Research on Distributed Calculation of Flight Parameters Based on Hadoop. Issue 1 (1st September 2022)

• Record Type: Journal Article
• Authors: Li, Pengcheng; Chen, Haidong; Li, Shipeng; Yan, Tinggui; Qian, Hang
• Is Part Of: Journal of physics. Volume 2337:Issue 1(2022)
• Publication Date: 2022-09-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2337/1/012013
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: With the improvement of launch vehicle technology and the increase of launch missions, under the intensive launch tasks, the contradiction between the large-scale calculation demand of flight parameters of launch vehicle and the traditional standalone calculation mode is increasingly prominent, which is mainly reflected in the slow calculation speed, low processing efficiency, limited bandwidth bottleneck, and single point fault. Big data processing architecture Hadoop's distributed computing framework MapReduce, running in low cost cluster, is innovative applied in the large-scale calculation of launch vehicle's flight parameters, relying on its distributed storage, coordination and load balancing mechanism. The method effectively improves computing efficiency, breakthroughs performance bottleneck and avoids single point failure. Compared with the traditional standalone deployment and pseudo-distributed cluster deployment based on Hadoop, the fully distributed cluster deployment based on Hadoop is the optimal deployment for calculating flight parameters. The results show that the parallel calculation of flight parameters based on Hadoop could save time used by 51% with the consistency of calculation results, which is the same as the standalone deployment.