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Goal-Oriented Integration of Sensing, Communication, Computing, and Control for Mission-Critical Internet-of-Things

Jie Cao, Ernest Kurniawan, Amnart Boonkajay, Sumei Sun, Petar Popovski, Xu Zhu

TL;DR

The paper tackles the challenge of building mission-critical 6G MC-IoT by integrating sensing, communication, computing, and control (S3C) through a goal-oriented framework. It proposes GIS3C, an end-to-end architecture that uses goal-oriented communication to bridge subsystems and reduce unnecessary data while focusing on task completion effectiveness. The contributions include environment-aware sensing, semantic communication, context-aware control, and situation-aware computing, plus a unified system-level metric for co-design, namely task completion effectiveness and cost, with $J_{sys}=\chi(J_{sa},J_{cm},J_{cn},J_{cp})$ and $C_{sys}=c_{sa}(C_{sa})+c_{cm}(C_{cm})+c_{cn}(C_{cn})+C_{cp}$. A use case on load frequency control demonstrates improved task completion effectiveness and reduced costs, and the paper discusses open challenges and directions for real-time green SemCom, heterogeneous network coexistence, and semantic-native communication.

Abstract

Driven by the development goal of network paradigm and demand for various functions in the sixth-generation (6G) mission-critical Internet-of-Things (MC-IoT), we foresee a goal-oriented integration of sensing, communication, computing, and control (GIS3C) in this paper. We first provide an overview of the tasks, requirements, and challenges of MC-IoT. Then we introduce an end-to-end GIS3C architecture, in which goal-oriented communication is leveraged to bridge and empower sensing, communication, control, and computing functionalities. By revealing the interplay among multiple subsystems in terms of key performance indicators and parameters, this paper introduces unified metrics, i.e., task completion effectiveness and cost, to facilitate S3C co-design in MC-IoT. The preliminary results demonstrate the benefits of GIS3C in improving task completion effectiveness while reducing costs. We also identify and highlight the gaps and challenges in applying GIS3C in the future 6G networks.

Goal-Oriented Integration of Sensing, Communication, Computing, and Control for Mission-Critical Internet-of-Things

TL;DR

The paper tackles the challenge of building mission-critical 6G MC-IoT by integrating sensing, communication, computing, and control (S3C) through a goal-oriented framework. It proposes GIS3C, an end-to-end architecture that uses goal-oriented communication to bridge subsystems and reduce unnecessary data while focusing on task completion effectiveness. The contributions include environment-aware sensing, semantic communication, context-aware control, and situation-aware computing, plus a unified system-level metric for co-design, namely task completion effectiveness and cost, with and . A use case on load frequency control demonstrates improved task completion effectiveness and reduced costs, and the paper discusses open challenges and directions for real-time green SemCom, heterogeneous network coexistence, and semantic-native communication.

Abstract

Driven by the development goal of network paradigm and demand for various functions in the sixth-generation (6G) mission-critical Internet-of-Things (MC-IoT), we foresee a goal-oriented integration of sensing, communication, computing, and control (GIS3C) in this paper. We first provide an overview of the tasks, requirements, and challenges of MC-IoT. Then we introduce an end-to-end GIS3C architecture, in which goal-oriented communication is leveraged to bridge and empower sensing, communication, control, and computing functionalities. By revealing the interplay among multiple subsystems in terms of key performance indicators and parameters, this paper introduces unified metrics, i.e., task completion effectiveness and cost, to facilitate S3C co-design in MC-IoT. The preliminary results demonstrate the benefits of GIS3C in improving task completion effectiveness while reducing costs. We also identify and highlight the gaps and challenges in applying GIS3C in the future 6G networks.
Paper Structure (24 sections, 5 figures, 1 table)

This paper contains 24 sections, 5 figures, 1 table.

Table of Contents

  1. Introduction
  2. Tasks and Challenges of S3C for 6G MC-IoT
  3. Tasks and Requirements of 6G MC-IoT
  4. Challenges of Realizing S3C Co-Design in 6G MC-IoT
  5. E2E GIS3C for 6G MC-IoT
  6. GIS3C in 6G MC-IoT
  7. Environment-aware Sensing
  8. Time-Based Metric
  9. Error-Based Metric
  10. Goal-Based Metric
  11. Semantic Communication
  12. Semantic Extraction and Filtering
  13. Semantic Encoding
  14. Context-Aware Control
  15. Modeling
  16. ...and 9 more sections

Figures (5)

  • Figure 1: An Example of 6G MC-IoT: Smart Factory with Sensing, Communication, Control and Computing Functionalities.
  • Figure 2: E2E GIS3C Architecture in 6G MC-IoT.
  • Figure 3: Interplay Among Multiple Subsystems in GIS3C-assisted 6G MC-IoT.
  • Figure 4: Comparison Between Bit-oriented Independent Design (the upper part) and Goal-oriented S3C Co-Design (the bottom part).
  • Figure 5: Performance Comparison Among Different Design Methods in Terms of Task Completion Effectiveness and Costs.