Directed Acyclic Graph-Based Optimization of Apache Flink to Process Streaming Big Data of Industry 4.0

This paper presents a new approach to improve the management of workflow for DAG processing in Apache Flink for further optimization of stream big data. The proposed optimization techniques focus on enhancing the performance metrics of Average Task Execution Time, CPU & Memory Utilization, and System Throughput. Reported experiments demonstrate that the optimized Apache Flink significantly outperforms the baseline version, making it a promising solution for real-time big data analytics.