"X of Information'' Continuum: A Survey on AI-Driven Multi-dimensional Metrics for Next-Generation Networked Systems

TL;DR

This survey introduces a four-dimensional framework for evaluating information quality in next-generation networks, emphasizing AI-driven adaptive metrics to meet diverse application needs.

Contribution

It presents the first comprehensive taxonomy of multi-dimensional information metrics and analyzes their interdependencies and AI-based optimization in modern networks.

Findings

Interdependencies among temporal, quality, reliability, and network dimensions are increasing.

AI techniques enable adaptive optimization of information quality objectives.

Application-specific insights demonstrate the framework's versatility across domains.

Abstract

The development of next-generation networking systems has inherently shifted from throughput-based paradigms towards intelligent, information-aware designs that emphasize the quality, relevance, and utility of transmitted information, rather than sheer data volume. While classical network metrics, such as latency and packet loss, remain significant, they are insufficient to quantify the nuanced information quality requirements of modern intelligent applications, including autonomous vehicles, digital twins, and metaverse environments. In this survey, we present the first comprehensive study of the ``X of Information'' continuum by introducing a systematic four-dimensional taxonomic framework that structures information metrics along temporal, quality/utility, reliability/robustness, and network/communication dimensions. We uncover the increasing interdependencies among these dimensions, whereby temporal freshness triggers quality evaluation, which in turn helps with reliability appraisal, ultimately enabling effective network delivery. Our analysis reveals that artificial intelligence technologies, such as deep reinforcement learning, multi-agent systems, and neural optimization models, enable adaptive, context-aware optimization of competing information quality objectives. In our extensive study of six critical application domains, covering autonomous transportation, industrial IoT, healthcare digital twins, UAV communications, LLM ecosystems, and metaverse settings, we illustrate the revolutionary promise of multi-dimensional information metrics for meeting diverse operational needs. Our survey identifies prominent implementation challenges, including ...