Quality of Service (QoS) in MPLS networks

Telecommunications networks have been always expanding and thanks to it, new services have appeared. The old mechanisms for carrying packets have become obsolete due to the new service requirements, which have begun working in real time. Real time traffic requires strict service guarantees. When this traffic is sent through the network, enough resources must be given in order to avoid delays and information losses. When browsing through the Internet and requesting web pages, data must be sent from a server to the user. If during the transmission there is any packet drop, the packet is sent again. For the end user, it does not matter if the webpage loads in one or two seconds more. But if the user is maintaining a conversation with a VoIP program, such as Skype, one or two seconds of delay in the conversation may be catastrophic, and none of them can understand the other. In order to provide support for this new services, the networks have to evolve. For this purpose MPLS and QoS were developed. MPLS is a packet carrying mechanism used in high performance telecommunication networks which directs and carries data using pre-established paths. Now, packets are forwarded on the basis of labels, making this process faster than routing the packets with the IP addresses. MPLS also supports Traffic Engineering (TE). This refers to the process of selecting the best paths for data traffic in order to balance the traffic load between the different links. In a network with multiple paths, routing algorithms calculate the shortest one, and most of the times all traffic is directed through it, causing overload and packet drops, without distributing the packets in the other paths that the network offers and do not have any traffic. But this is not enough in order to provide the real time traffic the guarantees it needs. In fact, those mechanisms improve the network, but they do not make changes in how the traffic is treated. That is why Quality of Service (QoS) was developed. Quality of service is the ability to provide different priority to different applications, users, or data flows, or to guarantee a certain level of performance to a data flow. Traffic is distributed into different classes and each of them is treated differently, according to its Service Level Agreement (SLA). Traffic with the highest priority will have the preference over lower classes, but this does not mean it will monopolize all the resources. In order to achieve this goal, a set policies are defined to control and alter how the traffic flows. Possibilities are endless, and it depends in how the network must be structured. By using those mechanisms it is possible to provide the necessary guarantees to the real-time traffic, distributing it between categories inside the network and offering the best service for both real time data and non real time data. Las Redes de Telecomunicaciones siempre han estado en expansión y han propiciado la aparición de nuevos servicios. Los viejos mecanismos para transportar paquetes se han quedado obsoletos debido a las exigencias de los nuevos servicios, que han comenzado a operar en tiempo real. El tráfico en tiempo real requiere de unas estrictas garantías de servicio. Cuando este tráfico se envía a través de la red, necesita disponer de suficientes recursos para evitar retrasos y pérdidas de información. Cuando se navega por la red y se solicitan páginas web, los datos viajan desde un servidor hasta el usuario. Si durante la transmisión se pierde algún paquete, éste se vuelve a mandar de nuevo. Para el usuario final, no importa si la página tarda uno o dos segundos más en cargar. Ahora bien, si el usuario está manteniendo una conversación usando algún programa de VoIP (como por ejemplo Skype) uno o dos segundos de retardo en la conversación podrían ser catastróficos, y ninguno de los interlocutores sería capaz de entender al otro. Para poder dar soporte a estos nuevos servicios, las redes deben evolucionar. Para este propósito se han concebido MPLS y QoS MPLS es un mecanismo de transporte de paquetes que se usa en redes de telecomunicaciones de alto rendimiento que dirige y transporta los datos de acuerdo a caminos preestablecidos. Ahora los paquetes se encaminan en función de unas etiquetas, lo cual hace que sea mucho más rápido que encaminar los paquetes usando las direcciones IP. MPLS también soporta Ingeniería de Tráfico (TE). Consiste en seleccionar los mejores caminos para el tráfico de datos con el objetivo de balancear la carga entre los diferentes enlaces. En una red con múltiples caminos, los algoritmos de enrutamiento actuales calculan el camino más corto, y muchas veces el tráfico se dirige sólo por éste, saturando el canal, mientras que otras rutas se quedan completamente desocupadas. Ahora bien, esto no es suficiente para ofrecer al tráfico en tiempo real las garantías que necesita. De hecho, estos mecanismos mejoran la red, pero no realizan cambios a la hora de tratar el tráfico. Por esto es por lo que se ha desarrollado el concepto de Calidad de Servicio (QoS). La calidad de servicio es la capacidad para ofrecer diferentes prioridades a las diferentes aplicaciones, usuarios o flujos de datos, y para garantizar un cierto nivel de rendimiento en un flujo de datos. El tráfico se distribuye en diferentes clases y cada una de ellas se trata de forma diferente, de acuerdo a las especificaciones que se indiquen en su Contrato de Tráfico (SLA). EL tráfico con mayor prioridad tendrá preferencia sobre el resto, pero esto no significa que acapare la totalidad de los recursos. Para poder alcanzar estos objetivos se definen una serie de políticas para controlar y alterar el comportamiento del tráfico. Las posibilidades son inmensas dependiendo de cómo se quiera estructurar la red. Usando estos mecanismos se pueden proporcionar las garantías necesarias al tráfico en tiempo real, distribuyéndolo en categorías dentro de la red y ofreciendo el mejor servicio posible tanto a los datos en tiempo real como a los que no lo son.

Un modelo de encaminamiento en las redes móviles ad hoc con QoS

En la última década ha aumentado en gran medida el interés por las redes móviles Ad Hoc. La naturaleza dinámica y sin infraestructura de estas redes, exige un nuevo conjunto de algoritmos y estrategias para proporcionar un servicio de comunicación fiable extremo a extremo. En el contexto de las redes móviles Ad Hoc, el encaminamiento surge como una de las áreas más interesantes para transmitir información desde una fuente hasta un destino, con la calidad de servicio de extremo a extremo. Debido a las restricciones inherentes a las redes móviles, los modelos de encaminamiento tradicionales sobre los que se fundamentan las redes fijas, no son aplicables a las redes móviles Ad Hoc. Como resultado, el encaminamiento en redes móviles Ad Hoc ha gozado de una gran atención durante los últimos años. Esto ha llevado al acrecentamiento de numerosos protocolos de encaminamiento, tratando de cubrir con cada uno de ellos las necesidades de los diferentes tipos de escenarios. En consecuencia, se hace imprescindible estudiar el comportamiento de estos protocolos bajo configuraciones de red variadas, con el fin de ofrecer un mejor encaminamiento respecto a los existentes. El presente trabajo de investigación muestra precisamente una solución de encaminamiento en las redes móviles Ad Hoc. Dicha solución se basa en el mejoramiento de un algoritmo de agrupamiento y la creación de un modelo de encaminamiento; es decir, un modelo que involucra la optimización de un protocolo de enrutamiento apoyado de un mecanismo de agrupación. El algoritmo mejorado, denominado GMWCA (Group Management Weighted Clustering Algorithm) y basado en el WCA (Weighted Clustering Algorithm), permite calcular el mejor número y tamaño de grupos en la red. Con esta mejora se evitan constantes reagrupaciones y que los jefes de clústeres tengan más tiempo de vida intra-clúster y por ende una estabilidad en la comunicación inter-clúster. En la tesis se detallan las ventajas de nuestro algoritmo en relación a otras propuestas bajo WCA. El protocolo de enrutamiento Ad Hoc propuesto, denominado QoS Group Cluster Based Routing Protocol (QoSG-CBRP), utiliza como estrategia el empleo de clúster y jerarquías apoyada en el algoritmo de agrupamiento. Cada clúster tiene un jefe de clúster (JC), quien administra la información de enrutamiento y la envía al destino cuando esta fuera de su área de cobertura. Para evitar que haya constantes reagrupamientos y llamados al algoritmo de agrupamiento se consideró agregarle un jefe de cluster de soporte (JCS), el que asume las funciones del JC, siempre y cuando este haya roto el enlace con los otros nodos comunes del clúster por razones de alejamiento o por desgaste de batería. Matemáticamente y a nivel de algoritmo se han demostrado las mejoras del modelo propuesto, el cual ha involucrado el mejoramiento a nivel de algoritmo de clustering y del protocolo de enrutamiento. El protocolo QoSG-CBRP, se ha implementado en la herramienta de simulación Network Simulator 2 (NS2), con la finalidad de ser comparado con el protocolo de enrutamiento jerárquico Cluster Based Routing Protocol (CBRP) y con un protocolo de enrutamiento Ad Hoc reactivo denominado Ad Hoc On Demand Distance Vector Routing (AODV). Estos protocolos fueron elegidos por ser los que mejor comportamiento presentaron dentro de sus categorías. Además de ofrecer un panorama general de los actuales protocolos de encaminamiento en redes Ad Hoc, este proyecto presenta un procedimiento integral para el análisis de capacidades de la propuesta del nuevo protocolo con respecto a otros, sobre redes que tienen un alto número de nodos. Estas prestaciones se miden en base al concepto de eficiencia de encaminamiento bajo parámetros de calidad de servicio (QoS), permitiendo establecer el camino más corto posible entre un nodo origen y un nodo destino. Con ese fin se han realizado simulaciones con diversos escenarios para responder a los objetivos de la tesis. La conclusiones derivadas del análisis de los resultados permiten evaluar cualitativamente las capacidades que presenta el protocolo dentro del modelo propuesto, al mismo tiempo que avizora un atractivo panorama en líneas futuras de investigación. ABSTRACT In the past decade, the interest in mobile Ad Hoc networks has greatly increased. The dynamic nature of these networks without infrastructure requires a new set of algorithms and strategies to provide a reliable end-to-end communication service. In the context of mobile Ad Hoc networks, routing emerges as one of the most interesting areas for transmitting information from a source to a destination, with the quality of service from end-to-end. Due to the constraints of mobile networks, traditional routing models that are based on fixed networks are not applicable to Ad Hoc mobile networks. As a result, the routing in mobile Ad Hoc networks has experienced great attention in recent years. This has led to the enhancement of many routing protocols, trying to cover with each one of them, the needs of different types of scenarios. Consequently, it is essential to study the behavior of these protocols under various network configurations, in order to provide a better routing scheme. Precisely, the present research shows a routing solution in mobile Ad Hoc networks. This solution is based on the improvement of a clustering algorithm, and the creation of a routing model, ie a model that involves optimizing a routing protocol with the support of a grouping mechanism. The improved algorithm called GMWCA (Group Management Weighted Clustering Algorithm) and based on the WCA (Weighted Clustering Algorithm), allows to calculate the best number and size of groups in the network. With this enhancement, constant regroupings are prevented and cluster heads are living longer intra-cluster lives and therefore stability in inter-cluster communication. The thesis details the advantages of our algorithm in relation to other proposals under WCA. The Ad Hoc routing protocol proposed, called QoS Group Cluster Based Routing Protocol (QoSG-CBRP), uses a cluster-employment strategy and hierarchies supported by the clustering algorithm. Each cluster has a cluster head (JC), who manages the routing information and sends it to the destination when is out of your coverage area. To avoid constant rearrangements and clustering algorithm calls, adding a support cluster head (JCS) was considered. The JCS assumes the role of the JC as long as JC has broken the link with the other nodes in the cluster for common restraining reasons or battery wear. Mathematically and at an algorithm level, the improvements of the proposed model have been showed, this has involved the improvement level clustering algorithm and the routing protocol. QoSG-CBRP protocol has been implemented in the simulation tool Network Simulator 2 (NS2), in order to be compared with the hierarchical routing protocol Cluster Based Routing Protocol (CBRP) and with the reactive routing protocol Ad Hoc On Demand Distance Vector Routing (AODV). These protocols were chosen because they showed the best individual performance in their categories. In addition to providing an overview of existing routing protocols in Ad Hoc networks, this project presents a comprehensive procedure for capacity analysis of the proposed new protocol with respect to others on networks that have a high number of nodes. These benefits are measured based on the concept of routing efficiency under the quality of service (QoS) parameters, thus allowing for the shortest possible path between a source node and a destination node. To meet the objectives of the thesis, simulations have been performed with different scenarios. The conclusions derived from the analysis of the results to assess qualitatively the protocol capabilities presented in the proposed model, while an attractive scenario for future research appears.

Call admission control algorithms in OFDM-based wireless multiservice networks

Orthogonal frequency division multiplexing (OFDM) is becoming a fundamental technology in future generation wireless communications. Call admission control is an effective mechanism to guarantee resilient, efficient, and quality-of-service (QoS) services in wireless mobile networks. In this paper, we present several call admission control algorithms for OFDM-based wireless multiservice networks. Call connection requests are differentiated into narrow-band calls and wide-band calls. For either class of calls, the traffic process is characterized as batch arrival since each call may request multiple subcarriers to satisfy its QoS requirement. The batch size is a random variable following a probability mass function (PMF) with realistically maximum value. In addition, the service times for wide-band and narrow-band calls are different. Following this, we perform a tele-traffic queueing analysis for OFDM-based wireless multiservice networks. The formulae for the significant performance metrics call blocking probability and bandwidth utilization are developed. Numerical investigations are presented to demonstrate the interaction between key parameters and performance metrics. The performance tradeoff among different call admission control algorithms is discussed. Moreover, the analytical model has been validated by simulation. The methodology as well as the result provides an efficient tool for planning next-generation OFDM-based broadband wireless access systems.

A Distributed Support based on Kubeflow to Ease MLOps of Federated Learning Algorithms

The main objective of my thesis work is to exploit the Google native and open-source platform Kubeflow, specifically using Kubeflow pipelines, to execute a Federated Learning scalable ML process in a 5G-like and simplified test architecture hosting a Kubernetes cluster and apply the largely adopted FedAVG algorithm and FedProx its optimization empowered by the ML platform ‘s abilities to ease the development and production cycle of this specific FL process. FL algorithms are more are and more promising and adopted both in Cloud application development and 5G communication enhancement through data coming from the monitoring of the underlying telco infrastructure and execution of training and data aggregation at edge nodes to optimize the global model of the algorithm ( that could be used for example for resource provisioning to reach an agreed QoS for the underlying network slice) and after a study and a research over the available papers and scientific articles related to FL with the help of the CTTC that suggests me to study and use Kubeflow to bear the algorithm we found out that this approach for the whole FL cycle deployment was not documented and may be interesting to investigate more in depth. This study may lead to prove the efficiency of the Kubeflow platform itself for this need of development of new FL algorithms that will support new Applications and especially test the FedAVG algorithm performances in a simulated client to cloud communication using a MNIST dataset for FL as benchmark.

Biased Random-key Genetic Algorithms For The Winner Determination Problem In Combinatorial Auctions.

Abstract In this paper, we address the problem of picking a subset of bids in a general combinatorial auction so as to maximize the overall profit using the first-price model. This winner determination problem assumes that a single bidding round is held to determine both the winners and prices to be paid. We introduce six variants of biased random-key genetic algorithms for this problem. Three of them use a novel initialization technique that makes use of solutions of intermediate linear programming relaxations of an exact mixed integer-linear programming model as initial chromosomes of the population. An experimental evaluation compares the effectiveness of the proposed algorithms with the standard mixed linear integer programming formulation, a specialized exact algorithm, and the best-performing heuristics proposed for this problem. The proposed algorithms are competitive and offer strong results, mainly for large-scale auctions.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

E-contracting with price configuration for Web services and QoS

The large amount of information in electronic contracts hampers their establishment due to high complexity. An approach inspired in Software Product Line (PL) and based on feature modelling was proposed to make this process more systematic through information reuse and structuring. By assessing the feature-based approach in relation to a proposed set of requirements, it was showed that the approach does not allow the price of services and of Quality of Services (QoS) attributes to be considered in the negotiation and included in the electronic contract. Thus, this paper also presents an extension of such approach in which prices and price types associated to Web services and QoS levels are applied. An extended toolkit prototype is also presented as well as an experiment example of the proposed approach.

GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

Hybrid Algorithms for Routing and Assignment Wavelengths in Optical Networks

This paper presents a strategy for the solution of the WDM optical networks planning. Specifically, the problem of Routing and Wavelength Allocation (RWA) in order to minimize the amount of wavelengths used. In this case, the problem is known as the Min-RWA. Two meta-heuristics (Tabu Search and Simulated Annealing) are applied to take solutions of good quality and high performance. The key point is the degradation of the maximum load on the virtual links in favor of minimization of number of wavelengths used; the objective is to find a good compromise between the metrics of virtual topology (load in Gb/s) and of the physical topology (quantity of wavelengths). The simulations suggest good results when compared to some existing in the literature.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

A Taxonomy for Locality Algorithms on Peer-to-Peer Networks

The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Approximate algorithms for credal networks with binary variables

This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.

Some heuristic algorithms for total tardiness minimization in a flowshop with blocking

The flowshop scheduling problem with blocking in-process is addressed in this paper. In this environment, there are no buffers between successive machines: therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Heuristic approaches are proposed to minimize the total tardiness criterion. A constructive heuristic that explores specific characteristics of the problem is presented. Moreover, a GRASP-based heuristic is proposed and Coupled with a path relinking strategy to search for better outcomes. Computational tests are presented and the comparisons made with an adaptation of the NEH algorithm and with a branch-and-bound algorithm indicate that the new approaches are promising. (c) 2007 Elsevier Ltd. All rights reserved.