Cognitive networking techniques on content distribution networks

First we want to design a strategy based on Artificial Intelligence (AI) techniques with the aim of increasing peers download performance. Some AI algorithms can find patterns in the information available to a peer locally, and use it to predict values that cannot be calculated by means of mathematical formulas. An important aspect of these techniques is that can be trained in order to improve its interpretation of the local available information. With this process they can make more accurate predictions and perform better results. We will use this prediction system to increase our knowledge about the swarm and the peers who are part of it. This global knowledge increase can be used to optimize the algorithms of BitTorrent and can represent a great improvement in peers download capacity. Our second challenge is to create a reduced group of peers (Crowd) that focus their efforts on improving the condition of the swarm through collaborative techniques. The basic idea of this approach is to organize a group of peers to act as a single node and focus them on getting all pieces of the content they are interested in. This involves avoiding, as far as possible, to download pieces that any of the members already have. The main goal of this technique consists of reaching as quickly as possible a copy of the content distributed between all members of the Crowd. Getting a distributed copy of the content is expected to increase the availability of parts and reduce dependence on the seeds (users who have the complete content), which would represent a great benefit for the whole swarm. Another aspect that we want to investigate is the use of a priority system among members of the Crowd. We consider that in certain situations to prioritize the Crowd peers at expense of regular peers can result in a significant increase of the download ratio

Preliminary specification and design documentation for software components to achieve catallaxy in computational systems

This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing

A theoretical and computational basis for CATNETS

The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

A Survey of Methods for Encrypted Traffic Classification and Analysis

With the widespread use of encrypted data transport network traffic encryption is becoming a standard nowadays. This presents a challenge for traffic measurement, especially for analysis and anomaly detection methods which are dependent on the type of network traffic. In this paper, we survey existing approaches for classification and analysis of encrypted traffic. First, we describe the most widespread encryption protocols used throughout the Internet. We show that the initiation of an encrypted connection and the protocol structure give away a lot of information for encrypted traffic classification and analysis. Then, we survey payload and feature-based classification methods for encrypted traffic and categorize them using an established taxonomy. The advantage of some of described classification methods is the ability to recognize the encrypted application protocol in addition to the encryption protocol. Finally, we make a comprehensive comparison of the surveyed feature-based classification methods and present their weaknesses and strengths.Šifrování síťového provozu se v dnešní době stalo standardem. To přináší vysoké nároky na monitorování síťového provozu, zejména pak na analýzu provozu a detekci anomálií, které jsou závislé na znalosti typu síťového provozu. V tomto článku přinášíme přehled existujících způsobů klasifikace a analýzy šifrovaného provozu. Nejprve popisujeme nejrozšířenější šifrovací protokoly, a ukazujeme, jakým způsobem lze získat informace pro analýzu a klasifikaci šifrovaného provozu. Následně se zabýváme klasifikačními metodami založenými na obsahu paketů a vlastnostech síťového provozu. Tyto metody klasifikujeme pomocí zavedené taxonomie. Výhodou některých popsaných klasifikačních metod je schopnost rozeznat nejen šifrovací protokol, ale také šifrovaný aplikační protokol. Na závěr porovnáváme silné a slabé stránky všech popsaných klasifikačních metod

An architectural framework for self-configuration and self-improvement at runtime

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