0000000000053766

AUTHOR

G. Di Fatta

Distributed intelligent management,of active networks

This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distribut…

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Context-Aware Visual Exploration of Molecular Databases

Facilitating the visual exploration of scientific data has\ud received increasing attention in the past decade or so. Especially\ud in life science related application areas the amount\ud of available data has grown at a breath taking pace. In this\ud paper we describe an approach that allows for visual inspection\ud of large collections of molecular compounds. In\ud contrast to classical visualizations of such spaces we incorporate\ud a specific focus of analysis, for example the outcome\ud of a biological experiment such as high throughout\ud screening results. The presented method uses this experimental\ud data to select molecular fragments of the underlying\ud molecules that have intere…

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Fast Training of Self Organizing Maps for the Visual Exploration of Molecular Compounds

Visual exploration of scientific data in life science\ud area is a growing research field due to the large amount of\ud available data. The Kohonen’s Self Organizing Map (SOM) is\ud a widely used tool for visualization of multidimensional data.\ud In this paper we present a fast learning algorithm for SOMs\ud that uses a simulated annealing method to adapt the learning\ud parameters. The algorithm has been adopted in a data analysis\ud framework for the generation of similarity maps. Such maps\ud provide an effective tool for the visual exploration of large and\ud multi-dimensional input spaces. The approach has been applied\ud to data generated during the High Throughput Screening\ud of mo…

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Context-Aware Visual Exploration of Molecular Datab

Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the res…

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Sub-Symbolic Encoding of Words in WordNet Environment

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A Reconfigurable Neural Environment on Active Networks

This paper proposes the deployment of a neural network computing environment on Active Networks. Active Networks are packet-switched computer networks in which packets can contain code fragments that are executed on the intermediate nodes. This feature allows the injection of small pieces of codes to deal with computer network problems directly into the network core, and the adoption of new computing techniques to solve networking problems. The goal of our project is the adoption of a distributed neural network for approaching tasks which are specific of the computer network environment. Dynamically reconfigurable neural networks are spread on an experimental wide area backbone of active no…

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Word Mapping in Semantic Hyperspaces

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A management architecture for active networks

In this paper we present an architecture for network and applications management, which is based on the Active Networks paradigm and shows the advantages of network programmability. The stimulus to develop this architecture arises from an actual need to manage a cluster of active nodes, where it is often required to redeploy network assets and modify nodes connectivity. In our architecture, a remote front-end of the managing entity allows the operator to design new network topologies, to check the status of the nodes and to configure them. Moreover, the proposed framework allows to explore an active network, to monitor the active applications, to query each node and to install programmable …

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A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those\ud policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the\ud hosts on the network borders, and the adoption of a suitable control\ud policy. This paper proposes the adoption of a fuzzy proportional\ud integral (FPI) controller as an active queue manager for Internet\ud routers. The analytical design of the proposed FPI controller is\ud carried out in analogy with a proportional integral (PI) controller,\ud which recently has been proposed for AQM. A genetic algorithm is\ud proposed for tuning of the FPI controller parameters with respect\ud to optimal disturbance rej…

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Efficient tree construction for the multicast problem

A new heuristic for the Steiner minimal tree problem is presented. The method described is based on the detection of particular sets of nodes in networks, the "hot spot" sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used as comparison terms in the experimental analysis which demonstrates the capability of the heuristic discussed.

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