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The Age of Generative AI and AI-Generated Everything

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arXiv 2023年

作者： Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Zhang, Ping Cui, Shuguang Shen, Xuemin Mao, Shiwen Han, Zhu Jamalipour, Abbas Vincent Poor, H. Kim, Dong In School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore School of Automation Guangdong University of Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of School of Electrical and Information Engineering University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative AI (GAI) has emerged as a significant advancement in artificial intelligence, renowned for its language and image generation capabilities. This paper presents "AIGenerated Everything" (AIGX), a concept that extends GAI beyond mere content creation to real-time adaptation and control across diverse technological domains. In networking, AIGX collaborates closely with physical, data link, network, and application layers to enhance real-time network management that responds to various system and service settings as well as application and user requirements. Networks, in return, serve as crucial components in further AIGX capability optimization through the AIGX lifecycle, i.e., data collection, distributed pre-training, and rapid decision-making, thereby establishing a mutually enhancing interplay. Moreover, we offer an in-depth case study focused on power allocation to illustrate the interdependence between AIGX and networking systems. Through this exploration, the article analyzes the significant role of GAI for networking, clarifies the ways networks augment AIGX functionalities, and underscores the virtuous interactive cycle they form. This article paves the way for subsequent future research aimed at fully unlocking the potential of GAI and networks. © 2023, CC BY.

关键词： Decision making

Experimental Demonstration of 16D Voronoi Constellation with Two-Level Coding over 50km Four-Core Fiber

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arXiv 2024年

作者： Zhao, Can Chen, Bin Cai, Jiaqi Liang, Zhiwei Lei, Yi Xiong, Junjie Ma, Lin Hu, Daohui Sun, Lin Shen, Gangxiang School of Computer Science and Information Engineering Hefei University of Technology Hefei China School of Electronic and Information Engineering Soochow University Suzhou China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China

A 16-dimensional Voronoi constellation concatenated with multilevel coding is experimentally demonstrated over a 50 km four-core fiber transmission system. The proposed scheme reduces the required launch power by 6 dB and provides a 17 dB larger operating range than 16QAM with BICM at the outer HD-FEC BER threshold. © 2024, CC BY-NC-SA.

关键词： Digital television

Kinetic granular temperature and its measurement using speckle visibility spectroscopy

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Particuology 2020年第1期18卷 160-169页

作者： Hui Yang Yonghai Zhu Ran Li Qicheng Sun School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Shanghai Key Laboratory of Modern Optical Systems University of Shanghai for Science and TechnologyShanghai 200093China State Key Laboratory of Hydroscience and Engineering Tsinghua UniversityBeijing 100084China

The occurrence of a mesoscopic scale in granular materials leads to a sharp increase in the number of interaction processes at both intra-and inter-scale *** mesoscopic scale is the main source of the complex macroscopic properties of granular *** quantification of mesoscopic disordered movements is often referred to as granular *** this paper,we first introduce the physical meaning of the original granular temperature of a kinetic nature,Tk,and then briefly summarize the advances made over the past few *** research group has focused on Tk measurement using speckle visibility *** principle of this technique and the instruments developed in our research group are briefly *** work shows great promise in the measurement of kinetic granular ***,a summary of granular temperature and some recent developments in speckle visibility spectroscopy measurements are presented.

关键词： Granular flow Mesoscopic process Granular temperature Speckle visibility spectroscopy

Optimal Input Design for Sparse System Identification

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Optimal Input Design for Sparse System Identification

European Control Conference (ECC)

作者： Javad Parsa Cristian R. Rojas Hå kan Hjalmarsson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9783907144077

ISBN: (纸本)9781665497336

In this contribution we consider sparse linear regression problems. It is well known that the mutual coherence, i.e. the maximum correlation of the regressors, is important for the ability of any algorithm to recover the sparsity pattern of an unknown parameter vector from data. A low mutual coherence improves the ability of recovery. In optimal experiment design this requirement may be in conflict with other objectives encoded by the desired Fisher matrix. In this contribution we alleviate this issue by combining optimal input design with a recently proposed approach to achieve low mutual coherence by way of a linear coordinate transformation. The resulting optimization problem is solved using cyclic minimization. Via simulations we demonstrate that the resulting algorithm is able to achieve a Fisher matrix which results in a performance close to the performance if the sparsity would have been known, while at the same time being able to recover the sparsity pattern.

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Cryptanalysis via Machine Learning Based Information Theoretic Metrics

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arXiv 2025年

作者： Kim, Benjamin D. Vasudevan, Vipindev Adat D’Oliveira, Rafael G.L. Cohen, Alejandro Stahlbuhk, Thomas Médard, Muriel Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign ChampaignIL61820 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States School of Mathematical and Statistical Sciences Clemson University ClemsonSC29631 United States Technion Faculty of Electrical Engineering Technion Israel Institute of Technology Haifa32000 Israel MIT Lincoln Laboratory LexingtonMA02421 United States

The fields of machine learning (ML) and cryptanalysis share an interestingly common objective of creating a function, based on a given set of inputs and outputs. However, the approaches and methods in doing so vary vastly between the two fields. In this paper, we explore integrating the knowledge from the ML domain to provide empirical evaluations of cryptosystems. Particularly, we utilize information theoretic metrics to perform ML-based distribution estimation. We propose two novel applications of ML algorithms that can be applied in a known plaintext setting to perform cryptanalysis on any cryptosystem. We use mutual information neural estimation to calculate a cryptosystem’s mutual information leakage, and a binary cross entropy classification to model an indistinguishability under chosen plaintext attack (CPA). These algorithms can be readily applied in an audit setting to evaluate the robustness of a cryptosystem and the results can provide a useful empirical bound. We evaluate the efficacy of our methodologies by empirically analyzing several encryption schemes. Furthermore, we extend the analysis to novel network coding-based cryptosystems and provide other use cases for our algorithms. We show that our classification model correctly identifies the encryption schemes that are not IND-CPA secure, such as DES, RSA, and AES ECB, with high accuracy. It also identifies the faults in CPA-secure cryptosystems with faulty parameters, such a reduced counter version of AES-CTR. We also conclude that with our algorithms, in most cases a smaller-sized neural network using less computing power can identify vulnerabilities in cryptosystems, providing a quick check of the sanity of the cryptosystem and help to decide whether to spend more resources to deploy larger networks that are able to break the cryptosystem. © 2025, CC BY-NC-ND.

关键词： Information leakage

A Multi-Layer Software Architecture for Aerial Cognitive Multi-Robot systems in Power Line Inspection Tasks

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arXiv 2023年

作者： Silano, Giuseppe Bednar, Jan Nascimento, Tiago Capitan, Jesus Saska, Martin Ollero, Anibal The Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Department of Computer Systems Universidade Federal da Paraiba Brazil The GRVC Robotics Laboratory University of Seville Spain

This paper presents a multi-layer software architecture to perform cooperative missions with a fleet of quad-rotors providing support in electrical power line inspection operations. The proposed software framework guarantees the compliance with safety requirements between drones and human workers while ensuring that the mission is carried out successfully. Besides, cognitive capabilities are integrated in the multi-vehicle system in order to reply to unforeseen events and external disturbances. The feasibility and effectiveness of the proposed architecture are demonstrated by means of realistic simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Software architecture

Control of Reaction-Diffusion Processes Under Communication Delays

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Control of Reaction-Diffusion Processes Under Communication ...

European Control Conference (ECC)

作者： Luca Ballotta Juncal Arbelaiz Vijay Gupta Luca Schenato Mihailo R. Jovanović Delft Center for Systems and Control Delft University of Technology Delft The Netherlands Department of Mechanical and Aerospace Engineering Center for Statistics and Machine Learning Princeton University Princeton NJ USA Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Department of Information Engineering University of Padova Padova Italy Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this paper we investigate the design of optimal spatially distributed controllers for a linear and spatially invariant reaction-diffusion process over the real line. The controller receives state measurements from different spatial locations with non-negligible delays. In this set-up and for the class of proportional spatially invariant state feedback controllers, the optimal control synthesis problem is equivalent to a feedback gain optimization for a spatially distributed delay system. We show that the spatial locality of optimal feedback gains is affected not only by diffusion and reaction coefficients, but also by the parameter representing communication time-delay that causes a sharp flattening of the control gains. In the expensive control regime, the optimal controller is solved analytically, yielding some practical design guidelines.

关键词： State feedback Delay systems Design methodology Process control Optimal control Europe Delays

Large Models for Aerial Edges: An Edge-Cloud Model Evolution and Communication Paradigm

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arXiv 2024年

作者： Zhang, Shuhang Liu, Qingyu Chen, Ke Di, Boya Zhang, Hongliang Yang, Wenhan Niyato, Dusit Han, Zhu Poor, H. Vincent The Pengcheng Laboratory Shenzhen518055 China The School of Electronic and Computer Engineering Peking University Shenzhen518055 China The Department of Electronics Peking University Beijing100871 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore The Department of Electrical and Computer Engineering The University of Houston HoustonTX77004 United States The Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of The Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

The future sixth-generation (6G) of wireless networks is expected to surpass its predecessors by offering ubiquitous coverage through integrated air-ground facility deployments in both communication and computing domains. In this network, aerial facilities, such as unmanned aerial vehicles (UAVs), conduct artificial intelligence (AI) computations based on multi-modal data to support diverse applications including surveillance and environment construction. However, these multi-domain inference and content generation tasks require large AI models, demanding powerful computing capabilities and finely tuned inference models trained on rich datasets, thus posing significant challenges for UAVs. To tackle this problem, we propose an integrated air-ground edge-cloud model evolution framework, where UAVs serve as edge nodes for data collection and small model computation. Through wireless channels, UAVs collaborate with ground cloud servers, providing large model computation and model updating for edge UAVs. With limited wireless communication bandwidth, the proposed framework faces the challenge of information exchange scheduling between the edge UAVs and the cloud server. To tackle this, we present joint task allocation, transmission resource allocation, transmission data quantization design, and edge model update design to enhance the inference accuracy of the integrated air-ground edge-cloud model evolution framework by mean average precision (mAP) maximization. A closed-form lower bound on the mAP of the proposed framework is derived based on the mAP of the edge model and mAP of the cloud model, and the solution to the mAP maximization problem is optimized accordingly. Simulations, based on results from vision-based classification experiments, consistently demonstrate that the mAP of the proposed integrated air-ground edge-cloud model evolution framework outperforms both a centralized cloud model framework and a distributed edge model framework across various communica

关键词： Bandwidth

Hidden Convexity-Based Distributed Operation of Integrated Electricity-Gas systems

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arXiv 2024年

作者： Liu, Rong-Peng Song, Yue Liu, Junhong Wang, Xiaozhe Guo, Jinpeng Hou, Yunhe The Department of Electrical and Computer Engineering McGill University MontrealQCH3A 0E9 Canada The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The Department of Energy and Electrical Engineering Ho-Hai University Jiangsu Nanjing China

This letter proposes a hidden convexity-based method to address distributed optimal energy flow (OEF) problems for transmission-level integrated electricity-gas systems. First, we develop a node-wise decoupling method to decompose an OEF problem into multiple OEF subproblems. Then, we propose a hidden convexity-based method to equivalently reformulate nonconvex OEF subproblems as semi-definite programs. This method differs from any approximation and convexification methods that may incur infeasible solutions. Since all OEF subproblems are originally convex or equivalently convexified, we adopt an ADMM to solve the hidden convexity-based distributed OEF problem with convergence analysis. Test results validate the effectiveness of the proposed method, especially in handling a large number of agents. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadratic programming