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        <datestamp>2023-07-10</datestamp>
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          <dc:contributor>Gupta, Indranil</dc:contributor>
          <dc:contributor>Nahrstedt, Klara</dc:contributor>
          <dc:contributor>Abdelzaher, Tarek F.</dc:contributor>
          <dc:contributor>Milojicic, Dejan</dc:contributor>
          <dc:creator>Ko, Steven Y.</dc:creator>
          <dc:date>2009-08-05T01:17:36Z</dc:date>
          <dc:date>2009-08-05T01:17:36Z</dc:date>
          <dc:date>2009-08-04</dc:date>
          <dc:description>In large-scale distributed infrastructures such as clouds, Grids, peer-to-peer systems, and wide-area testbeds, users and administrators typically desire to perform on-demand operations that deal with the most up-to-date state of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to support on-demand operations efficiently, i.e., in a bandwidth- and response-efficient manner.
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.</dc:description>
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  Previous issue date: 2009-08-04</dc:description>
          <dc:identifier>http://hdl.handle.net/2142/13386</dc:identifier>
          <dc:language>en</dc:language>
          <dc:rights>Copyright 2009 Steven Y. Ko</dc:rights>
          <dc:subject>Distributed Systems</dc:subject>
          <dc:title>Efficient On-Demand Operations in Large-Scale Infrastructures</dc:title>
          <dc:type>Dissertation / Thesis</dc:type>
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            <department>Computer Science</department>
            <discipline>Computer Science</discipline>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <level>Dissertation</level>
            <name>Ph.D.</name>
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