Real-Time Transmission of Secured PLCs Sensing Data
Bunrong Leang, Rockwon Kim, Kwan‐Hee Yoo · 2018
The proposed method aims to facilitate streaming and processing of sensing data in manufacturing industry. In our implementation, Apache Kafka cluster is carried out as real-time data transmission from PLCs to a database server. To do it, multiple tasks are performed simultaneously in Apache Kafka. Moreover, the number of Kafka producers and Kafka consumers are scaled up to make data transmission more efficiency with tremendous PLCs. And public-key cryptography is performed to encrypt and decrypt the data between the producer and consumer. Especially, Spark cluster for real-time data processing and analysis is used as the consumer processing engine. Through the proposed method, we empowered to accelerate the high performance of real-time data streaming and processing by integrating of Kafka and Spark including the public-key cryptography.