Scheduling Distributed Clusters of Parallel Machines : Primal-Dual and LP-based Approximation Algorithms

The Map-Reduce computing framework rose to prominence with datasets of such size that dozens of machines on a single cluster were needed for individual jobs. As datasets approach the exabyte scale, a single job may need distributed processing not only on multiple machines, but on multiple clusters ....

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Bibliographic Details
Published in:	Algorithmica Vol. 80; no. 10; pp. 2777 - 2798
Main Authors:	Murray, Riley, Khuller, Samir, Chao, Megan
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.10.2018 Springer Nature B.V
Subjects:	Algorithm Analysis and Problem Complexity Algorithms Approximation Clusters Combinatorial analysis Completion time Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Datasets Distributed processing Employment Mapping Mathematics of Computing Production scheduling Scheduling Theory of Computation Approximation algorithms Primal-dual algorithms Machine scheduling F.2.2 Nonnumerical Algorithms and Problems LP relaxations Distributed computing
ISSN:	0178-4617, 1432-0541
Online Access:	Get full text
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