Experiments play an important role in parallel and distributedcomputing. Simulation is a common experimental technique that relies on abstractions of the tested application and execution environment but offers reprod...
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Networked computer systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these environments. A failure will cause one or...
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ISBN:
(纸本)9781424493289
Networked computer systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these environments. A failure will cause one or multiple computer(s) to be unavailable, which affects the resource utilization and system throughput. When a computer fails to function properly, health-related data are valuable for trouble shooting. However, it is challenging to effectively identify anomalies from the voluminous amount of noisy, high-dimensional data. In this paper, we present auto-AID, an autonomic mechanism for anomaly identification in networked computer systems. It is composed of a set of data mining techniques that facilitates automatic analysis of system health data. The identification results are very valuable for the system administrators to manage systems and schedule the available resources. We implement a prototype of auto-AID and evaluate it on a production institution wide compute grid. The results show that auto-AID can effectively identify anomalies with little human intervention.
This paper presents the structure and functionality of zFunction, which is an adaptive distributedcomputing platform that supports a user-friendly programming model for developing parallel processing applications. It...
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parallelcomputing is widely adotped in scientific and engineering applications to enhance the efficiency. Moreover, there are increasing research interests focusing on utilizing distributed networked computers for pa...
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ISBN:
(纸本)9780791849002
parallelcomputing is widely adotped in scientific and engineering applications to enhance the efficiency. Moreover, there are increasing research interests focusing on utilizing distributed networked computers for parallelcomputing. The Message Passing Interface (MPI) standard was designed to support portability and platform independence of a developed parallel program. However, the procedure to start an MPI-based parallel computation among distributed computers lacks autonomicity and flexibility. This article presents an autonomic dynamic parallelcomputing framework that provides autonomicity and flexibility that are important and necessary to some parallelcomputing applications involving resource constrained and heterogeneous platforms. In this framework, an MPI parallelcomputing environment consisting of multiple computing entities is dynamically established through inter-agent communications using the IEEE Foundation for Intelligent Physical Agents (FIPA) compliant Agent Communication Language (ACL) messages. For each computing entity in the MPI parallelcomputing environment, a load-balanced MPI program C source code along with the MPI environment configuration statements are dynamically composed as a mobile agent code. A mobile agent wrapping the mobile agent code is created and sent to the computing entity where the mobile agent code is retrieved and interpretively executed. An example of autonomic parallel matrix multiplication is given to demonstrate the self-configuration and self-optimization properties of the presented framework.
distributedcomputing and data mining are nowadays almost ubiquitous. Authors propose methodology of distributed data mining by combining local analytical models (built in parallel in nodes of a distributed computer s...
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ISBN:
(纸本)9783642132070
distributedcomputing and data mining are nowadays almost ubiquitous. Authors propose methodology of distributed data mining by combining local analytical models (built in parallel in nodes of a distributed computer system) into a. global one without necessity to construct distributed version of data mining algorithm. Different combining strategies for clustering and classification are proposed and their verification methods as well. Proposed solutions were tested with data sets coming from UCI Machine Learning Repository.
Cooperative distributed Problem Solving refers to a loosely coupled network of problem solvers working together to solve problems that may be beyond the capabilities of individual agents. Individual nodes may not have...
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The convergence rate of iterative stationary methods for the PageRank linear system is significant for efficient computation of the relative rank of web pages based on the Web graph. This paper investigates this probl...
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The proceedings contain 41 papers. The topics discussed include: Bayesian network inference with qualitative expert knowledge for decision support systems;semantic query validation in guided-based systems: assuring th...
ISBN:
(纸本)9780769540887
The proceedings contain 41 papers. The topics discussed include: Bayesian network inference with qualitative expert knowledge for decision support systems;semantic query validation in guided-based systems: assuring the construction of queries that make sense;user and item pattern matching in multi-criteria recommender systems;modeling of device collaboration process based on Petri net;CP-nets based methodology for integrating functional verification and performance analysis of network protocol;a novel security approach for critical information systems: preventing flooding in the non-authenticated client area using a new service from local network service providers;achieving flow-level controllability in network intrusion detection system;explaining classification by finding response-related subgroups in data;real-time implementation of synthetic aperture sonar imaging on high performance clusters;and recovering depth from a single image using dark channel prior.
Map Reduce is a key-value based programming model and an associated implementation for processing large data sets. It has been adopted in various scenarios and seems promising. However, when spatial computation is exp...
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As the complexity of current computer architecture increases, domain-specific program generators are extensively used to implement performance portable libraries. Dynamic programming is a performance-critical kernel i...
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