The increasing complexity, heterogeneity and dynamism of networks, systems, services applications have made our computational/information infrastructure brittle, unmanageable and insecure. This has necessitated the in...
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The increasing complexity, heterogeneity and dynamism of networks, systems, services applications have made our computational/information infrastructure brittle, unmanageable and insecure. This has necessitated the investigation of a new paradigm for design, development and deployment based on strategies used by biological systems to deal with complexity, heterogeneity, and uncertainty, i.e. autonomic computing. This paper introduces the AutoMate project and describes its key components. The overall objective of AutoMate is to investigate key technologies to enable the development of autonomic grid applications that are context aware and are capable of self-configuring, self-composing, self-optimizing and self-adapting. Specifically, it will investigate the definition of autonomic components, the development of autonomic applications as dynamic composition of autonomic components, and the design of key enhancements to existing grid middleware and runtime services to support these applications.
Clusters of workstations are being extensively used for solving computationally intensive scientific problems. However, there is limited support for quality of service (QoS) based distributed computing on commercial o...
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Clusters of workstations are being extensively used for solving computationally intensive scientific problems. However, there is limited support for quality of service (QoS) based distributed computing on commercial off- the-shelf (COTS) clusters. This limitation has restricted successful deployment of distributed real-time high-performance computing applications to customized and dedicated embedded multi-processor systems. This paper describes research work that attempts to provide a cluster platform that can guarantee access to computational and communication resources to distributed applications. The authors have developed PromisQoS, an architecture that supports execution of hard real-time distributed applications on a Linux cluster while providing high-throughput and low-latency communication using Myrinet. PromisQoS consists of the following major components - Hare, BDM-RT and Turtle. Hare is a prototype implementation of time-based QoS channels specified by the real-time message passing interface (MPI/RT 1.1) standard. BDM-RT is a low-level messaging library on Myrinet that provides deterministic communication latency and bandwidth on Myrinet. Turtle, a variant of RT-Linux, is the real-time operating system that provides guaranteed computation time. This work demonstrates that it is possible to deploy hard real-time distributed applications on COTS clusters and underlines the significance of the MPI/RT API in the realm of distributed high-performance computing applications that require QoS.
The emergence of the computational Grid and the potential for seamless aggregation, integration and interactions has made it possible to conceive a new generation of realistic, scientific and engineering simulations o...
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The emergence of the computational Grid and the potential for seamless aggregation, integration and interactions has made it possible to conceive a new generation of realistic, scientific and engineering simulations of complex physical phenomena. The inherently heterogeneous and dynamic nature of these application and the Grid presents significant runtime management challenges. In this paper we extend the PRAGMA framework to enable self adapting, self optimizing runtime management of dynamically adaptive applications. Specifically, we present the design, prototype implementation and initial evaluation of policies and mechanisms that enable PRAGMA to autonomically manage, adapt and optimize structured adaptive mesh refinement applications (SAMR) based on current system and application state and predictive models for system behavior and application performance. We use the 3-D adaptive Richtmyer-Meshkov compressible fluid dynamics application and Beowulf clusters at Rutgers University, University of Arizona, and NERSC to develop our performance models, and define and evaluate our adaptation policies. In our prototype, the predictive performance models capture computational and communicational loads and, along with current system state, adjust processors capacities at runtime to enable the application to adapt and optimize its performance.
Based on the advances of research in cognitive informatics and related fields, this paper attempts to develop a layered reference model of the brain that explains the functional mechanisms and cognitive processes of t...
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ISBN:
(纸本)0769519865
Based on the advances of research in cognitive informatics and related fields, this paper attempts to develop a layered reference model of the brain that explains the functional mechanisms and cognitive processes of the natural intelligence. A variety of life functions and cognitive processes have been identified in cognitive informatics, cognitive science, neuropsychology, and neurophilosophy. In order to formally and rigorously describe a comprehensive and coherent set of mental processes and their relationships, an integrated reference model of the brain is established, which encompasses 37 cognitive processes at six layers known as the sensation, memory, perception, action, meta and higher cognitive layers from bottom up. The reference model of the brain may be applied to explain a wide range of physiological, psychological, and cognitive phenomena in cognitive informatics, particularly relationships between the inherited and the acquired life functions, as well as the subconscious and conscious cognitive processes.
Partition method of interval is adopted in current classification based on associations (CBA), but this method cannot reflect the actual distribution of data and exists the problem of sharp boundary. Quantitative attr...
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ISBN:
(纸本)0780381386
Partition method of interval is adopted in current classification based on associations (CBA), but this method cannot reflect the actual distribution of data and exists the problem of sharp boundary. Quantitative attributes are partitioned into several fuzzy sets by fuzzy c-means algorithm, and search technology of Apriori algorithm is improved to discover interesting fuzzy association rules, which are used to build classification system. Because fuzzy c-means algorithm can embody the actual distribution of the data and fuzzy sets can soften partition boundary, the classification system of the fuzzy association rules can obtain better classification accuracy than two popular classification methods: C4.5 and CBA
Web-based logs contain potentially useful data with which designers can assess the usability and effectiveness of their choices. Clustering techniques have been used to automatically discover typical user profiles fro...
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ISBN:
(纸本)9780769519326
Web-based logs contain potentially useful data with which designers can assess the usability and effectiveness of their choices. Clustering techniques have been used to automatically discover typical user profiles from Web access logs recently. But it is a challenging problem to design effective similarity measure between the session vectors, which are usually high dimensional and sparse. Nonnegative matrix factorisation approaches are applied to dimensionality reduction of the session-URL matrix, and the spherical k-means algorithm is used to partition the projecting vectors of the user session vectors into several clusters. Two methods for discovering typical user session profiles from the clusters are presented last. The results of experiment show that our algorithms can mine interesting user profiles effectively.
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