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In this thesis, I study the spectral characteristics of large dynamic networks and formulate the spectral evolution model. The spectral evolution model applies to networks that evolve over time, and describes their spectral decompositions such as the eigenvalue and singular value decomposition. The spectral evolution model states that over time, the eigenvalues of a network change while its eigenvectors stay approximately constant.
I validate the spectral evolution model empirically on over a hundred network datasets, and theoretically by showing that it generalizes arncertain number of known link prediction functions, including graph kernels, path counting methods, rank reduction and triangle closing. The collection of datasets I use contains 118 distinct network datasets. One dataset, the signed social network of the Slashdot Zoo, was specifically extracted during work on this thesis. I also show that the spectral evolution model can be understood as a generalization of the preferential attachment model, if we consider growth in latent dimensions of a network individually. As applications of the spectral evolution model, I introduce two new link prediction algorithms that can be used for recommender systems, search engines, collaborative filtering, rating prediction, link sign prediction and more.
The first link prediction algorithm reduces to a one-dimensional curve fitting problem from which a spectral transformation is learned. The second method uses extrapolation of eigenvalues to predict future eigenvalues. As special cases, I show that the spectral evolution model applies to directed, undirected, weighted, unweighted, signed and bipartite networks. For signed graphs, I introduce new applications of the Laplacian matrix for graph drawing, spectral clustering, and describe new Laplacian graph kernels. I also define the algebraic conflict, a measure of the conflict present in a signed graph based on the signed graph Laplacian. I describe the problem of link sign prediction spectrally, and introduce the signed resistance distance. For bipartite and directed graphs, I introduce the hyperbolic sine and odd Neumann kernels, which generalize the exponential and Neumann kernels for undirected unipartite graphs. I show that the problem of directed and bipartite link prediction are related by the fact that both can be solved by considering spectral evolution in the singular value decomposition.

Die Arbeit beschäftigt sich mit der für Router und Kleingeräte entwickelten Linux-Distribution OpenWrt. Im ersten Teil der Arbeit wird die Erstellung von Softwarepaketen für OpenWrt erläutert und eine Anzeige- und Konfigurationskomponente für die Dateien des Quagga RIP-Daemons für die Benutzeroberfläche LuCI erstellt. Im zweiten Teil wird der Aufbau eines Testnetzwerkes mit OpenWrt Routern dokumentiert, sowie die Anbindung an VNUML-virtualisierte Netzwerke.

In this thesis a Java program is developed that can be used to visualize networks previously described in configuration files. These networks must consist of layer 2 switches and hosts only. After loading such a configuration file, the program will visualize the network, and the spanning tree algorithm IEEE 802.1D may be started. The program allows the user to modify specific attributes of switches and hosts. The hosts will be able to exchange messages. The switches are realized as threads so that they can run independently and parallel to each other. The absence of central coordination and control prevents the switches from sharing global knowledge. This characteristic renders the implementation closer to the way an actual network functions.

In this work, some network protocols with Wireshark Protokollanalyser should be observed and described the deal with them. Wireshark is an offshoot of "Ethereal", one of the most popular protocol analyzer. Wireshark analysis network traffic, draws on it and make it clear . For the simulation of the network is used VNUML. Since VNUML can only be used under Linux, andLinux is running as a virtual machine in between to work in Windows to be able to.

The high cost of routing infrastructure makes checking theories about larger nets a very difficult and expensive task. One possible approach to fight this problem is the use of virtual instead of physical infrastructure. OPNet- IT Guru software is a suite designed to simulate large nets and present relevant information. This allows validating extensive changes before actually implementing them on a productive network or testing theories without the overhead of a physical infrastructure.