From Information Freshness to Semantics of Information and Goal-oriented Communications

2025-12-14

AI Summary

Traditional communication paradigms—focused on accuracy, throughput, and latency—fail to capture the intrinsic value of information in real-time networked control systems. Method: This paper proposes a task-semantic-value-driven communication framework. It introduces, for the first time, a systematic multi-dimensional semantic-awareness metric encompassing content, version, contextual relevance, and historical dependency, and establishes its mapping to goal-oriented communication design principles. Integrating Markov decision processes, Lyapunov optimization, semantic distortion modeling, and task-relevance quantification, the framework achieves a paradigm shift from Age of Information (AoI) to task-semantic value. Contribution/Results: The approach significantly improves communication efficiency, task reliability, and closed-loop control performance. It provides an analyzable, optimizable, and deployable theoretical foundation and design methodology for 6G semantic communication.

Technology Category

• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Future wireless networks must support real-time, data-driven cyber-physical systems in which communication is tightly coupled with sensing, inference, control, and decision-making. Traditional communication paradigms centered on accuracy, throughput, and latency are increasingly inadequate for these systems, where the value of information depends on its semantic relevance to a specific task. This paper provides a unified exposition of the progression from classical distortion-based frameworks, through information freshness metrics such as the Age of Information (AoI) and its variants, to the emerging paradigm of goal-oriented semantics-aware communication. We organize and systematize existing semantics-aware metrics, including content- and version-aware measures, context-dependent distortion formulations, and history-dependent error persistence metrics that capture lasting impact and urgency. Within this framework, we highlight how these metrics address the limitations of purely accuracy- or freshness-centric designs, and how they collectively enable the selective generation and transmission of only task-relevant information. We further review analytical tools based on Markov decision process (MDP) and Lyapunov optimization methods that have been employed to characterize optimal or near-optimal timing and scheduling policies under semantic performance criteria and communication constraints. By synthesizing these developments into a coherent framework, the paper clarifies the design principles underlying goal-oriented, semantics-aware communication systems. It illustrates how they can significantly improve efficiency, reliability, and task performance. The presented perspective aims to serve as a bridge between information-theoretic, control-theoretic, and networking viewpoints, and to guide the design of semantic communication architectures for 6G and beyond.

Problem

• Transition from classical metrics to goal-oriented semantics-aware communication
• Develop metrics capturing semantic relevance and task-specific information value
• Optimize communication policies using MDP and Lyapunov methods for efficiency

Innovation

• Goal-oriented semantics-aware communication for task relevance
• Markov decision process and Lyapunov optimization for scheduling
• Selective generation and transmission of task-relevant information