Application of simulated annealing to data distribution for all-to-all comparison problems in homogeneous systems

Zhang, Yi-Fan, Tian, Yu-Chu, Kelly, Wayne A., Fidge, Colin J., & Gao, Jing (2015) Application of simulated annealing to data distribution for all-to-all comparison problems in homogeneous systems. In Neural Information Processing: 22nd International Conference, ICONIP 2015, Proceedings Part III [Lecture Notes in Computer Science, Volume 9491], Springer, Istanbul, Turkey, pp. 683-691.

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Abstract

Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.

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ID Code: 87373
Item Type: Conference Paper
Refereed: Yes
Keywords: Big data, distributed computing, all-to-all comparison, data distribution, simulated annealing
DOI: 10.1007/978-3-319-26555-1_77
ISBN: 978-3-319-26554-4
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > DISTRIBUTED COMPUTING (080500) > Distributed Computing not elsewhere classified (080599)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Springer
Deposited On: 09 Sep 2015 00:27
Last Modified: 23 Dec 2015 04:51

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