Semantic-Functional Communications in Cyber-Physical Systems

TL;DR

This paper introduces a semantic-functional approach for cyber-physical systems that reduces explicit communication by leveraging implicit, semantic-based knowledge, demonstrated through drone swarm simulations to optimize resource use while maintaining system performance.

Contribution

It proposes a novel semantic-functional communication method that minimizes explicit data transmission in CPS, ensuring system functionality and resource efficiency.

Findings

The method effectively reduces radio resource usage.

It maintains system performance in remote sensing tasks.

Demonstrates a fundamental energy-communication-functionality relationship.

Abstract

This paper explores the use of semantic knowledge inherent in the cyber-physical system (CPS) under study in order to minimize the use of explicit communication, which refers to the use of physical radio resources to transmit potentially informative data. It is assumed that the acquired data have a function in the system, usually related to its state estimation, which may trigger control actions. We propose that a semantic-functional approach can leverage the semantic-enabled implicit communication while guaranteeing that the system maintains functionality under the required performance. We illustrate the potential of this proposal through simulations of a swarm of drones jointly performing remote sensing in a given area. Our numerical results demonstrate that the proposed method offers the best design option regarding the ability to accomplish a previously established task -- remote sensing in the addressed case -- while minimising the use of radio resources by controlling the trade-offs that jointly determine the CPS performance and its effectiveness in the use of resources. In this sense, we establish a fundamental relationship between energy, communication, and functionality considering a given end application.