131 research outputs found
Application of an automatically designed fuzzy logic decision support system to connection admission control in ATM networks
PhDAbstract not availabl
An Algorithm to Evaluate the Echo Signal and the Voice Quality in VoIP Networks
Voice over the Internet Protocol (VoIP) has been increasingly popular, but reliability and voice quality remain important factors that limit the widespread adoption of VoIP systems. Providing good voice quality is of major importance for the transition from the PSTN to VoIP networks. There are several non-real-time algorithms that estimate the voice quality such as the PESQ and the E-model. In this thesis we propose a real-time fuzzy algorithm to estimate the echo quality component of the voice quality in VoIP networks. Differently from the existing algorithms, the proposed algorithm does not need a reference signal and has low computational complexity. For these reasons, the proposed algorithm can be embedded in every VoIP system of a network to monitor live calls, giving an estimate of the instantaneous voice quality to the network provider
Comparison of vertical handover decision-based techniques in heterogeneous networks
Industry leaders are currently setting out standards for 5G Networks projected for 2020 or even sooner. Future generation networks will be heterogeneous in nature because no single network type is capable of optimally meeting all the rapid changes in customer demands. Heterogeneous networks are typically characterized by some network architecture, base stations of varying transmission power, transmission solutions and the deployment of a mix of technologies (multiple radio access technologies). In heterogeneous networks, the processes involved when a mobile node successfully switches from one radio access technology to the other for the purpose of quality of service continuity is termed vertical handover or vertical handoff. Active calls that get dropped, or cases where there is discontinuity of service experienced by mobile users can be attributed to the phenomenon of delayed handover or an outright case of an unsuccessful handover procedure. This dissertation analyses the performance of a fuzzy-based VHO algorithm scheme in a Wi-Fi, WiMAX, UMTS and LTE integrated network using the OMNeT++ discrete event simulator. The loose coupling type network architecture is adopted and results of the simulation are analysed and compared for the two major categories of handover basis; multiple and single criteria based handover methods. The key performance indices from the simulations showed better overall throughput, better call dropped rate and shorter handover time duration for the multiple criteria based decision method compared to the single criteria based technique. This work also touches on current trends, challenges in area of seamless handover and initiatives for future Networks (Next Generation Heterogeneous Networks)
Klausurtagung des Instituts fĂŒr Telematik. Schloss Dagstuhl, 29. MĂ€rz bis 1. April 2000
Der vorliegende Bericht gibt einen Ăberblick ĂŒber aktuelle
Forschungsarbeiten des Instituts fĂŒr Telematik an der
UniversitÀt
Karlsruhe (TH). Das Institut fĂŒr Telematik ist in einem
Teilgebiet der
Informatik tÀtig, welches durch das Zusammenwachsen von
Informatik
und Kommunikationstechnik zur Telematik geprÀgt ist. Es
gliedert sich
in die Forschungsbereiche Telematik, Telecooperation Office
(TecO),
Cooperation & Management, Hochleistungsnetze und
Netzwerkmanagement
sowie dezentrale Systeme und Netzdienste.
Die Schwerpunkte des Forschungsbereichs "Telematik"
(Prof. Dr. Dr. h.c. mult. G. KrĂŒger) liegen in den Bereichen
"DienstgĂŒte", "Mobilkommunikation" und "Verteilte
Systeme". Gemeinsames Ziel ist die Integration heterogener Netze
(Festnetze und Funknetze), Rechnersysteme (von Workstations bis
zu
PDAs) und Softwarekomponenten, um damit den Anwendern eine
Vielzahl
von integrierten Diensten effizient und mit gröĂtmöglicher
QualitÀt zu erbringen.
Das "Telecooperation Office" (TecO,
Prof. Dr. Dr. h.c. mult. G. KrĂŒger) ist ein Institutsbereich,
der in
Zusammenarbeit mit der Industrie anwendungsnahe
Forschungsthemen der
Telematik aufgreift. Im Mittelpunkt steht die innovative
Nutzung von
Kommunikationsinfrastrukturen mit den Schwerpunkten
Softwaretechnik
fĂŒr Web-Anwendungen, neue Formen der Telekooperation sowie
tragbare
und allgegenwÀrtige Technologien (Ubiquitous Computing).
Die Kernkompetenz des Forschungsbereichs "Cooperation &
Management"
(Prof. Dr. S. Abeck) liegt im prozessorientierten Netz-, System-
und
Anwendungsmanagement. Es werden werkzeuggestĂŒtzte
Managementlösungen fĂŒr Betriebsprozesse entwickelt und in realen
Szenarien erprobt. Ein wichtiges Szenario stellt das
multimediale
Informationssystem "NEXUS" dar, das als Plattform eines
europaweit
verteilten Lehr- und Lernsystems genutzt wird.
Der Forschungsbereich "Hochleistungsnetze & Netzwerkmanagement"
(Prof. Dr. W. Juling) befasst sich mit Technologie und Konzepten
moderner leistungsfĂ€higer Netzwerke sowie darĂŒber hinaus mit
sÀmtlichen Aspekten des Managements dieser zumeist ausgedehnten
Netze. Um eine enge Abstimmung zwischen ForschungsaktivitÀten
und
betrieblicher Praxis zu erzielen, werden insbesondere auch
Synergien
zwischen Institut und Rechenzentrum angestrebt.
Die Arbeiten des Forschungsbereichs "Dezentrale Systeme und
Netzdienste" (Prof. Dr. L. Wolf) befassen sich mit der
UnterstĂŒtzung
verteilter Multimedia-Systeme, auch unter BerĂŒcksichtigung von
Komponenten mit drahtlosem Zugang und den dafĂŒr geeigneten
Architekturen und Infrastrukturen. Dabei werden vor allem
Aspekte der
Kommunikationssysteme wie Protokollmechanismen,
Ressourcenverwaltung
und adaptive und heterogene Systeme untersucht
Active self-diagnosis in telecommunication networks
Les rĂ©seaux de tĂ©lĂ©communications deviennent de plus en plus complexes, notamment de par la multiplicitĂ© des technologies mises en Ćuvre, leur couverture gĂ©ographique grandissante, la croissance du trafic en quantitĂ© et en variĂ©tĂ©, mais aussi de par l Ă©volution des services fournis par les opĂ©rateurs. Tout ceci contribue Ă rendre la gestion de ces rĂ©seaux de plus en plus lourde, complexe, gĂ©nĂ©ratrice d erreurs et donc coĂ»teuse pour les opĂ©rateurs. On place derriĂšre le terme rĂ©seaux autonome l ensemble des solutions visant Ă rendre la gestion de ce rĂ©seau plus autonome. L objectif de cette thĂšse est de contribuer Ă la rĂ©alisation de certaines fonctions autonomiques dans les rĂ©seaux de tĂ©lĂ©communications. Nous proposons une stratĂ©gie pour automatiser la gestion des pannes tout en couvrant les diffĂ©rents segments du rĂ©seau et les services de bout en bout dĂ©ployĂ©s au-dessus. Il s agit d une approche basĂ©e modĂšle qui adresse les deux difficultĂ©s du diagnostic basĂ© modĂšle Ă savoir : a) la façon d'obtenir un tel modĂšle, adaptĂ© Ă un rĂ©seau donnĂ© Ă un moment donnĂ©, en particulier si l'on souhaite capturer plusieurs couches rĂ©seau et segments et b) comment raisonner sur un modĂšle potentiellement Ă©norme, si l'on veut gĂ©rer un rĂ©seau national par exemple. Pour rĂ©pondre Ă la premiĂšre difficultĂ©, nous proposons un nouveau concept : l auto-modĂ©lisation qui consiste d abord Ă construire les diffĂ©rentes familles de modĂšles gĂ©nĂ©riques, puis Ă identifier Ă la volĂ©e les instances de ces modĂšles qui sont dĂ©ployĂ©es dans le rĂ©seau gĂ©rĂ©. La seconde difficultĂ© est adressĂ©e grĂące Ă un moteur d auto-diagnostic actif, basĂ© sur le formalisme des rĂ©seaux BayĂ©siens et qui consiste Ă raisonner sur un fragment du modĂšle du rĂ©seau qui est augmentĂ© progressivement en utilisant la capacitĂ© d auto-modĂ©lisation: des observations sont collectĂ©es et des tests rĂ©alisĂ©s jusqu Ă ce que les fautes soient localisĂ©es avec une certitude suffisante. Cette approche de diagnostic actif a Ă©tĂ© expĂ©rimentĂ©e pour rĂ©aliser une gestion multi-couches et multi-segments des alarmes dans un rĂ©seau IMS.While modern networks and services are continuously growing in scale, complexity and heterogeneity, the management of such systems is reaching the limits of human capabilities. Technically and economically, more automation of the classical management tasks is needed. This has triggered a significant research effort, gathered under the terms self-management and autonomic networking. The aim of this thesis is to contribute to the realization of some self-management properties in telecommunication networks. We propose an approach to automatize the management of faults, covering the different segments of a network, and the end-to-end services deployed over them. This is a model-based approach addressing the two weaknesses of model-based diagnosis namely: a) how to derive such a model, suited to a given network at a given time, in particular if one wishes to capture several network layers and segments and b) how to reason a potentially huge model, if one wishes to manage a nation-wide network for example. To address the first point, we propose a new concept called self-modeling that formulates off-line generic patterns of the model, and identifies on-line the instances of these patterns that are deployed in the managed network. The second point is addressed by an active self-diagnosis engine, based on a Bayesian network formalism, that consists in reasoning on a progressively growing fragment of the network model, relying on the self-modeling ability: more observations are collected and new tests are performed until the faults are localized with sufficient confidence. This active diagnosis approach has been experimented to perform cross-layer and cross-segment alarm management on an IMS network.RENNES1-Bibl. Ă©lectronique (352382106) / SudocSudocFranceF
Application of learning algorithms to traffic management in integrated services networks.
SIGLEAvailable from British Library Document Supply Centre-DSC:DXN027131 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
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