Simulated Annealing

The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine

Mobility management in wireless cellular systems.

by Wing Ho Andy Yuen.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 85-[90]).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Design Issues in Wireless Cellular Systems --- p.1Chapter 1.1.1 --- Channel Assignment --- p.2Chapter 1.1.2 --- Handoff --- p.3Chapter 1.1.3 --- Multiple Accesses --- p.3Chapter 1.1.4 --- Mobility Management --- p.4Chapter 1.2 --- Motivation of the thesis --- p.5Chapter 1.3 --- Outline of the thesis --- p.6Chapter 2 --- Background Studies --- p.9Chapter 2.1 --- Current Standards --- p.9Chapter 2.2 --- Mobility Models --- p.11Chapter 2.2.1 --- Fluid Flow Model --- p.12Chapter 2.2.2 --- Markovian model --- p.13Chapter 2.3 --- Dynamic versus Static Location Strategy --- p.14Chapter 2.4 --- Location Registration Strategies --- p.14Chapter 2.4.1 --- Time Based Strategy --- p.15Chapter 2.4.2 --- Geographic Based Strategy --- p.17Chapter 2.4.3 --- Distance Based Strategy --- p.18Chapter 2.4.4 --- Miscellaneous Strategies --- p.19Chapter 2.5 --- Summary --- p.20Chapter 3 --- Hybrid Bloom Filter Location Update Algorithm --- p.21Chapter 3.1 --- Introduction --- p.21Chapter 3.2 --- System Model --- p.22Chapter 3.3 --- Hybrid Bloom Filter Algorithm --- p.23Chapter 3.3.1 --- Location Update Protocol --- p.23Chapter 3.3.2 --- Paging Protocol --- p.25Chapter 3.4 --- Performance Evaluation --- p.27Chapter 3.4.1 --- Comparison of the hybrid and time based Bloom filter algorithms --- p.32Chapter 3.5 --- Numerical Studies --- p.33Chapter 3.5.1 --- Cost versus mobility --- p.34Chapter 3.5.2 --- Cost versus call arrival rate --- p.37Chapter 3.6 --- Summary --- p.39Chapter 4 --- A Dynamic Location Area Assignment Algorithm --- p.40Chapter 4.1 --- Geographic versus Distance Based Strategies --- p.41Chapter 4.2 --- System Model --- p.42Chapter 4.2.1 --- cell layout --- p.42Chapter 4.2.2 --- mobility model --- p.43Chapter 4.2.3 --- cost function --- p.44Chapter 4.3 --- Dynamic Location Area Assignment Algorithm --- p.45Chapter 4.3.1 --- Measurement --- p.46Chapter 4.3.2 --- "Computation of (iopt, jopt)" --- p.46Chapter 4.3.3 --- Computation of location area size k --- p.51Chapter 4.4 --- Numerical Studies --- p.52Chapter 4.5 --- Summary --- p.57Chapter 5 --- Paging Cost Reduction Using Bloom Filtering As Auxilliary Strategy --- p.64Chapter 5.1 --- Introduction --- p.64Chapter 5.2 --- A Case Study - Joint DLA-HBF Algorithm --- p.65Chapter 5.2.1 --- The Algorithm --- p.65Chapter 5.2.2 --- Performance Evaluation --- p.67Chapter 5.3 --- Summary --- p.68Chapter 6 --- Conclusion --- p.70Chapter 6.1 --- Summary of Results --- p.70Chapter 6.2 --- Future Research Directions --- p.71Appendix --- p.73Chapter A --- Optimality of the Hybrid Bloom Filter Algorithm --- p.73Chapter B --- Derivation of the Expected First Passage Time ExTi and EyTj --- p.77Chapter C --- Optimality of the Dynamic Location Area Algorithm --- p.81Bibliography --- p.8

Next-Generation Self-Organizing Networks through a Machine Learning Approach

Fecha de lectura de Tesis Doctoral: 17 Diciembre 2018.Para reducir los costes de gestión de las redes celulares, que, con el tiempo, aumentaban en complejidad, surgió el concepto de las redes autoorganizadas, o self-organizing networks (SON). Es decir, la automatización de las tareas de gestión de una red celular para disminuir los costes de infraestructura (CAPEX) y de operación (OPEX). Las tareas de las SON se dividen en tres categorías: autoconfiguración, autooptimización y autocuración. El objetivo de esta tesis es la mejora de las funciones SON a través del desarrollo y uso de herramientas de aprendizaje automático (machine learning, ML) para la gestión de la red. Por un lado, se aborda la autocuración a través de la propuesta de una novedosa herramienta para una diagnosis automática (RCA), consistente en la combinación de múltiples sistemas RCA independientes para el desarrollo de un sistema compuesto de RCA mejorado. A su vez, para aumentar la precisión de las herramientas de RCA mientras se reducen tanto el CAPEX como el OPEX, en esta tesis se proponen y evalúan herramientas de ML de reducción de dimensionalidad en combinación con herramientas de RCA. Por otro lado, en esta tesis se estudian las funcionalidades multienlace dentro de la autooptimización y se proponen técnicas para su gestión automática. En el campo de las comunicaciones mejoradas de banda ancha, se propone una herramienta para la gestión de portadoras radio, que permite la implementación de políticas del operador, mientras que, en el campo de las comunicaciones vehiculares de baja latencia, se propone un mecanismo multicamino para la redirección del tráfico a través de múltiples interfaces radio. Muchos de los métodos propuestos en esta tesis se han evaluado usando datos provenientes de redes celulares reales, lo que ha permitido demostrar su validez en entornos realistas, así como su capacidad para ser desplegados en redes móviles actuales y futuras

Probe-based visual analysis of geospatial simulations

This work documents the design, development, refinement, and evaluation of probes as an interaction technique for expanding both the usefulness and usability of geospatial visualizations, specifically those of simulations. Existing applications that allow the visualization of, and interaction with, geospatial simulations and their results generally present views of the data that restrict the user to a single perspective. When zoomed out, local trends and anomalies become suppressed and lost; when zoomed in, spatial awareness and comparison between regions become limited. The probe-based interaction model integrates coordinated visualizations within individual probe interfaces, which depict the local data in user-defined regions-of-interest. It is especially useful when dealing with complex simulations or analyses where behavior in various localities differs from other localities and from the system as a whole. The technique has been incorporated into a number of geospatial simulations and visualization tools. In each of these applications, and in general, probe-based interaction enhances spatial awareness, improves inspection and comparison capabilities, expands the range of scopes, and facilitates collaboration among multiple users. The great freedom afforded to users in defining regions-of-interest can cause modifiable areal unit problems to affect the reliability of analyses without the user’s knowledge, leading to misleading results. However, by automatically alerting the user to these potential issues, and providing them tools to help adjust their selections, these unforeseen problems can be revealed, and even corrected

Data analytics for mobile traffic in 5G networks using machine learning techniques

This thesis collects the research works I pursued as Ph.D. candidate at the Universitat Politecnica de Catalunya (UPC). Most of the work has been accomplished at the Mobile Network Department Centre Tecnologic de Telecomunicacions de Catalunya (CTTC). The main topic of my research is the study of mobile network traffic through the analysis of operative networks dataset using machine learning techniques. Understanding first the actual network deployments is fundamental for next-generation network (5G) for improving the performance and Quality of Service (QoS) of the users. The work starts from the collection of a novel type of dataset, using an over-the-air monitoring tool, that allows to extract the control information from the radio-link channel, without harming the users’ identities. The subsequent analysis comprehends a statistical characterization of the traffic and the derivation of prediction models for the network traffic. A wide group of algorithms are implemented and compared, in order to identify the highest performances. Moreover, the thesis addresses a set of applications in the context mobile networks that are prerogatives in the future mobile networks. This includes the detection of urban anomalies, the user classification based on the demanded network services, the design of a proactive wake-up scheme for efficient-energy devices.Esta tesis recoge los trabajos de investigación que realicé como Ph.D. candidato a la Universitat Politecnica de Catalunya (UPC). La mayor parte del trabajo se ha realizado en el Centro Tecnológico de Telecomunicaciones de Catalunya (CTTC) del Departamento de Redes Móviles. El tema principal de mi investigación es el estudio del tráfico de la red móvil a través del análisis del conjunto de datos de redes operativas utilizando técnicas de aprendizaje automático. Comprender primero las implementaciones de red reales es fundamental para la red de próxima generación (5G) para mejorar el rendimiento y la calidad de servicio (QoS) de los usuarios. El trabajo comienza con la recopilación de un nuevo tipo de conjunto de datos, utilizando una herramienta de monitoreo por aire, que permite extraer la información de control del canal de radioenlace, sin dañar las identidades de los usuarios. El análisis posterior comprende una caracterización estadística del tráfico y la derivación de modelos de predicción para el tráfico de red. Se implementa y compara un amplio grupo de algoritmos para identificar los rendimientos más altos. Además, la tesis aborda un conjunto de aplicaciones en el contexto de redes móviles que son prerrogativas en las redes móviles futuras. Esto incluye la detección de anomalías urbanas, la clasificación de usuarios basada en los servicios de red demandados, el diseño de un esquema de activación proactiva para dispositivos de energía eficiente.Postprint (published version

Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

Large-scale Mobile Traffic Analysis: a Survey

International audienceThis article surveys the literature on analyses of mobile traffic collected by operators within their network infrastructure. This is a recently emerged research field, and, apart from a few outliers, relevant works cover the period from 2005 to date, with a sensible densification over the last three years. We provide a thorough review of the multidisciplinary activities that rely on mobile traffic datasets, identifying major categories and sub-categories in the literature, so as to outline a hierarchical classification of research lines. When detailing the works pertaining to each class, we balance a comprehensive view of state-of-the-art results with punctual focuses on the methodological aspects. Our approach provides a complete introductory guide to the research based on mobile traffic analysis. It allows summarizing the main findings of the current state-of-the-art, as well as pinpointing important open research directions

Internet of Things and Sensors Networks in 5G Wireless Communications

The Internet of Things (IoT) has attracted much attention from society, industry and academia as a promising technology that can enhance day to day activities, and the creation of new business models, products and services, and serve as a broad source of research topics and ideas. A future digital society is envisioned, composed of numerous wireless connected sensors and devices. Driven by huge demand, the massive IoT (mIoT) or massive machine type communication (mMTC) has been identified as one of the three main communication scenarios for 5G. In addition to connectivity, computing and storage and data management are also long-standing issues for low-cost devices and sensors. The book is a collection of outstanding technical research and industrial papers covering new research results, with a wide range of features within the 5G-and-beyond framework. It provides a range of discussions of the major research challenges and achievements within this topic

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors

Internet of Things and Sensors Networks in 5G Wireless Communications

This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors