Improving RFC5865 Core Network Scheduling with a Burst Limiting Shaper

We define a novel core network router scheduling architecture to carry and isolate time constrained and elastic traffic flows from best-effort traffic. To date, one possible solution has been to implement a core DiffServ network with standard fair queuing and scheduling mechanisms as proposed in the well-known “A Differentiated Services Code Point (DSCP) for Capacity-Admitted Traffic” from RFC5865. This architecture is one of the most selected solutions by internet service provider for access networks (e.g. Customer-Premises Equipment or satellite PEP). In this study, we argue that the proposed standard implementation does not allow to efficiently quantify the reserved capacity for the AF class. By using a novel credit based shaper mechanism called Burst Limiting Shaper, we show that we can provide the same isolation for the time constrained EF class while better quantifying the part allocated to the AF class

Performance analysis of VoIP data over IP networks

The paper presents the results of research and analysis of voice data transmission quality in IP packet networks. It analyses mechanisms allowing for the assessment of packet telephony data transmission quality. Possible transmission quality levels and adequate quality metrics, applicable in the recommen- dations of standardisation organisations, as well as suggested limit values conditioning acceptable voice data transmission quality were indicated and discussed. A packet network model was designed and tested, taking into account VoIP architecture supporting various audio codecs used for voice compression. Transmission mechanisms based on audio codecs G.711, G.723, G.726, G.728 and G.729 were investigated. It was shown that    for delay-sensitive traffic which fluctuates beyond its nominal rate, selected codecs have an advantage over others and allow   for better transmission quality of VoIP traffic with guaranteed bandwidth and delay

Discriminating if a network flow could have been created from a given sequence of network packets

This thesis aims to design a neural network (NN), that is capable of discriminating if a network flow could have been created based on a sequence of packets and can be used as a discriminative network (DN) for a Generative Adversarial Network (GAN) in future work. For this, we first determined the features of network flows and packets alike, which are relevant to this task. We then created a dataset by extracting the relevant features from well-known network traffic datasets from the field of network intrusion detection (NID), as well as falsifying said datapoints to provide negative samples. We also provide a pipeline for the process of creating such datasets. For our NN model we compared available architectures of recurrent neural networks (RNNs): simple RNN (simpleRNN), Long Short Term Memory (LSTM), and Gated Recurrent Units (GRUs). Furthermore our model uses a special kind of RNN called a conditional RNN (condRNN), which already has provided good results for a mixture of conditional and sequential input in the field of image region classification. This is necessary as a flow is the conditional counterpart to a sequence of packets. We aim to test the effectiveness of the different RNN architectures in regards to our problem and in the context of condRNNs

Reducing Internet Latency : A Survey of Techniques and their Merit

Bob Briscoe, Anna Brunstrom, Andreas Petlund, David Hayes, David Ros, Ing-Jyh Tsang, Stein Gjessing, Gorry Fairhurst, Carsten Griwodz, Michael WelzlPeer reviewedPreprin

Encaminhamento de tráfego por classes de serviço em redes DiffServ

Dissertação de mestrado integrado em Engenharia de ComunicaçõesAtualmente assistimos a um crescimento exponencial do número de aplicações que surgem para atender às necessidades dos utilizadores da Internet. As aplicações são cada vais mais avançadas e exigentes em termos de requisitos de Qualidade de Serviço. No entanto, os recursos e mecanismos disponibilizados pelas redes IP não acompanham esta evolução e não conseguem satisfazer estes novos requisitos. A comunidade científica tem proposto ao longo dos anos formas alternativas de resolver este problema, sendo uma delas a incorporação de mecanismos de QoS no encaminhamento. Neste sentido surgiram duas abordagens de encaminhamento com Qualidade de Serviço: uma abordagem por fluxo, onde as rotas são calculadas a pedido, e os recursos da rede são reservados ao longo de um caminho desde a origem até ao destino, para cada fluxo de dados; e uma abordagem por classes de serviço, onde os fluxos são agregados num número reduzido de classes de serviço, de acordo com os requisitos das aplicações, e os pacotes de dados são condicionados na rede IP, de acordo com a classe a que pertencem. Esta dissertação propõe uma estratégia de encaminhamento por classes de serviço, com mecanismos de diferenciação nos encaminhadores da rede. Divide-se em dois componentes: um modelo de diferenciação baseado no funcionamento do DiffServ, ao nível dos encaminhadores; e um protocolo de encaminhamento unicast por classes de serviço, que resulta de uma extensão ao protocolo OSPF. Os pacotes de dados são marcados numa das classes de serviço, e tratados pelos encaminhadores da rede de acordo com a classe a que pertencem. O protocolo de encaminhamento, por sua vez, passa a incluir nas tabelas de encaminhamento os caminhos mais curtos baseados em métricas relacionadas com os requisitos das classes de serviço, sendo os pacotes de dados encaminhados pelo melhor caminho percecionado pela classe de serviço a que pertencem. A estratégia foi implementada e testada usando o simulador de redes Network Simulator 3. O modelo de encaminhamento proposto foi alvo de comparação com outros modelos de encaminhamento e, mesmo numa situação de excesso de carga de tráfego com QoS a circular na rede, o modelo apresenta-se como uma solução eficiente para otimizar o desempenho das classes de serviço com requisitos de QoS, sem prejudicar o desempenho da classe Best Effort.Currently we have seen an exponential growth in the number of applications that emerge to serve the needs of the Internet users. Applications are increasingly advanced and more demanding in terms of quality of service requirements. However, the resources and mechanisms provided by IP Network are not yet prepared to meet these new requirements. In attempt of solving this problematic, emerged two approaches of routing with quality of service, a per-flow approach, where routes are calculated on demand and network resources are reserved along a path from source to destination for each data flow; and an approach per-classe, where flows are aggregated into a small number of service classes, according to the requirements of the applications and data packets are conditioned in the IP Network in accordance with the class they belong to. This Thesis presents a multi-classe routing strategy, with differentiation mechanisms in network routers. It is divided into two components: a model of differentiation based on DiffServ, and a unicast multi-classe routing protocol, based in an extension of OSPF. On the network routers, data packets are marked on one of the classes of service, and conditioned in accordance with the markings. The routing protocol in turn, includes in the routing tables the shortest paths based on metrics related to the requirements of classes of service, and data packets are forwarded by the best path according the class of service they belong. The strategy was implemented and tested using Network Simulator 3. The routing model proposed was compared with other routing models, and even in a situation of excess of QoS traffic on the network, the model presented, appears as an efficient solution to optimize the performance of QoS traffic, without significantly impair the performance of the Best Effort traffic

Quality of Service in Converged Systems with Elements Controlled by Neural Network

Kvalita služby (QoS) je v konvergovaných systémech důležitým parametrem. Disertační práce se zabývá výzkumem její implementace do navrženého nového síťového prvku. Byl navržen a implementován nový protokol inspirovaný IP protokolem. V rámci řešení disertační práce byl navržen nový síťový prvek – přepínač vybavený řízením založeným na neuronové síti. V rámci naplňování cílů disertační práce byly zkoumány současné metody řízení přepínačů, několik přepínačů napříč výkonnostním spektrem bylo proměřeno. Na základě získaných poznatků byl navržen čtyřportový přepínač se spojovacím polem založeným na křížovém spínači s externím řízením. Přepínač byl navržen tak, aby v maximální možné míře podporoval QoS. Spojovací pole je řízeno neuronovou sítí typu „feedforward backpropagation“. Navržený přepínač byl modelován v MATLABu a především v Simulinku. Provedené simulace prokázaly funkčnost navrženého řešení.The Quality of Service (QoS) is in converged systems an important parameter. The dissertation thesis deals with research of QoS implementation into a newly developed network element. There was designed and implemented new protocol, based on the IP. The dissertation thesis deals with proposal of a new network element – the switch controlled by a neural network. During the research have been measured switches cross a performance classes. On the base of the measurement was designed the new four-port switch with switch fabric build on crossbar switch with an external control. The switch was designed with maximum QoS support. The switch fabric is controlled by the feedforward backpropagation neural network. The designed switch was modeled in the MATLAB and Simulink. The simulations prove that developed solution is functional.