A Goal-Oriented Networking Approach for Intelligent IoT Service Deployment

2026-05-27

AI Summary

This work proposes a task-oriented end-to-end communication framework tailored to the stringent requirements of 6G intelligent Internet of Things (IoT), where energy efficiency, latency, and task accuracy must be jointly optimized. The framework uniquely integrates application-layer key performance indicators (KPIs) into network resource scheduling through a multi-objective optimization model that systematically balances energy consumption, latency, and task accuracy. By leveraging AI-driven data preprocessing and task relevance filtering mechanisms, it enables on-demand allocation of communication resources aligned with actual task needs. Simulation results demonstrate that the proposed approach significantly enhances network energy efficiency and latency performance while effectively preserving task accuracy, thereby validating the feasibility and advantages of task-oriented communication paradigms in 6G networks.

Abstract

The first 6G standardization efforts are about to start, shaping the new generation of mobile networks. The IMT-2030 extends the IMT-2020 by expanding its usage scenarios to Immersive, Massive, and Hyper-Reliable and Low-Latency Communications. It also introduces novel scenarios by integrating Artificial Intelligence and Sensing with Communication and supporting Ubiquitous Connectivity. Compared to the previous generation, 6G is expected to improve not only throughput and latency, but also coverage and energy efficiency. A paradigm called Goal-Oriented (GO) communications has recently emerged as a promising solution to improve network efficiency. It relies on the fact that the goal of the communication network is to achieve a specific task with a defined accuracy, rather than creating perfect data delivery. Intelligent devices can pre-process data to send only what is relevant to achieve the task, thus saving precious network resources and energy. Recent works demonstrate that incorporating service- and application-level KPIs in the network allows to achieve higher communication efficiency for devices, but the consequence of using such techniques on the network itself has not yet been explored. This paper proposes a practical end-to-end framework to assess energy consumption, latency, and goal accuracy KPIs, which includes a Multi-Objective optimization model to evaluate the trade-offs between the multiple KPIs relevant to GO networking. We demonstrate, through simulation, that the network can benefit from the application of the GO paradigm, indicating its potential in future network architectures.

Problem

• Goal-Oriented Networking
• 6G
• Intelligent IoT
• KPI Trade-offs
• Energy Efficiency

Innovation

• Goal-Oriented Networking
• Multi-Objective Optimization
• Intelligent IoT
• 6G
• KPI-aware Communication