Resource management in IP-based radio access networks

IP is being considered to be used in the Radio Access Network (RAN) of UMTS. It is of paramount importance to be able to provide good QoS guarantees to real time services in such an IP-based RAN. QoS in IP networks is most efficiently provided with Differentiated services (Diffserv). However, currently Diffserv mainly specifies Per Hop Behaviors (PHB). Proper mechanisms for admission control and resource reservation have not yet been defined. A new resource management concept in the IP-based RAN is needed to offer QoS guarantees to real time services. We investigate the current Diffserv mechanisms and contribute to development of a new resource management protocol. We focus on the load control algorithm [9], which is an attempt to solve the problem of admission control and resource reservation in IP-based networks. In this document we present some load control issues and propose to enhance the load control protocol with the Measurement Based Admission Control (MBAC) concept. With this enhancement the traffic load in the IP-based RAN can be estimated, since the ingress router in the network path can be notified by marking packets with the resource state information. With this knowledge, the ingress router can perform admission control to keep the IP-based RAN stable with a high utilization even in overload situations

Cross-Layer Peer-to-Peer Track Identification and Optimization Based on Active Networking

P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a crosslayer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols

REDES NEURAIS APLICADAS À CLASSIFICAÇÃO DE TRÁFEGO DE REDES DE COMPUTADORES UTILIZANDO OS PROTOCOLOS TCP E UDP

This article presents the use of the Artificial Neural Network (ANN) on measurement and classification of traffic data using TCP and UDP transport protocols. I has been used the Adaline and Perceptron ANN to classify a data network traffic in the following categories: Source IP, destination IP, source port, destination port, type protocol (TCP or UDP and if the( connection started from the internal or external network. The implemented system allowed the traffic classification process can be done in a more dynamic way. Thus, the use of Artificial Neural Networks for classification and measurement of traffic on computer networks, using TCP and UDP transport protocols, was considered a productive way and applicable to the problem of classification of traffic data.Este artigo apresenta o uso da Rede Neural Artificial (RNA) na mensuração e classificação de dados trafegados utilizando os protocolos de transporte TCP e UDP. Foram utilizadas as RNAs Adaline e Perceptron  para classificar o tráfego de uma rede de dados nas seguintes categorias: IP de origem, IP de destino, porta de origem, porta de destino, tipo do protocolo (TCP ou UDP) e se a conexão partiu da rede interna ou externa. O sistema implementado permitiu que o processo  de classificação do tráfego seja feito de forma mais dinâmica. Assim, o uso de Redes Neurais Artificiais para a classificação e mensuração de tráfego de redes de computadores, utilizando protocolos de transporte TCP e UDP, foi considerado uma maneira produtiva e aplicável ao problema de classificação de dados trafegados

A novel non-intrusive objective method to predict voice quality of service in LTE networks.

This research aimed to introduce a novel approach for non-intrusive objective measurement of voice Quality of Service (QoS) in LTE networks. While achieving this aim, the thesis established a thorough knowledge of how voice traffic is handled in LTE networks, the LTE network architecture and its similarities and differences to its predecessors and traditional ground IP networks and most importantly those QoS affecting parameters which are exclusive to LTE environments. Mean Opinion Score (MOS) is the scoring system used to measure the QoS of voice traffic which can be measured subjectively (as originally intended). Subjective QoS measurement methods are costly and time-consuming, therefore, objective methods such as Perceptual Evaluation of Speech Quality (PESQ) were developed to address these limitations. These objective methods have a high correlation with subjective MOS scores. However, they either require individual calculation of many network parameters or have an intrusive nature that requires access to both the reference signal and the degraded signal for comparison by software. Therefore, the current objective methods are not suitable for application in real-time measurement and prediction scenarios. A major contribution of the research was identifying LTE-specific QoS affecting parameters. There is no previous work that combines these parameters to assess their impacts on QoS. The experiment was configured in a hardware in the loop environment. This configuration could serve as a platform for future research which requires simulation of voice traffic in LTE environments. The key contribution of this research is a novel non-intrusive objective method for QoS measurement and prediction using neural networks. A comparative analysis is presented that examines the performance of four neural network algorithms for non-intrusive measurement and prediction of voice quality over LTE networks. In conclusion, the Bayesian Regularization algorithm with 4 neurons in the hidden layer and sigmoid symmetric transfer function was identified as the best solution with a Mean Square Error (MSE) rate of 0.001 and regression value of 0.998 measured for the testing data set

An Internet Heartbeat

Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratization of Internet measurement, we consider the inferential power possible were the network to include a constant and predictable stream of dedicated lightweight measurement traffic. We posit an Internet "heartbeat," which nodes periodically send to random destinations, and show how aggregating heartbeats facilitates introspection into parts of the network that are today generally obtuse. We explore the design space of an Internet heartbeat, potential use cases, incentives, and paths to deployment

Packet loss characteristics of IPTV-like traffic on residential links

Packet loss is one of the principal threats to quality of experience for IPTV systems. However, the packet loss characteristics of the residential access networks which carry IPTV are not widely understood. We present packet level measurements of streaming IPTV-like traffic over four residential access links, and describe the extent and nature of packet loss we encountered. We discuss the likely impact of these losses for IPTV traffic, and outline steps which can ameliorate this