A fault-tolerant computing method for Xdraw parallel algorithm

Viewshed analysis has widely been used in various spatial analysis applications. But the expense of viewshed computation remains high both in time and space complexity for large-scale terrain data, so parallel computing technique has been introduced to improve their performance. However, the failure in such a parallel computing system with a lot of computing nodes or processors may lead to an increase in execution time and cost of running viewshed computation. Highly fault-tolerant parallel computing will greatly enhance the reliability of the algorithm without losing its performance. In this article, we present a fault-tolerant computing framework for parallel viewshed computation in a parallel computing system using redundancy computing strategy. Two schedule strategies, layer and axis direction schedule, are adopted, respectively, as primary process and slave process to check whether or not there are errors to occur during the computation. A rollback and re-computation process is presented to correct these errors, while an error is found by comparing the results of the primary process and its slave process. The fault-tolerant algorithm in this article is implemented using process-level and thread-level parallelization. Our method can make full use of multiple processors providing by parallel computing environment without losing the computation efficiency of the algorithm. To illustrate the usefulness of our approach, several experiments are executed by using Xdraw viewshed algorithm. The results demonstrate that our approach achieves the 14.91 of speedup ratio with 16 processes and the 99.4% of average precision rate in comparison with simple checkpoint Xdraw algorithm.