Replica Placement for Availability in the Worst Case
We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects...
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sg-smu-ink.sis_research-39182020-07-22T07:41:41Z Replica Placement for Availability in the Worst Case Li, Peng GAO, Debin Reiter, Mike We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects which nodes to fail to minimize the number of objects that remain available. We specifically explore placement strategies based on combinatorial structures called t-packings; provide a lower bound for the object availability they offer; show that these placements offer availability that is c-competitive with optimal; propose an efficient algorithm for computing combinations of t-packings that maximize their availability lower bound; and provide parameter selection strategies to concretely instantiate our schemes for different system sizes. We compare the availability offered by our approach to that of random replica placement, owing to the popularity of the latter approach in previous work. After quantifying the availability offered by random replica placement in our model, we show that our combinatorial strategy yields placements with better availability than random replica placement for many realistic parameter values. 2015-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2918 info:doi/10.1109/ICDCS.2015.67 https://ink.library.smu.edu.sg/context/sis_research/article/3918/viewcontent/icdcs15.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University availability replica placement replication OS and Networks |
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availability replica placement replication OS and Networks Li, Peng GAO, Debin Reiter, Mike Replica Placement for Availability in the Worst Case |
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We explore the problem of placing object replicas on nodes in a distributed system to maximize the number of objects that remain available when node failures occur. In our model, failing (the nodes hosting) a given threshold of replicas is sufficient to disable each object, and the adversary selects which nodes to fail to minimize the number of objects that remain available. We specifically explore placement strategies based on combinatorial structures called t-packings; provide a lower bound for the object availability they offer; show that these placements offer availability that is c-competitive with optimal; propose an efficient algorithm for computing combinations of t-packings that maximize their availability lower bound; and provide parameter selection strategies to concretely instantiate our schemes for different system sizes. We compare the availability offered by our approach to that of random replica placement, owing to the popularity of the latter approach in previous work. After quantifying the availability offered by random replica placement in our model, we show that our combinatorial strategy yields placements with better availability than random replica placement for many realistic parameter values. |
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text |
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Li, Peng GAO, Debin Reiter, Mike |
author_facet |
Li, Peng GAO, Debin Reiter, Mike |
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Li, Peng |
title |
Replica Placement for Availability in the Worst Case |
title_short |
Replica Placement for Availability in the Worst Case |
title_full |
Replica Placement for Availability in the Worst Case |
title_fullStr |
Replica Placement for Availability in the Worst Case |
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Replica Placement for Availability in the Worst Case |
title_sort |
replica placement for availability in the worst case |
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Institutional Knowledge at Singapore Management University |
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2015 |
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https://ink.library.smu.edu.sg/sis_research/2918 https://ink.library.smu.edu.sg/context/sis_research/article/3918/viewcontent/icdcs15.pdf |
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