Research on Data Producing Services across Compute Engines
Authors:Qi Wang, Ruiyun Wang, Ming Lei
China Justice Big Data Institute Co., LTD., Beijing, China
China Electronics Technology Group Corporation 15, Beijing, China
Information:Advanced Journal of Engineering, October 2022 Vol.1, No.4, pp 57-68
Abstract:Currently, data production services are facing the following challenges: achieving cross-computing engine scheduling, automated accurate labeling, and on-demand task scheduling. In this paper, cross-computing engine scheduling technology for business data production, domain-oriented business data automatic labeling technology and business data production visualization process scheduling technology are investigated, while high concurrency-related technical solutions are studied to improve the service processing performance. At the end of the paper, technical risk assessment analysis is also given in four aspects, including computing resource scheduling, labeling reliability, process scheduling optimization and thread safety.
Keywords:Cross-computing engine scheduling; Automatic data labeling; Data production task flow scheduling; Hi
Cite This Article:Wang Q., Wang R.Y. and Lei M. (2022). Research on Data Producing Services across Compute Engines. Advanced Journal of Engineering, October 2022 Vol.1, No.4, pp 57-68.