Fuzzy logic-based fault detection in containerized data centers using digital twins

Abstract

Containerized data centers (CDCs) have experienced rapid growth in recent years, owing to their modular and scalable nature. However, ensuring reliability and early fault detection in these complex systems is critical. This paper presents a novel Fuzzy Logic-based Fault Detection (FLFD) framework for CDCs using Digital Twins (DTs). The proposed approach employs DTs to create accurate virtual representations of the CDCs, which enable real-time monitoring and analysis of the physical systems. This paper focuses on three main aspects: (1) the development of a comprehensive DT model for CDCs, (2) the design and implementation of a FLFD algorithm, and (3) the validation of the proposed approach through extensive simulations and real-world case studies. The FLFD algorithm leverages fuzzy logic principles to identify and localize faults in the system, thereby enhancing the overall fault detection accuracy and reducing false alarms. Results demonstrate the effectiveness of the proposed framework, with significant improvements in fault detection performance and system reliability. The FLFD approach offers a promising solution for proactive maintenance and management in containerized data centers, paving the way for more efficient and resilient operations.