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Adaptive resource management in large scale distributed systems

Adaptive resource management in large scale distributed systems
Adaptive resource management in large scale distributed systems

An emergent trend in large scale distributed systems enables collaboration between large numbers of independent resource providers. Grid computing and peer-to-peer computing are part of this trend. Resource management in such systems is inherently different from that found in traditional distributed systems, the key difference being that the new classes of systems are primarily designed to operate under inconsistent system information and temporally varying operating environments. Although primarily used to enable collaboration of computational resources, these systems have also found application in the field of distributed data management. Although the principles of grid computing and peer-to-peer computing have found many applications, little effort has been made to abstract the common requirements, in order to provide a conceptual resource framework. This thesis investigates the alleviation of such common requirements through investigations in the field of online scheduling, information dissemination in peer-to-peer networks, and query processing in distributed stream processing systems.

A survey of system types is provided to highlight the new trends observed. A top down approach to developing a unifying model seems inapplicable and the range of problems encountered in these system types can only be addressed by identifying common trends and addressing them individually. Consequently, three application domains have been identified in the respective fields of online scheduling, data dissemination and stream query processing. Each of these application class is investigated individually. For each application domain, a review of the state-of-the-art is followed by a precise definition of the problem addressed in the application domain and the solutions developed are substantiated with experimental evaluation. Findings from individual applications have been summarized to generalize the observations towards an overall hypothesis.

University of Southampton
Dialani, Vijay K
0cab6a27-4773-4fde-a1b2-043cd76ca419
Dialani, Vijay K
0cab6a27-4773-4fde-a1b2-043cd76ca419

Dialani, Vijay K (2005) Adaptive resource management in large scale distributed systems. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

An emergent trend in large scale distributed systems enables collaboration between large numbers of independent resource providers. Grid computing and peer-to-peer computing are part of this trend. Resource management in such systems is inherently different from that found in traditional distributed systems, the key difference being that the new classes of systems are primarily designed to operate under inconsistent system information and temporally varying operating environments. Although primarily used to enable collaboration of computational resources, these systems have also found application in the field of distributed data management. Although the principles of grid computing and peer-to-peer computing have found many applications, little effort has been made to abstract the common requirements, in order to provide a conceptual resource framework. This thesis investigates the alleviation of such common requirements through investigations in the field of online scheduling, information dissemination in peer-to-peer networks, and query processing in distributed stream processing systems.

A survey of system types is provided to highlight the new trends observed. A top down approach to developing a unifying model seems inapplicable and the range of problems encountered in these system types can only be addressed by identifying common trends and addressing them individually. Consequently, three application domains have been identified in the respective fields of online scheduling, data dissemination and stream query processing. Each of these application class is investigated individually. For each application domain, a review of the state-of-the-art is followed by a precise definition of the problem addressed in the application domain and the solutions developed are substantiated with experimental evaluation. Findings from individual applications have been summarized to generalize the observations towards an overall hypothesis.

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Published date: 2005

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Local EPrints ID: 465787
URI: http://eprints.soton.ac.uk/id/eprint/465787
PURE UUID: 78f7f5a3-1735-4dad-8c03-671f55fd5ebe

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Date deposited: 05 Jul 2022 03:04
Last modified: 16 Mar 2024 20:22

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Author: Vijay K Dialani

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