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ISPRS Int. J. Geo-Inf. 2016, 5(8), 141; doi:10.3390/ijgi5080141

Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms

1,2,* , 1,2
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 20 May 2016 / Revised: 24 July 2016 / Accepted: 29 July 2016 / Published: 10 August 2016
View Full-Text   |   Download PDF [4406 KB, uploaded 10 August 2016]   |  


Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1) It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2) It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency. View Full-Text
Keywords: task scheduling; Hypergraph+; spatial data processing; master-slave platforms task scheduling; Hypergraph+; spatial data processing; master-slave platforms

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Cheng, B.; Guan, X.; Wu, H.; Li, R. Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms. ISPRS Int. J. Geo-Inf. 2016, 5, 141.

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