TY - GEN

T1 - Distributed Backup Placement in Networks

AU - Halldórsson, Magnús M.

AU - Köhler, Sven

AU - Patt-Shamir, Boaz

AU - Rawitz, Dror

PY - 2015

Y1 - 2015

N2 - 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 copies) over all nodes in the network. It is known that a natural selfish local improvement policy has approximation ratio Ω(log n / log log n); 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 distributed algorithm which finds a placement in polylogarithmic time and achieves approximation ratio O(log n/log log n). We obtain this result using a distributed approximation algorithm for f-matching in bipartite graphs that may be of independent interest.

AB - 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 copies) over all nodes in the network. It is known that a natural selfish local improvement policy has approximation ratio Ω(log n / log log n); 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 distributed algorithm which finds a placement in polylogarithmic time and achieves approximation ratio O(log n/log log n). We obtain this result using a distributed approximation algorithm for f-matching in bipartite graphs that may be of independent interest.

KW - load balancing

KW - distributed algorithms

KW - approximation algorithms

KW - f-matching

UR - https://www.mendeley.com/catalogue/bd5acc21-270c-3d71-8c42-cb0044e35c43/

U2 - 10.1145/2755573.2755583

DO - 10.1145/2755573.2755583

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SN - 9781450335881

T3 - SPAA '15

SP - 274

EP - 283

BT - Proceedings of the 27th ACM Symposium on Parallelism in Algorithms and Architectures

PB - Association for Computing Machinery

CY - New York, NY, USA

ER -