation problems in a two-tier, underlay heterogeneous network and in a self-sustainable green network. For the heterogeneous network, we propose a stochastic learning algorithm based on repeated games to allow individual macro- or femto-users to find a Stackelberg equilibrium without flooding the network with local action information. For the self-sustainable green network, we propose a combinatorial auction mechanism that allows mobile stations to adaptively choose the optimal base station and sub-carrier group for transmission only from local payoff and transmission strategy information. In the third part of this work, we study a cross-layer routing problem in an interweaved Cognitive Radio Network (CRN), where an accurate network model is not available and the secondary users that are distributed within the CRN only have access to local action/utility information. In order to develop a spectrum-aware routing mechanism that is robust against potential insider attackers, we model the uncoordinated interaction between CRN nodes in the dynamic wireless environment as a stochastic game. Through decomposition of the stochastic routing game, we propose two stochastic learning algorithm based on a group of repeated stage games for the secondary users to learn the best-response strategies without the need of information flooding

Mobile Ad Hoc Networks

Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms