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A Fault Tolerant Decentralized Scheduling in Large Scale Distributed Systems

A Fault Tolerant Decentralized Scheduling in Large Scale Distributed Systems

Florin Pop
Copyright: © 2010 |Pages: 23
ISBN13: 9781615206865|ISBN10: 1615206868|EISBN13: 9781615206872
DOI: 10.4018/978-1-61520-686-5.ch024
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MLA

Pop, Florin. "A Fault Tolerant Decentralized Scheduling in Large Scale Distributed Systems." Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications, edited by Nick Antonopoulos, et al., IGI Global, 2010, pp. 566-588. https://doi.org/10.4018/978-1-61520-686-5.ch024

APA

Pop, F. (2010). A Fault Tolerant Decentralized Scheduling in Large Scale Distributed Systems. In N. Antonopoulos, G. Exarchakos, M. Li, & A. Liotta (Eds.), Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications (pp. 566-588). IGI Global. https://doi.org/10.4018/978-1-61520-686-5.ch024

Chicago

Pop, Florin. "A Fault Tolerant Decentralized Scheduling in Large Scale Distributed Systems." In Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies and Applications, edited by Nick Antonopoulos, et al., 566-588. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-61520-686-5.ch024

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Abstract

This chapter presents a fault tolerant framework for the applications scheduling in large scale distributed systems (LSDS). Due to the specific characteristics and requirements of distributed systems, a good scheduling model should be dynamic. More specifically, it should adapt the scheduling decisions to resource state changes, which are commonly captured through monitoring. The scheduler and the monitor are two important middleware pieces that correlate their actions to ensure the high performance execution of distributed applications. The chapter presents and analyses agent based architecture for scheduling in large scale distributed systems. Then the user and resources management are presented. Optimization schemes for scheduling consider the near-optimal algorithm for distributed scheduling. The chapter presents the solution for scheduling optimization. The chapter covers and explains the fault tolerance cases for Grid environments and describes two possible scenarios for scheduling system.

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