Definition
The recent advances in high-speed networks and improved microprocessor performance are making clusters or networks of workstations an appealing vehicle for cost effective parallel computing. Clusters built using commodity hardware and software components are playing a major role in redefining the concept of supercomputing.



Clusters
A cluster is a type of parallel or distributed processing system, which consists of a collection of interconnected stand-alone computers cooperatively working together as a single, integrated com ....etc

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A page link based ensemble approach for categorical data clustering data flow diagrams ....etc

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need document for page link based cluster ensemble approach for categorical data ....etc

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A cluster is a type of parallel or distributed processing system, which consists of a collection of interconnected stand-alone computers co - operatively working together as a single, integrated computing resource. This cluster of computers shares common network characteristics like the same namespace and it is available to other computers on the network as a single resource. These computers are linked together using high-speed network interfaces between themselves and the actual binding together of the all the individual computers in the clust ....etc

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Design Of Cluster Logical Volume Manager

Abstract :

In an open systems environment, logical volume manager (LVM) virtualizes storage by consolidating physical storage into logical volumes, which are available to applications or file systems. LVMs are available on most Unix platforms (including Linux) and on Windows 2000. By assembling virtual storage volumes out of numerous physical devices, you can create storage configurations tuned for specific applications, without the limitations of specific hardware devices. Instead, you can make ....etc

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HBA DISTRIBUTED METADATA MANAGEMENT FOR LARGE SCALE CLUSTER BASED STORAGE SYSTEM

Abstract: An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers, here the technique used called HIERARCHICAL BLOOM FILTER ARRAYS (HBA) to map filenames to the metadata servers holding their metadata. The Bloom filter arrays with different levels of accuracies are used on each metadata server. The first one with low accuracy and used to capture the destination metad ....etc

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Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks

Abstract

The challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and quality-of-service (QoS) requirements. The clustering problem is modeled as a hypergraph partitioning and its resolution is based on a tabu search heuristic. Our approach ....etc

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Terracotta is Open Source JVM-level clustering software for Java. It delivers clustering as a runtime infrastructure service, which simplifies the task of clustering a Java application immensely, by effectively clustering the JVM underneath the application, instead of clustering the application itself. Terracotta's JVM-level clustering can turn single-node, multi-threaded applications into distributed, multi-node applications, often with no code changes. Terracotta uses standard bytecode manipulation techniques to plug into the Java Memory Mod ....etc

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Abstract

Although attempts have been made to solve the problem of clustering categorical data via cluster ensembles, with the cresults being competitive to conventional algorithms, it is observed that these techniques unfortunately generate a final data partition based on incomplete information. The underlying ensemble-information matrix presents only cluster-data point relations, with many entries being left unknown. The paper presents an analysis that suggests this problem degrades the quality of the clustering result, and it presents a ne ....etc

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Abstract
his paper represents a currency recognition systemusing ensemble neural network (ENN). The individualneural networks (NN) in an ENN are trained vianegative correlation learning. The object of usingnegative correlation learning (NCr) is to expertise theindividuals in an ensemble on different parts or portionofinput patterns. The available currencies in the marketconsist of new, old and noisy ones. It is often difficultfor machine to recognize these currencies; therefore wepropose a system that uses ENN to identify them. Weperfo ....etc

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