Decentralized Dynamic Resource Allocation for Workflows in Grid Environments

In this paper we present an innovative decentralized dynamic resource scheduling solution of large scale application workflows onto distributed, heterogeneous grid environments. The presented resource allocation solution aims to optimize large-scale scientific application workflows by efficiently an...

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Vydáno v:Symbolic and Numeric Algorithms for Scientific Computing, Proceedings s. 557 - 563
Hlavní autoři: Pop, F., Dobre, C., Cristea, V.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.09.2008
Témata:
Application software
Computational modeling
Context modeling
Decentralized Architecture
Dynamic scheduling
Environmental management
Grid computing
Grid Scheduling
Large-scale systems
Processor scheduling
Resource Allocation
Resource management
Scheduling algorithm
Simulation
Workflows Management
ISBN:0769535232, 9780769535234
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Shrnutí:In this paper we present an innovative decentralized dynamic resource scheduling solution of large scale application workflows onto distributed, heterogeneous grid environments. The presented resource allocation solution aims to optimize large-scale scientific application workflows by efficiently and effectively mapping and scheduling them onto grid resources. The proposed solution is part of a framework that aims to help scientists easily deploy large-scale scientific workflow applications from a wide-range of research fields. The decentralized architecture, together with the scheduling policies and fault management being proposed in this paper, are specifically designed to optimize the scheduling management for workflows in case of a wide range of grid environment. In order to demonstrate the validity and performance of the presented scheduling solution we propose using modeling and simulation techniques. For that we present the characteristics of a generic simulator that includes all the necessary components to help in evaluating a wide-range of scheduling procedures, such as the ones presented in this, in the context of large-scale heterogeneous grid environment.
ISBN:0769535232
9780769535234
DOI:10.1109/SYNASC.2008.15