this paper introduces a resource management infrastructure for grid computing environments. the technique couples application performance prediction with a hierarchical multi-agent system. An initial system implementa...
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this paper introduces a resource management infrastructure for grid computing environments. the technique couples application performance prediction with a hierarchical multi-agent system. An initial system implementation utilises the performance prediction capabilities of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on local grid resources. the validation results show that a high level of accuracy can be obtained, that cross-platform comparisons can be easily undertaken, and that the estimates can be evaluated rapidly. A hierarchy of homogeneous agents are used to provide a scalable and adaptable abstraction of the grid system architecture. An agent is a representative of a local grid resource and is considered to be both a service provider and a service requestor. Agents are organised into a hierarchy and cooperate to provide service advertisement and discovery. A performance monitor and advisor has been developed to optimise the performance of the agent system. A case study with corresponding experimental results are included to demonstrate the efficiency of the resource management and scheduling system.
HARNESS is an experimental metacomputing system that supports dynamic software reconfiguration, both of the resources that comprise the virtual machine and the services provided therein. Plugins, or distributed module...
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HARNESS is an experimental metacomputing system that supports dynamic software reconfiguration, both of the resources that comprise the virtual machine and the services provided therein. Plugins, or distributed modules with certain properties, are the mainstay of this computing model. the plugin architecture greatly enhances reconfigurability, but it also aids failure resilience by providing a framework for the re-instantiation of some types of modules on surviving resources in the event of failures. this paper describes a recent scheme that consolidates this model of failure recovery and enables HARNESS to function as a heterogeneous distributed system that is resilient to a number of types of failures.
An efficient method for including the impact of uncertain input data along withthe impact of truncation errors in finite element calculations is presented. this method is based on the theory of interval numbers. the ...
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An efficient method for including the impact of uncertain input data along withthe impact of truncation errors in finite element calculations is presented. this method is based on the theory of interval numbers. the formulation involves a predictor-corrector approach that allows for wide interval values as input and maintains sharp results during calculations. Results that illustrate the method's improved sharpness for solid mechanics problems are presented.
Task scheduling is a key element in achieving highperformance from multicomputer systems. To be efficient, scheduling algorithms must be based on a cost model appropriate for computing systems in use. the optimal sch...
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Task scheduling is a key element in achieving highperformance from multicomputer systems. To be efficient, scheduling algorithms must be based on a cost model appropriate for computing systems in use. the optimal scheduling of tasks is NP-hard, and a large number of heuristic algorithms have been proposed for a variety of scheduling conditions (graph types, granularities or cost models). this paper studies the problem of task scheduling under the LogP model and presents boththeoretical and experimental results for a cluster-based, task duplication methodology.
the demand for real-time database services has been increasing recently. Examples include sensor data fusion, stock trading, decision support, web information services, and data-intensive smart spaces. In these system...
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ISBN:
(纸本)0769515584
the demand for real-time database services has been increasing recently. Examples include sensor data fusion, stock trading, decision support, web information services, and data-intensive smart spaces. In these systems, it is essential to execute transactions in time using fresh (temporally consistent) data. Due to the high service demand, many transactions may miss their deadlines regardless of their importance. To address the problem, we present a service differentiation architecture for real-time databases. Transactions are classified into several service classes based on their importance. Under overload, different degrees of deadline miss ratio guarantees are provided among the service classes according to their importance. A certain data freshness guarantee is also provided for the data accessed by timely transactions which finish within their deadlines. Feedback control is applied to support the miss ratio and freshness guarantees. In a simulation study, our service differentiation approach shows a significant performance improvement compared to the baseline approaches. the specified miss ratio and freshness are supported even in the presence of unpredictable workloads and data access patterns.
Withthe advent of Grid computing, scheduling strategies for distributed heterogeneous systems have either become irrelevant or have to be extended significantly to support Grid dynamics. In this paper, we describe a ...
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Withthe advent of Grid computing, scheduling strategies for distributed heterogeneous systems have either become irrelevant or have to be extended significantly to support Grid dynamics. In this paper, we describe a metascheduling architecture for a Grid system that takes into account boththe application and system level considerations. Results are presented to demonstrate the usefulness of the metascheduler.
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