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Distributed backup placement in networks.

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Τίτλος: Distributed backup placement in networks.
Συγγραφείς: Halldórsson, Magnús M., Köhler, Sven, Patt-Shamir, Boaz, Rawitz, Dror
Πηγή: Distributed Computing; Apr2018, Vol. 31 Issue 2, p83-98, 16p
Θεματικοί όροι: Data protection, Back up systems, Wireless localization, Distributed computing, Geographical positions
Περίληψη: We consider the backup placement problem, defined as follows. Some nodes (processors) in a given network have objects (e.g., files, tasks) whose backups should be stored in additional nodes for increased fault resilience. To minimize the disturbance in case of a failure, it is required that a backup copy should be located at a neighbor of the primary node. The goal is to find an assignment of backup copies to nodes which minimizes the maximum load (number or total size of backup copies) over all nodes in the network. It is known that a natural selfish local improvement policy has approximation ratio Ω(logn/loglogn); we show that it may take this policy Ω(n) time to reach equilibrium in the distributed setting. Our main result in this paper is a randomized distributed algorithm which finds a placement in polylogarithmic time and achieves approximation ratio Olognloglogn. We obtain this result using a randomized distributed approximation algorithm for f-matching in bipartite graphs that may be of independent interest. [ABSTRACT FROM AUTHOR]
Copyright of Distributed Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
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  – Url: https://dx.doi.org/doi:10.1007/s00446-017-0299-x
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IllustrationInfo
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  Data: Distributed backup placement in networks.
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  Data: <searchLink fieldCode="AR" term="%22Halldórsson%2C+Magnús+M%2E%22">Halldórsson, Magnús M.</searchLink><br /><searchLink fieldCode="AR" term="%22Köhler%2C+Sven%22">Köhler, Sven</searchLink><br /><searchLink fieldCode="AR" term="%22Patt-Shamir%2C+Boaz%22">Patt-Shamir, Boaz</searchLink><br /><searchLink fieldCode="AR" term="%22Rawitz%2C+Dror%22">Rawitz, Dror</searchLink>
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  Data: Distributed Computing; Apr2018, Vol. 31 Issue 2, p83-98, 16p
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Data+protection%22">Data protection</searchLink><br /><searchLink fieldCode="DE" term="%22Back+up+systems%22">Back up systems</searchLink><br /><searchLink fieldCode="DE" term="%22Wireless+localization%22">Wireless localization</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+computing%22">Distributed computing</searchLink><br /><searchLink fieldCode="DE" term="%22Geographical+positions%22">Geographical positions</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: We consider the <italic>backup placement</italic> problem, defined as follows. Some nodes (processors) in a given network have objects (e.g., files, tasks) whose backups should be stored in additional nodes for increased fault resilience. To minimize the disturbance in case of a failure, it is required that a backup copy should be located at a neighbor of the primary node. The goal is to find an assignment of backup copies to nodes which minimizes the maximum load (number or total size of backup copies) over all nodes in the network. It is known that a natural selfish local improvement policy has approximation ratio Ω(logn/loglogn)<inline-graphic></inline-graphic>; we show that it may take this policy Ω(n)<inline-graphic></inline-graphic> time to reach equilibrium in the distributed setting. Our main result in this paper is a randomized distributed algorithm which finds a placement in polylogarithmic time and achieves approximation ratio Olognloglogn<inline-graphic></inline-graphic>. We obtain this result using a randomized distributed approximation algorithm for <italic>f</italic>-matching in bipartite graphs that may be of independent interest. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Distributed Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s00446-017-0299-x
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      – Code: eng
        Text: English
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        PageCount: 16
        StartPage: 83
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      – SubjectFull: Data protection
        Type: general
      – SubjectFull: Back up systems
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      – SubjectFull: Wireless localization
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              Text: Apr2018
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