SCADA-Based Message Generator for Multi-Vendor Smart Grids: Distributed Integration and Verification of TASE.2
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Recent developments in massive machine-type communication (mMTC) scenarios have given rise to never-seen requirements, which triggered the Industry 4.0 revolution. The new scenarios bring even more pressure to comply with the reliability and communication security and enable flawless functionality of the critical infrastructure, e.g., smart grid infrastructure. We discuss typical network grid architecture, communication strategies, and methods for building scalable and high-speed data processing and storage platform. This paper focuses on the data transmissions using the sets of standards IEC 60870-6 (ICCP/TASE.2). The main goal is to introduce the TASE.2 traffic generator and the data collection back-end with the implemented load balancing functionality to understand the limits of current protocols used in the smart grids. To this end, the assessment framework enabling generating and collecting TASE.2 communication with long-term data storage providing high availability and load balancing capabilities was developed. The designed proof-of-concept supports complete cryptographic security and allows users to perform the complex testing and verification of the TASE.2 network nodes configuration. Implemented components were tested in a cloud-based Microsoft Azure environment in four geographically separated locations. The findings from the testing indicate the high performance and scalability of the proposed platform, allowing the proposed generator to be also used for high-speed load testing purposes. The load-balancing performance shows the CPU usage of the load-balancer below 15% while processing 5000 messages per second. This makes it possible to achieve up to a 7-fold improvement of performance resulting in processing up to 35,000 messages per second.
KeywordsIEC 60870-6, TASE.2, smart grid, traffic generator, Apache JMeter, Apache Kafka, SCADA, MongoDB, Microsoft Azure
Document typePeer reviewed
Document versionFinal PDF
SourceSENSORS. 2021, vol. 21, issue 20, p. 1-20.
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