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International Conference on Parallel and Distributed systems (ICPADS)

作者： Long Cheng Haoyang He Yan Gu Qingzhi Liu Zhiming Zhao Fang Fang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing China Information Technology Group Wageningen University and Research Netherlands Research Group of Multi-Scale Networked Systems University of Amsterdam Netherlands

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Scheduling workflows in hybrid cloud environments presents significant challenges due to the inherent complexity of workflows and the dynamic nature of cloud resources. This complexity is further increased when attempting to balance workflow performance with privacy protection. Recent efforts have leveraged deep reinforcement learning (DRL) to address these challenges. However, most of these approaches rely on single-agent models, which can lead to security issues and scalability problems due to their centralized processing. Specifically, the properties of workflows are transferred to the single agent, which risks leaking privacy information. Our paper addresses these issues by introducing MARS, a real-time workflow scheduling method that prioritizes privacy protection in hybrid clouds. MARS leverages multi-agent deep reinforcement learning (MADRL) to optimize the workflow scheduling of cloud virtual machines (VMs). The benefit of our solution is that it relies on the collaborative learning of multi-agents on multiple VMs, which could assign user data to specific cloud servers for privacy protection while sharing training experiences between agents. In our implementation, MARS aims to reduce workflow completion time and operational costs while complying with strict privacy protection guidelines. The experimental results demonstrate that MARS can significantly surpass existing methods, reducing makespan by an average of $53.18 \%$ and costs by $61.98 \%$ compared to basic techniques, and achieving $20.26 \%$ and $25.71 \%$ improvements over the latest advanced methods, respectively.

关键词： Training Cloud computing Privacy Costs Scalability Deep reinforcement learning Dynamic scheduling Real-time systems Complexity theory Protection

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Graph Neural Network Enabled Fluid Antenna systems: A Two-Stage Approach

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IEEE Transactions on Vehicular Technology 2025年

作者： He, Changpeng Lu, Yang Chen, Wei Ai, Bo Wong, Kai-Kit Niyato, Dusit State Key Laboratory of Advanced Rail Autonomous Operation China Beijing Jiaotong University School of Computer Science and Technology Beijing100044 China Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China University College London Department of Electronic and Electrical Engineering LondonWC1E 6BT United Kingdom Yonsei University Yonsei Frontier Laboratory School of Integrated Technology Seoul03722 Korea Republic of Nanyang Technological University College of Computing and Data Science 639798 Singapore

An emerging fluid antenna system (FAS) brings a new dimension, i.e., the antenna positions, to deal with the deep fading, but simultaneously introduces challenges related to the transmit design. This paper proposes an "unsupervised learning to optimize" paradigm to optimize the FAS. Particularly, we formulate the sum-rate and energy efficiency (EE) maximization problems for a multiple-user multiple-input single-output (MU-MISO) FAS and solved by a two-stage graph neural network (GNN) where the first stage and the second stage are for the inference of antenna positions and beamforming vectors, respectively. The outputs of the two stages are jointly input into an unsupervised loss function to train the two-stage GNN. The numerical results demonstrate that the advantages of the FAS for performance improvement and the two-stage GNN for real-time and scalable optimization. Besides, the two stages can function separately. © 1967-2012 IEEE.

关键词： Graph neural networks

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Arbitrage equilibria in active matter systems

arXiv

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arXiv 2024年

作者： Venkatasubramanian, Venkat Sivaram, Abhishek Sanjeevrajan, N. Sankar, Arun Complex Resilient Intelligent Systems Laboratory Department of Chemical Engineering Columbia University New YorkNY10027 United States Department of Chemical and Biochemical Engineering Technical University of Denmark Kongens Lyngby2800 Denmark Department of Materials Engineering Indian Institute of Technology-Madras Chennai600036 India School of Electrical Computer and Energy Engineering Arizona State University TempeAZ United States

The motility-induced phase separation (MIPS) phenomenon in active matter has been of great interest for the past decade or so. A central conceptual puzzle is that this behavior, which is generally characterized as a nonequilibrium phenomenon, can yet be explained using simple equilibrium models of thermodynamics. Here, we address this problem using a new theory, statistical teleodynamics, which is a conceptual synthesis of game theory and statistical mechanics. In this framework, active agents compete in their pursuit of maximum effective utility, and this self-organizing dynamics results in an arbitrage equilibrium in which all agents have the same effective utility. We show that MIPS is an example of arbitrage equilibrium and that it is mathematically equivalent to other phase-separation phenomena in entirely different domains, such as sociology and economics. As examples, we present the behavior of Janus particles in a potential trap and the effect of chemotaxis on MIPS. © 2024, CC BY.

关键词： Phase separation

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Distributed Event-Triggered Bandit Convex Optimization with Time-Varying Constraints

arXiv

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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Mathematics Southeast University Nanjing210096 China The Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms require that each agent broadcasts its decision to its neighbors at each iteration. To better utilize the limited communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

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The Age of Generative AI and AI-Generated Everything

arXiv

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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

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Sensing With Communication Signals: From Information Theory to Signal Processing

arXiv

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arXiv 2025年

作者： Liu, Fan Liu, Ya-Feng Cui, Yuanhao Masouros, Christos Xu, Jie Han, Tony Xiao Buzzi, Stefano Eldar, Yonina C. Jin, Shi National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematicsand Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Guangdong518172 China Huawei Technologies Co. Ltd China Department of Electrical and Information Engineering University of Cassino and Southern Lazio CassinoI-03043 Italy Department of Electronics Information and Bioengineering Politecnico di Milano MilanoI-20133 Italy ParmaI-43124 Italy Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

The Integrated Sensing and Communications (ISAC) paradigm is anticipated to be a cornerstone of the upcoming 6G networks. In order to optimize the use of wireless resources, 6G ISAC systems need to harness the communication data payload signals, which are inherently random, for both sensing and communication (S&C) purposes. This tutorial paper provides a comprehensive technical overview of the fundamental theory and signal processing methodologies for ISAC transmission with random communication signals. We begin by introducing the deterministic-random tradeoff (DRT) between S&C from an information-theoretic perspective, emphasizing the need for specialized signal processing techniques tailored to random ISAC signals. Building on this foundation, we review the core signal models and processing pipelines for communication-centric ISAC systems, and analyze the average squared auto-correlation function (ACF) of random ISAC signals, which serves as a fundamental performance metric for multi-target ranging tasks. Drawing insights from these theoretical results, we outline the design principles for the three key components of communication-centric ISAC systems: modulation schemes, constellation design, and pulse shaping filters. The goal is to either enhance sensing performance without compromising communication efficiency or to establish a scalable tradeoff between the two. We then extend our analysis from a single-antenna ISAC system to its multi-antenna counterpart, discussing recent advancements in multiinput multi-output (MIMO) precoding techniques specifically designed for random ISAC signals. We conclude by highlighting several open challenges and future research directions in the field of sensing with communication signals. Copyright © 2025, The Authors. All rights reserved.

关键词： Signal modulation

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Development of a Near-Field Sensor for Diagnosis of Liver Diseases Using 3D-EM Simulation of Mouse Model

Development of a Near-Field Sensor for Diagnosis of Liver Di...

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Microwaves Antennas and Propagation Conference (MAPCON)

作者： Poulami Samaddar Sunil Gaddam Md Mirazur Rahman Shuvashis Dey Sayan Roy Dipankar Mitra Shivaram P. Arunachalam Department of Medicine Mayo Clinic Division of Gastroenterology and Hepatology Microwave Engineering & Imaging Laboratory Rochester MN USA Department of Electrical and Computer Engineering North Dakota State University Fargo ND USA Division of Energy Matter and Systems School of Science and Engineering University of Missouri-Kansas City Kansas City MO USA Department of Computer Science & Computer Engineering University of Wisconsin-La Crosse La Crosse WI USA

In this work, we studied the response of an antipodal Vivaldi antenna in the presence of different types of mice liver models. The scope of the study was limited to two types of liver diseases, i.e., nonalcoholic steatohepatitis (NASH) and fibrosis. The complex dielectric properties of each liver type were measured using the open-ended coaxial probe dielectric spectroscopy method. A Vivaldi antenna for near-field sensing was designed and then simulated in CST Studio to determine the antenna characteristics. The antenna performance from the simulation matched the reflection coefficients (S11) measurements collected with the fabricated antenna in an anechoic chamber. This verified antenna was used for further measurements of different liver models placed near the antenna. The antenna response, S11 measurements, varied from one tissue type to another, demonstrating the potential of using the Vivaldi antenna as a near-field sensor to differentiate liver disease models from the healthy liver model.

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Demonstrating the Potential of Adaptive LMS Filtering on FPGA-Based Qubit Control Platforms for Improved Qubit Readout in 2D and 3D Quantum Processing Units

Demonstrating the Potential of Adaptive LMS Filtering on FPG...

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Quantum computing and engineering (QCE), IEEE International Conference on

作者： Hans Johnson Nicholas Bornman Taeyoon Kim David Van Zanten Silvia Zorzetti Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A. Fermi National Accelerator Laboratory Superconducting Quantum Materials and Systems (SQMS) Center Batavia IL U.S.A. Department of Physics and Astronomy Center for Applied Physics and Superconducting Technologies (CAPST) Northwestern University Evanston IL U.S.A.

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Advancements in quantum computing underscore the critical need for sophisticated qubit readout techniques to accurately discern quantum states. This abstract presents our research intended for optimizing readout pulse fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the application of the Least Mean Squares (LMS) adaptive filtering algorithm, we explore its integration into the FPGA-based control systems to enhance the accuracy and efficiency of qubit state detection by improving Signal-to-Noise Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3 devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation Control Kit (QICK) open-source platform, we aim to dynamically test and adjust the filtering parameters in real-time to characterize and adapt to the noise profile presented in quantum computing readout signals. Our preliminary results demonstrate the LMS filter's capability to maintain high readout accuracy while efficiently managing FPGA resources. These findings are expected to contribute to developing more reliable and scalable quantum computing architectures, highlighting the pivotal role of adaptive signal processing in quantum technology advancements.

关键词： Three-dimensional displays Accuracy Filtering Qubit Signal processing algorithms Superconducting filters Real-time systems Reliability Field programmable gate arrays Signal to noise ratio

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Codebook Design for Large Reconfigurable Refractive Surface Enabled Holographic MIMO systems

Codebook Design for Large Reconfigurable Refractive Surface ...

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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Yutong Zhang Boya Di Hongliang Zhang Lingyang Song State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

ISBN: (纸本)9781665435413

Holographic multiple-input multiple-output (HMI-MO) has recently motivated its potential use to handle the exponentially increasing data transmission demands by achieving a spatially continuous aperture. With densely-packed metamaterial elements, the reconfigurable refractive surfaces (RRSs) serving as antennas emerge to enable HMIMO. In this paper, we consider a multi-user system where an RRS is employed as the transmit antenna array at the base station (BS). To avoid the high overhead of acquiring perfect channel state information (CSI), a codebook and beam training mechanism is required to develop the beamforming scheme. Given the large physical dimension of the RRS, users are likely to distribute in both the near field and the far field of the BS, making the codebook design more difficult. To address this issue, we design a hybrid near-far field codebook which applies to all users in any location with low overhead. To further reduce the training overhead, each codeword is designed to cover multiple spatial areas, enabling a multi-user beam training mechanism which can be performed for all users simultaneously. Under a general setting including both the near-field and far-field users, simulation results show that the proposed scheme significantly reduces the overhead and achieves a higher sum rate compared to the state-of-the-art codebooks, which performs very close to that of the perfect CSI case.

关键词： Training Simulation Transmitting antennas Metamaterials MIMO Global communication Data communication

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Nonlocal Time-Resolved Terahertz Spectroscopy in the Near Field

Nonlocal Time-Resolved Terahertz Spectroscopy in the Near Fi...

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2022 IEEE Photonics Society Summer Topicals Meeting Series, SUM 2022

作者： Pizzuto, Angela Castro-Camus, Enrique Wilson, William Choi, Wonsik Li, Xiuling Mittleman, Daniel M. Brown University Department of Physics ProvidenceRI02912 United States University of Marburg Department of Physics Marburg Germany Centro de Investigaciones en Optica A. C. Guanajuato Leon37150 Mexico Harvard University Center for Nanoscale Systems CambridgeMA02138 United States University of Illinois at Urbana-Champaign Holonyak Micro and Nanotechnology Laboratory Department of Electrical and Computer Engineering ChampaignIL61820 United States School of Engineering Brown University ProvidenceRI02912 United States University of Texas Department of Electrical and Computer Engineering AustinTX78758 United States

ISBN: (数字)9781665434898

ISBN: (纸本)9781665434898

We describe scattering-type near-field terahertz imaging measurements in which the optical excitation spot is laterally displaced from the probed location. We demonstrate both non-local terahertz emission and non-local optical-pump, terahertz-probe measurements. This family of techniques are powerful new tools for studying anisotropic transport in nanostructures. © 2022 IEEE.

关键词： Terahertz spectroscopy

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