H2020Индивидуална стипендия2015–2017

CYBERNETS · Cybernetic Communication Networks: Fundamental Limits and Engineering Challenges

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2015-06-01 → 2017-05-31
Финансиране от ЕС: 185 076 €
Участници: 1
Схема: MSCA-IF-EF-RI

Линиите свързват координатора с партньорите.

Накратко на български

Кибернетичните комуникационни мрежи, използвани при спасителни операции или в медицината, се анализират за по-ефективен трансфер на данни и защита от атаки. Това помага за повишаване на надеждността и устойчивостта на безжичните системи при повреди или злонамерено поведение.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Cybernetic Communication Networks: Fundamental Limits and Engineering Challenges

This Reintegration Panel proposal, CYBERNETS, focuses on the study of Cybernetic Communication Networks (CCN). CCNs are wireless networks that are context-aware, possess learning capabilities and artificial intelligence to guarantee reliability, efficiency and resilience to changes, failures or attacks via autonomous, self-configuring and self-healing individual and network behavior. Typical examples of CCNs are critical communication systems, e.g., law enforcement, disaster relief, body-area, medical instruments, space, and indoor/outdoor commercial applications. Within this context the objectives of this project are: (1)To determine the fundamental limits of data transmission rates in fully distributed CCNs in which feedback is implemented. In particular, fundamental channels in which more than two transmitter-receiver pairs interact subject to mutual interference. (2) To identify and explore alternatives for allowing transmitter-receiver pairs to learn equilibrium strategies in the decentralized interference channel with and without feedback. (3) To study the impact of knowledge on scenarios derived from the malicious behavior of one of the receivers of the interference channel with feedback. That is, to identify the scenarios in which malicious behavior of one of the receivers of the interference channel can be combated by providing more knowledge about the network state.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

This Reintegration Panel proposal, CYBERNETS, focuses on the study of Cybernetic Communication Networks (CCN). CCNs are wireless networks that are context-aware, possess learning capabilities and artificial intelligence to guarantee reliability, efficiency and resilience to changes, failures or attacks via autonomous, self-configuring and self-healing individual and network behavior. Typical examples of CCNs are beyond-5G cellular systems and critical communication systems, e.g., law enforcement, disaster relief, body- area, medical instruments, space, and indoor/outdoor commercial applications. A practical implementation of a CCN requires extending classical communication systems to embrace the dynamics of fully decentralized systems whose components might exhibit either cooperative, non-cooperative or even malicious behaviors to improve individual and/or global performance. In this context, CYBERNETS aims to develop a relevant understanding of the interactions between information theory, game theory and signal processing to tackle two particular problems from both theoretical and practical perspectives: (I) use of feedback and (II) behavior adaptation in fully decentralized CCNs. In the former, the main objectives are: (i) to determine the fundamental limits of data transmission rates in CCNs with feedback; and (ii) to develop and test in real-systems, transmit-receive configurations to provide a proof-of-concept of feedback in CCNs. For the achievement of these practical objectives, CYBERNETS relies on the world-class testbed infrastructure of INRIA at the CITI Lab for fully closing the gap between theoretical analysis and real-system implementation. In the latter, the main objectives are: (i) to identify and explore alternatives for allowing transmitter-receiver pairs to learn equilibrium strategies in CCNs with and without feedback; (ii) to study the impact of network-state knowledge on scenarios derived from the malicious behavior of network components.

Оригинален текст от CORDIS (на английски).

Участници

INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE · Le Chesnay CedexКоординаторФранция