Title: Fault-tolerant parallel computing for DEM data blocks with layered dependent relationships based on redundancy mechanism

Authors: Wanfeng Dou; Shoushuai Miao; Yan Li

Addresses: School of Computer Science and Technology, Nanjing Normal University, Jiangsu Nanjing, 210023, China; Research Center of Information Security and Privacy Technology, Jiangsu Nanjing, 210097, China; Virtual Geographic Environment Key Laboratory of the Ministry of Education, Nanjing Normal University, Jiangsu Nanjing, 210023, China ' School of Computer Science and Technology, Nanjing Normal University, Jiangsu Nanjing, 210023 China ' School of Computer Science and Technology, Nanjing Normal University, Jiangsu Nanjing, 210023, China

Abstract: The objective of this paper is to build a quantitative method of data partition in parallelisation of digital terrain analysis (DTA) so as to guide the design of algorithms in parallel computing. According to the data-intensive characteristics of the digital elevation model (DEM), a data dependency model is proposed to describe the hierarchical relationships of data blocks. The parallel schedule policies and algorithms for the DEM are built according to the model. With the increase of computing scale in data or tasks, the reliability of the calculation must also be considered in parallel computing. A fault-tolerant parallel computing method is proposed based on the data dependence graph. Respectively, this paper puts forward parallel computing algorithms of two times redundant, three times redundant and partially redundant, with a discussion of their respective advantages. Finally, a visibility algorithm in DTA as an example is used to verify the validity of the strategies and methods.

Keywords: DTA; digital terrain analysis; data partitioning; parallelism; fault-tolerant computing; fault tolerance; parallel computing; DEM data blocks; digital elevation model; layered dependent relationships; redundancy; data dependency models; parallel scheduling.

DOI: 10.1504/IJHPCN.2015.072784

International Journal of High Performance Computing and Networking, 2015 Vol.8 No.4, pp.337 - 344

Received: 08 May 2014
Accepted: 07 Oct 2014
Published online: 03 Nov 2015 *

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