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Title:Efficient on -Demand Operations in Large-Scale Infrastructures
Author(s):Ko, Steven Y.
Doctoral Committee Chair(s):Gupta, Indranil
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Computer Science
Abstract:This dissertation discusses several on-demand operations, challenges associated with them, and system designs that meet these challenges. Specifically, we design and implement techniques for (1) on-demand group monitoring that allows users and administrators of an infrastructure to query and aggregate the up-to-date state of the machines (e.g., CPU utilization) in one or multiple groups, (2) on-demand storage for intermediate data generated by dataflow programming paradigms running in clouds, (3) on-demand Grid scheduling that makes worker-centric scheduling decisions based on the current availability of compute nodes, and (4) on-demand key/value pair lookup that is overlay-independent and perturbation-resistant. We evaluate these on-demand operations using large-scale simulations with traces gathered from real systems, as well as via deployments over real testbeds such as Emulab and PlanetLab.
Issue Date:2009
Description:120 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.
Other Identifier(s):(MiAaPQ)AAI3392096
Date Available in IDEALS:2015-09-25
Date Deposited:2009

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