Entity

Time filter

Source Type

Madrid, Spain

Fischer L.,Nordunet | Belter B.,PSNC | Przywecki M.,PSNC | Cosin M.,RedIRIS | And 6 more authors.
TERENA Networking Conference 2010: Living the Network Life, TNC 2010 | Year: 2010

This paper describes research carried out by the GN3 project into network federation, i.e. sharing resources among multiple independent networks. The aim of the research is to investigate how federated networks can contribute to the research and education networks' goal of improving performance and end-user service and reducing costs. To achieve this objective, we have assessed user demand for federated networks, analysing current and future projects requiring international data transmission, and investigated the three key building blocks for federated networks - network, operations and services - with particular reference to their current status among European NRENs and their potential usefulness or limitations for establishing a federation of research networks. We have used our findings to consider the architectural principles of federated networks and to develop models that optimise the use of shared resources and improve services. We have developed test cases to help refine the models, including one to support the Large Hadron Collider network, and have assessed the implications of a federated approach for both network operations and service delivery. Each of these aspects of our research is described in this paper, prefaced by a summary of the benefits and challenges of network federation and concluding with an outline of future work. The research's originality lies in its exploitation of leading-edge technologies, its innovative proposals for international collaboration, its access to and application of primary data sources. The results are of value not only to GÉANT and European NRENs but also to any special-purpose network and core networks in general. Source


Pouzols F.M.,Aalto University | Lopez D.R.,RedIRIS | Barros A.B.,Institute Microelectronica Of Seville
Studies in Computational Intelligence | Year: 2011

The structure and behavior of packet switched networks is difficult to model in a way comparable to many natural and artificial systems. Nonetheless, the Internet is an outstanding and challenging case because of its incredibly fast development, unparalleled heterogeneity and the inherent lack of measurement and monitoring mechanisms in its core conception. In short, packet switched networks defy analytical modeling. This chapter is intended to introduce and provide concise descriptions of some of the building blocks of what some authors call Internet Science [21, 104], i.e., the study of laws and patterns in Internet structure. Additional related aspects that will be used throughout the next chapters are discussed as well. We will briefly define and describe the most relevant concepts about Internet performance and measurement that will be used throughout the next chapters. However, we will not get into details about all the networking concepts this monograph deals with.We refer to [37] for a good overall and in-depth analysis of traffic measurement and performance analysis. There are also a number of research papers that provide good insight into more specific topics. Among these, we highlight [21], where some key mathematical concepts in Internet traffic analysis are discussed. It is also out of the scope of this monograph to analyze in detail the mathematical aspects of most of the concepts this monograph deals with, and in particular those related to traffic control. For this, we refer the interested reader to [153] and [15]. Some of the most relevant and seminal research papers in this area can also be consulted [134, 132, 129, 171, 71]. © 2011 Springer-Verlag Berlin Heidelberg. Source


Pouzols F.M.,Aalto University | Lopez D.R.,RedIRIS | Barros A.B.,Institute Microelectronica Of Seville
Studies in Computational Intelligence | Year: 2011

Understanding the dynamics and performance of packet switched networks on the basis of measurements enables practitioners to optimize resources. As network measurement research further advances and new measurement tools and infrastructures are available, the task of network operation becomes more and more complex. In this chapter we apply the methodology developed in the previous chapter to time series concerning network traffic load. An extensive predictability analysis is performed using the same nonparametric residual variance estimation technique that is integrated into the prediction methodology. Based on the predictability results, fuzzy inference based models that are both interpretable and accurate are derived for a wide set of heterogeneous time series for network traffic. © 2011 Springer-Verlag Berlin Heidelberg. Source


Pouzols F.M.,Aalto University | Lopez D.R.,RedIRIS | Barros A.B.,Institute Microelectronica Of Seville
Studies in Computational Intelligence | Year: 2011

In this chapter, we focus on long-term modeling and prediction of univariate nonlinear time series. First, a method for long-term time series prediction by means of fuzzy inference systems combined with residual variance estimation techniques is developed and validated through a number of time series prediction benchmarks. This method provides an automatic means of modeling and predicting network traffic load, and can thus be classified as a method for predictive data mining. Although the primary focus in this section is to develop a methodology for building simple and thus interpretable fuzzy inference systems, it will be shown that they also outperform some of the most accurate and commonly used techniques in the field of time series prediction. © 2011 Springer-Verlag Berlin Heidelberg. Source


Pouzols F.M.,Aalto University | Lopez D.R.,RedIRIS | Barros A.B.,Institute Microelectronica Of Seville
Studies in Computational Intelligence | Year: 2011

This chapter looks into the practical implementation of some of the fuzzy inference systems proposed in previous chapters. Both architectural and operational constraints are considered. The focus is on an open FPGA-based hardware platform for the implementation of efficient fuzzy inference systems for solving problems in high-performance packet switched networks. A feasibility study is conducted in order to show that the techniques developed can be deployed in current and future network scenarios with satisfactory performance. © 2011 Springer-Verlag Berlin Heidelberg. Source

Discover hidden collaborations