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        <datestamp>2024-03-06T10:41:42Z</datestamp>
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          <dc:title>Dynamic Reconfiguration: Abstraction and Optimal Asynchronous Solution</dc:title>
          <dc:creator>Spiegelman, Alexander</dc:creator>
          <dc:creator>Keidar, Idit</dc:creator>
          <dc:creator>Malkhi, Dahlia</dc:creator>
          <dc:subject>Reconfiguration</dc:subject>
          <dc:subject>Dynamic Objects</dc:subject>
          <dc:subject>Optimal Algorithm</dc:subject>
          <dc:description>Providing clean and efficient foundations and tools for reconfiguration is a crucial enabler for distributed system management today. This work takes a step towards developing such foundations. It considers classic fault-tolerant atomic objects emulated on top of a static set of fault-prone servers, and turns them into dynamic ones. The specification of a dynamic object extends the corresponding static (non-dynamic) one with an API for changing the underlying set of fault-prone servers. Thus, in a dynamic model, an object can start in some configuration and continue in a different one. Its liveness is preserved through the reconfigurations it undergoes, tolerating a versatile set of faults as it shifts from one configuration to another.&#13;
&#13;
In this paper we present a general abstraction for asynchronous reconfiguration, and exemplify its usefulness for building two dynamic objects: a read/write register and a max-register. We first define a dynamic model with a clean failure condition that allows an administrator to reconfigure the system and switch off a server once the reconfiguration operation removing it completes. We then define the Reconfiguration abstraction and show how it can be used to build dynamic registers and max-registers. Finally, we give an optimal asynchronous algorithm implementing the Reconfiguration abstraction, which in turn leads to the first asynchronous (consensus-free) dynamic register emulation with optimal complexity. More concretely, faced with n requests for configuration changes, the number of configurations that the dynamic register is implemented over is n; and the complexity of each client operation is O(n).</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Alexander Spiegelman and Idit Keidar and Dahlia Malkhi</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 91, 31st International Symposium on Distributed Computing (DISC 2017)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.DISC.2017.40</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-79673</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2017.40</dc:identifier>
          <dc:language>eng</dc:language>
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