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SSRN 2022年

作者： Proietti Mattia, Gabriele Beraldi, Roberto Department of Computer Control and Management Engineering"Antonio Ruberti" Sapienza University of Rome Via Ariosto 25 Rome00185 Italy

In Edge and Fog Computing environments, it is usual to design and test distributed algorithms that implement scheduling and load balancing solutions. The operation paradigm that usually fits the context requires the users to make calls to the closer node for executing a task, and since the service must be distributed among a set of nodes, the serverless paradigm with the FaaS (Function-as-a-Service) is the most promising strategy to use. In light of these preconditions, we designed and implemented a framework called P2PFaaS. The framework, built upon Docker containers, allows the implementation of fully decentralised scheduling or load balancing algorithms among a set of nodes. By relying on three basic services, such as the scheduling service, the discovery service, and the learner service, the framework allows the implementation of any kind of scheduling solution, even if based on Reinforcement Learning. Finally, the framework provides a ready-to-go solution that can be installed and has been tested both on x86 servers and ARM-based edge nodes (like, for example, the Raspberry Pi). © 2022, The Authors. All rights reserved.

关键词： Scheduling

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SHIELD: Assessing Security-by-Design in Federated Data Spaces Using Attack Graphs 25

SHIELD: Assessing Security-by-Design in Federated Data Space...

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40th Annual ACM Symposium on Applied Computing, SAC 2025

作者： Palma, Alessandro Papadakis, Nikolaos Bouloukakis, Georgios Garcia-Alfaro, Joaquin Sospetti, Mattia Magoutis, Kostas Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy Samovar Télécom SudParis Institut Polytechnique de Paris Palaiseau91120 France GrottiniLab S.r.L. Porto Recanati Macerata Italy Computer Science Department University of Crete Greece Crete Greece

ISBN: (纸本)9798400706295

Federated data spaces allow organizations to share and control their own data across various domains, but their exposure to cyber attacks has increased due to a surge in newly discovered vulnerabilities. Existing solutions to secure them focus on messaging protocol protection (e.g., using cryptographic means), but this is not sufficient. Attackers may exploit additional vulnerabilities to cause significant issues (e.g., disrupting the availability of services). To this end, we propose SHIELD, a security-by-design approach for federated data spaces, which leverages attack graphs and trust computation to mitigate the risks of cyber attacks. Mitigation is accomplished by proactively assessing the data spaces' weaknesses and implementing security messaging measures to prevent detrimental attacks. A prototype implementation of SHIELD using publish/subscribe as a messaging mechanism is experimentally evaluated over a real architecture in a V2X (Vehicle-to-Everything) scenario. Copyright © 2025 held by the owner/author(s).

关键词： Trusted computing

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PDAVIS: Bio-inspired Polarization Event Camera

PDAVIS: Bio-inspired Polarization Event Camera

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Haessig, Germain Joubert, Damien Haque, Justin Milde, Moritz B. Delbruck, Tobi Gruev, Viktor Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria University of Zurich Institute of Neuroinformatics ETH Zurich Switzerland Western Sydney University International Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL United States

ISBN: (纸本)9798350302493

The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired frame-based cameras lack the high dynamic range and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12ms and dynamic range to ~72dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with submillisecond latencies over a millionfold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45°. Polarization information is reconstructed using both low-cost and low-latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image high dynamic range polarization scenes that vary at high speeds and to observe the dynamical properties of single collagen fibers in a bovine tendon under rapid cyclical ***: https://***/mFuCeTMWEqY © 2023 IEEE.

关键词： Polarization

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Interleaved Block-based Learned Image Compression with Feature Enhancement and Quantization Error Compensation

arXiv

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arXiv 2025年

作者： Jiang, Shiqi Yuan, Hui Li, Shuai Hamzaoui, Raouf Wang, Xu Huo, Junyan School of software Shandong University Shandong Jinan China School of Control Science and Engineering Shandong University Shandong Jinan China School of Engineering and Sustainable Development De Montfort University LeicesterLE1 9BH United Kingdom College of Computer Science and Software Engineering Shenzhen University Shenzhen China School of Telecommunications Engineering Xidian University Xi’an China

In recent years, learned image compression (LIC) methods have achieved significant performance improvements. However, obtaining a more compact latent representation and reducing the impact of quantization errors remain key challenges in the field of LIC. To address these challenges, we propose a feature extraction module, a feature refinement module, and a feature enhancement module. Our feature extraction module shuffles the pixels in the image, splits the resulting image into sub-images, and extracts coarse features from the sub-images. Our feature refinement module stacks the coarse features and uses an attention refinement block composed of concatenated three-dimensional convolution residual blocks to learn more compact latent features by exploiting correlations across channels, within sub-images (intra-sub-image correlations), and across sub-images (inter-sub-image correlations). Our feature enhancement module reduces information loss in the decoded features following quantization. We also propose a quantization error compensation module that mitigates the quantization mismatch between training and testing. Our four modules can be readily integrated into state-of-the-art LIC methods. Experiments show that combining our modules with Tiny-LIC outperforms existing LIC methods and image compression standards in terms of peak signal-to-noise ratio (PSNR) and multi-scale structural similarity (MS-SSIM) on the Kodak dataset and the CLIC dataset. Copyright © 2025, The Authors. All rights reserved.

关键词： Image compression

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Horizontal scaling method for a hyperconverged network

Horizontal scaling method for a hyperconverged network

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2021 International Conference on Information and Digital Technologies, IDT 2021

作者： Kovalenko, Andriy Kuchuk, Heorhii Kuchuk, Nina Kostolny, Jozef Kharkiv National University of Radio Electronics Faculty of Computer Engineering and Control Kharkiv Ukraine National Technical University KhPI Faculty of Computer and Information Technologies Kharkiv Ukraine Faculty of Management Science and Informatics Univeraity of Zilina Zilina Slovakia

ISBN: (纸本)9781665436922

Today cloud platforms are gradually being replaced by hyperconverged. With a hyperconverged infrastructure, the servers, networks, storage and computing power are combined. This is done through specific software. The main advantage of hyperconverged network is to reduce operating costs. However, system performance can be reduced due to the standardization of hardware modules and centralization of control, and, consequently, QoS deteriorates. At the same time, companies that operate computer systems are attracted by the ability to quick horizontal scaling and lower operating costs. Hyperconverged networks often use addition of a new hardware modules to meet QoS requirements using a simple horizontal scaling implementation. The purpose of the paper is to develop such a horizontal scaling method, which allows decreasing transaction processing time while total cost of data transmission does not exceed the specified values. The method also allows determining the optimal characteristics of additional hardware. © 2021 IEEE.

关键词： Resource allocation

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Robust Localization Based on Full Tdoa Set

SSRN

引用

SSRN 2023年

作者： Wang, Yuwei Xiong, Wenxin Wang, Zhi The College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310000 China The Department of Computer Science University of Freiburg Freiburg im Breisgau Baden-Württemberg79110 Germany

Time difference of arrival (TDOA) algorithms have attracted extensive attention among researchers in recent years. Instead of its widely studied non-redundant set counterpart, localization based on the full TDOA set is discussed herein. The non-redundant set is a subset of the full TDOA set. In the line-of-sight (LOS) scenarios, projecting the full TDOA set into a nonredundant set is a conventional way to reduce the computational complexity. In the non-LOS (NLOS) scenarios, it is no longer appropriate since the full TDOA set contains exploitable information and can not be transformed to an equivalent subset. Besides, the variety of NLOS errors is also a challenge. Alternatively, robust localization technologies can be used, yet it is not easy to combine the special data structures in the full TDOA set therewith. In this paper, we propose a new robust algorithm to perform NLOS-resistant localization using the full TDOA set. An essential contribution is that the proposed method jointly mitigates the negative effects of multiple types of NLOS bias errors in the optimization formulation. Simulation and experimental results demonstrate that the proposed scheme can outperform the state-of-the-art full TDOA set based approaches. © 2023, The Authors. All rights reserved.

关键词： Convex optimization

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An Efficient and Secured Energy Management System for Automated Guided Vehicles

An Efficient and Secured Energy Management System for Automa...

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IEEE International Conference on Big Data

作者： Jia-Hao Syu Jerry Chun-Wei Lin Dariusz Mrozek Department of Computer Science and Information Engineering National Taiwan University Taiwan Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Norway Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland

ISBN: (纸本)9781665480468

In this paper, we propose a Secure Energy Management System (SEMS) with anomaly detection and Q-Learning decision modules for Automated Guided Vehicles (AGV). The anomaly detection module is a multi-task learning network to simultaneously classify suppliers and predict the real supply quantities. The Q-learning decision module can then determine operating reserve and subsidies to manage the energy grid. Experimental results illustrate that the proposed anomaly detection module has an excellent performance in classifying malicious suppliers, excels at shaping supply distribution, and outperforms the existing benchmark systems.

关键词： Q-learning Remotely guided vehicles Big Data Benchmark testing Multitasking Energy management systems Anomaly detection

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VLC with PV-Based Optical Receiver for Motion Tolerant Optical Axon

VLC with PV-Based Optical Receiver for Motion Tolerant Optic...

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International Symposium on Communication Systems, Networks and Digital Signal Processing, CNSDSP

作者： George-Iulian Uleru Mircea Hulea Zabih Ghassemlooy Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iasi Iasi Romania Photonics Technologt Lab Optical Communications Research Group. FEE Northumbria University Newcastle upon Tyne United Kingdom

ISBN: (数字)9798350348743

ISBN: (纸本)9798350348750

Optical axons with visible light communication (VLC) can be used to connect areas of spiking neurons that are in relative motion to each other. In electro-optical-based spiking neural network the parallel transmission of the spikes generated by many neurons is achieved by multiplexing of optical signals. Alternatively, serial transmission of the optical pulses is possible if the activation rate of the neurons permits additional delays. In low-speed VLC systems, an energy efficient photovoltaic panels (PVs) could be used for energy harvesting and data reception (i.e., photodetectors). In this work, we report a multi-input optical axon VLC link with PV -based receiver and evaluate its performance in terms of the bit error ratio (BER) when PV panel powers the SOMAs of the neurons at the transmitter side. The results show that with power harvesting BER varies between 16% and ~40% when the channel length and misalignment are in the ranges 5 - 15 cm, and 0 - 60 degree, when the ambient light is around 280 lux. In the dark these parameters, when the ambient light is below 10 lux, BER drops under 10% for line of sight and distances up to 5 m.

关键词： Axons Neurons Optical computing Optical fiber networks Optical receivers Adaptive optics Optical transmitters

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CRB-Rate Tradeoff in RSMA-enabled Near-Field Integrated Multi-Target Sensing and Multi-User Communications

arXiv

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arXiv 2025年

作者： Zhou, Jiasi Zhou, Cong Sun, Yanjing Tellambura, Chintha School of Medical Information and Engineering Xuzhou Medical University Xuzhou221004 China School of Electronic and Information Engineering Harbin Institute of Technology Harbin150001 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada

Extremely large-scale antenna arrays enhance spectral efficiency and spatial resolution in integrated sensing and communication (ISAC) networks while expanding the Rayleigh distance, triggering a shift from conventional far-field plane waves to near-field (NF) spherical waves. However, full-digital beamforming is infeasible due to the need for dedicated radio frequency (RF) chains. To address this, NF-ISAC with a rate-splitting multiple access (RSMA) scheme is developed for advanced interference management, considering fully-connected and partially-connected hybrid analog and digital (HAD) beamforming architectures. Specifically, the Cramér-Rao bound (CRB) for joint distance and angle sensing is derived, and the achievable performance region between the max-min communication rate and the multi-target CRB is defined. To fully characterize the Pareto boundary of the CRB-rate region, a sensing-centric minimization problem is formulated under communication rate constraints for two HAD beamforming architectures. A penalty dual decomposition (PDD)-based double-loop algorithm is developed to optimize fully-connected HAD beamformers. To reduce computational complexity, a two-stage design algorithm for fully connected HAD beamforming is also proposed. Additionally, the PDD-based double-loop algorithm is extended to the partially-connected HAD architecture. Simulations demonstrate the proposed schemes and algorithms: 1) achieve performance comparable to a fully digital beamformer with fewer RF chains, 2) outperform space division multiple access and far-field ISAC, and 3) yield enhanced CRB-rate trade-off performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Cramer-Rao bounds

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Fair Division of Indivisible Goods: A Survey

arXiv

引用

arXiv 2022年

作者： Amanatidis, Georgios Birmpas, Georgios Filos-Ratsikas, Aris Voudouris, Alexandros A. Department of Mathematical Sciences University of Essex United Kingdom Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science University of Liverpool United Kingdom School of Computer Science and Electronic Engineering University of Essex United Kingdom

Allocating resources to individuals in a fair manner has been a topic of interest since the ancient times, with most of the early rigorous mathematical work on the problem focusing on infinitely divisible resources. Recently, there has been a surge of papers studying computational questions regarding various different notions of fairness for the indivisible case, like maximin share fairness (MMS) and envy-freeness up to any good (EFX). We survey the most important results in the discrete fair division literature, focusing on the case of additive valuation functions and paying particular attention to the progress made in the last 10 years. Copyright © 2022, The Authors. All rights reserved.

关键词： Surveys

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