A Systematic Review of Real-Time Session Control Using Temporal Logic Enforcement: Methods, Architectures, and Future Research Directions

Abstract

Real-time session control is essential in modern distributed systems, especially in areas such as cybersecurity, IoT networks, cloud computing, and cyber-physical systems. Ensuring that system behavior adheres to predefined specifications has led to the use of temporal logic enforcement mechanisms. Formal models such as Linear Temporal Logic (LTL), Signal Temporal Logic (STL), and Metric Temporal Logic (MTL) provide frameworks for expressing time-dependent constraints. When integrated with runtime monitoring, these approaches enable continuous validation and correction of system behavior during execution. This paper presents a systematic review of studies published between 2018 and 2023, focusing on methods, architectures, and emerging trends in real-time session control. It highlights key approaches including rule-based enforcement, automata-based monitoring, and learning-assisted systems. Recent advancements integrate temporal logic with neural networks and graph-based models to improve adaptability and scalability. The review also examines architectures such as decentralized monitoring, edge-based enforcement, and hybrid cloud-edge systems designed to minimize latency. Despite progress, challenges remain in scalability, computational overhead, and expressiveness, indicating the need for more efficient and intelligent real-time enforcement solutions.