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Entropy
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Foundations of Goal-Oriented Semantic Communication in Intelligent Networks
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Foundations of Goal-Oriented Semantic Communication in Intelligent Networks

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (31 March 2024) | Viewed by 2441

Special Issue Editors

Dr. Photios A. Stavrou

E-Mail Website
Guest Editor
Communication Systems Department, EURECOM, 06410 Biot, France
Interests: information theory; stochastic control; optimization; game theory; semantic goal-oriented communications
Dr. Giulia Cervia

E-Mail Website
Guest Editor
IMT Nord Europe, Institut Mines-Télécom, Univ. Lille, CERI SN - Centre for Digital Systems, F-59000 Lille, France
Interests: information theory; privacy; semantic communication; compression; probability theory
Dr. Serkan Sarıtaş

E-Mail Website
Guest Editor
Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara 06800, Turkey
Interests: game theory; networked control; communication theory; information theory; information security
Dr. Nikolaos Pappas

E-Mail Website
Guest Editor
Department of Computer and Information Science, Linköping University, 58183 Linköping, Sweden
Interests: age of information; goal-oriented semantics-aware communications; performance analysis and stochastic modeling; communication networks

Special Issue Information

Dear Colleagues,

With continued momentum around the deployment of 5G technologies, research communities in communications, control, and networking have already started looking at the requirements and technology components for the next generation of intelligent networks.  In the envisioned beyond-5G era, it is expected that data demands will continue to rapidly increase, leading to a world where everything is to be sensed and endowed with connected intelligence, fueled by the interconnection of myriad autonomous devices (robots, vehicles, drones, etc.). Consider, for example, data aggregated by an autonomous vehicle starting from at least 700 Mbit/s, whereas industrial Internet of Things deployments may deal with the transmission of 1 Gbit/s of aggregated data for remote actuation and digital twins. Gradually, wireless connectivity will become a true commodity that will serve a plethora of arising societal-scale applications such as consumer robotics, environmental monitoring and healthcare.

On the other hand, wireless connectivity is traditionally seen as a non-transparent data pipe carrying information whose importance, impact and usefulness for achieving a specific task have been deliberately set aside. This communication paradigm, although suitable for classical communication, is inefficient and inadequate to support the staggering amount of data and the timely communication needs of the next generation of intelligent networks. Therefore, it is vital to elevate wireless networks to generate, process and attempt to convey excessive real-time data using a new communication paradigm that accounts for the semantic goal-oriented importance of information that is generated, processed, transmitted, and utilized. 

In this Special Issue, we will consolidate the latest ideas and findings on the applications and theory of semantics and goal-oriented communications for networked intelligent systems.

Dr. Photios A. Stavrou
Dr. Giulia Cervia
Dr. Serkan Sarıtaş
Dr. Nikolaos Pappas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • goal-oriented compression
  • information bottleneck methods
  • goal-oriented joint source channel coding
  • information theoretic coordination
  • networked control systems
  • age of information
  • value of information
  • neuromorphic computing
  • semantic entropy
  • knowledge graphs
  • natural language processing
  • distributed function computation
  • machine learning
  • information theory
  • security and privacy aspects
  • game-theoretical models

Published Papers (2 papers)

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Research

30 pages, 662 KiB  
Article
Structural Properties of the Wyner–Ziv Rate Distortion Function: Applications for Multivariate Gaussian Sources
by Michail Gkagkos and Charalambos D. Charalambous
Entropy 2024, 26(4), 306; https://doi.org/10.3390/e26040306 - 29 Mar 2024
Viewed by 437
Abstract
The main focus of this paper is the derivation of the structural properties of the test channels of Wyner’s operational information rate distortion function (RDF), R¯(ΔX), for arbitrary abstract sources and, subsequently, the derivation of additional properties [...] Read more.
The main focus of this paper is the derivation of the structural properties of the test channels of Wyner’s operational information rate distortion function (RDF), R¯(ΔX), for arbitrary abstract sources and, subsequently, the derivation of additional properties for a tuple of multivariate correlated, jointly independent, and identically distributed Gaussian random variables, {Xt,Yt}t=1∞, Xt:Ω→Rnx, Yt:Ω→Rny, with average mean-square error at the decoder and the side information, {Yt}t=1∞, available only at the decoder. For the tuple of multivariate correlated Gaussian sources, we construct optimal test channel realizations which achieve the informational RDF, R¯(ΔX)=▵infM(ΔX)I(X;Z|Y), where M(ΔX) is the set of auxiliary RVs Z such that PZ|X,Y=PZ|X, X^=f(Y,Z), and E{||X−X^||2}≤ΔX. We show the following fundamental structural properties: (1) Optimal test channel realizations that achieve the RDF and satisfy conditional independence, PX|X^,Y,Z=PX|X^,Y=PX|X^,EX|X^,Y,Z=EX|X^=X^. (2) Similarly, for the conditional RDF, RX|Y(ΔX), when the side information is available to both the encoder and the decoder, we show the equality R¯(ΔX)=RX|Y(ΔX). (3) We derive the water-filling solution for RX|Y(ΔX). Full article
(This article belongs to the Special Issue Foundations of Goal-Oriented Semantic Communication in Intelligent Networks)
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22 pages, 1071 KiB  
Article
The Role of Gossiping in Information Dissemination over a Network of Agents
by Melih Bastopcu, Seyed Rasoul Etesami and Tamer Başar
Entropy 2024, 26(1), 9; https://doi.org/10.3390/e26010009 - 21 Dec 2023
Cited by 1 | Viewed by 880
Abstract
We consider information dissemination over a network of gossiping agents. In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and n receiver nodes want to follow the information at the source as accurately as [...] Read more.
We consider information dissemination over a network of gossiping agents. In this model, a source keeps the most up-to-date information about a time-varying binary state of the world, and n receiver nodes want to follow the information at the source as accurately as possible. When the information at the source changes, the source first sends updates to a subset of m≤n nodes. Then, the nodes share their local information during the gossiping period, to disseminate the information further. The nodes then estimate the information at the source, using the majority rule at the end of the gossiping period. To analyze the information dissemination, we introduce a new error metric to find the average percentage of nodes that can accurately obtain the most up-to-date information at the source. We characterize the equations necessary to obtain the steady-state distribution for the average error and then analyze the system behavior under both high and low gossip rates. We develop an adaptive policy that the source can use to determine its current transmission capacity m based on its past transmission rates and the accuracy of the information at the nodes. Finally, we implement a clustered gossiping network model, to further improve the information dissemination. Full article
(This article belongs to the Special Issue Foundations of Goal-Oriented Semantic Communication in Intelligent Networks)
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