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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Heterogeneous networked clusters are being increasingly used as platforms for resource-intensive parallel and distributed applications. The fundamental underlying idea is to provide large amounts of processing capacit...
Heterogeneous networked clusters are being increasingly used as platforms for resource-intensive parallel and distributed applications. The fundamental underlying idea is to provide large amounts of processing capacity over extended periods of time by harnessing the idle and available resources on the network in an opportunistic manner. In this paper we present the design, implementation and evaluation of a framework that uses JavaSpaces to support this type of opportunistic adaptive parallel/distributed computing over networked clusters in a non-intrusive manner. The framework targets applications exhibiting coarse grained parallelism and has three key features: (1) portability across heterogeneous platforms, (2) minimal configuration overheads for participating nodes, and (3) automated system state monitoring (using SNMP) to ensure non-intrusive behavior. Experimental results presented in this paper demonstrate that for applications that can be broken into coarse-grained, relatively independent tasks, the opportunistic adaptive parallel computing framework can provide performance gains. Furthermore, the results indicate that monitoring and reacting to the current system state minimizes the intrusiveness of the framework.
The ability to efficiently discover information using partial knowledge (for example keywords, attributes or ranges) is important in large, decentralized, resource sharing distributed environments such as computationa...
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ISBN:
(纸本)9780769519654
The ability to efficiently discover information using partial knowledge (for example keywords, attributes or ranges) is important in large, decentralized, resource sharing distributed environments such as computational grids and peer-to-peer (P2P) storage and retrieval systems. This paper presents a P2P information discovery system that supports flexible queries using partial keywords and wildcards, and range queries. It guarantees that all existing data elements that match a query are found with bounded costs in terms of number of messages and number of peers involved. The key innovation is a dimension reducing indexing scheme that effectively maps the multidimensional information space to physical peers. The design, implementation and experimental evaluation of the system are presented.
In this paper we present the design, implementation and evaluation of the Grid-enabled Discover middleware substrate. The middleware substrate enables Grid infrastructure services provided by the Globus Toolkit (secur...
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The paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems that operate in dynamic environments. Interesting aspects of the model include dynamic environm...
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Many similarities can be found between military training and computer game simulators. A review of definitions and classifications of military training simulators suggests that an adoption of DoD terminology also woul...
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ISBN:
(纸本)1565552687
Many similarities can be found between military training and computer game simulators. A review of definitions and classifications of military training simulators suggests that an adoption of DoD terminology also would suit game industry requirements. Similarities between applications are exemplified. Adhering to a common standard could possibly impose a challenge to both sectors because of (a) the rapid development of new concepts in the games sector, (b) the crossover between genres, and (c) the increasingly unclear distinction between "live" applications and simulations. The conclusion proposes further investigation into possible category dimensions that may emanate from research.
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.
In this paper we propose a method to create discrete abstraction of state space behavior for continuous-time systems based on gradient analysis of the system dynamics. Then we describe how to use such a discrete model...
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In this paper we propose a method to create discrete abstraction of state space behavior for continuous-time systems based on gradient analysis of the system dynamics. Then we describe how to use such a discrete model to design a supervisory controller for a given safety specification for the system. Finally we provide an entropy measure of nondeterminism, which can be used to evaluate the quality of the result discrete model as the degree of nondeterminism in that model.
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