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Boosting the Restoring Performance of Deduplication Data by Classifying Backup Metadata

ACM/IMS Transactions on Data Science 2021年第2期2卷 1–16页

作者： Yang, Ru Deng, Yuhui Zhou, Yi Huang, Ping Department of Computer Science Jinan University Guangzhou510632 China Department of Computer Science Jinan University China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China TSYS School of Computer Science Columbus State University Doimukh Georgia College of Engineering Temple University United States

Restoring data is the main purpose of data backup in storage systems. The fragmentation issue, caused by physically scattering logically continuous data across a variety of disk locations, poses a negative impact on the restoring performance of a deduplication system. Rewriting algorithms are used to alleviate the fragmentation problem by improving the restoring speed of a deduplication system. However, rewriting methods give birth to a big sacrifice in terms of deduplication ratio, leading to a huge storage space waste. Furthermore, traditional backup approaches treat file metadata and chunk metadata as the same, which causes frequent on-disk metadata accesses. In this article, we start by analyzing storage characteristics of backup metadata. An intriguing finding shows that with 10 million files, the file metadata merely takes up approximately 340 MB. Motivated by this finding, we propose a Classified-Metadata based Restoring method (CMR) that classifies backup metadata into file metadata and chunk metadata. Because the file metadata merely takes up a meager amount of space, CMR maintains all file metadata in memory, whereas chunk metadata are aggressively prefetched to memory in a greedy manner. A deduplication system with CMR in place exhibits three salient features: (i) It avoids rewriting algorithms' additional overhead by reducing the number of disk reads in a restoring process, (ii) it increases the restoring throughput without sacrificing the deduplication ratio, and (iii) it thoroughly leverages the hardware resources to boost the restoring performance. To quantitatively evaluate the performance of CMR, we compare our CMR against two state-of-the-art approaches, namely, a history-aware rewriting method (HAR) and a context-based rewriting scheme (CAP). The experimental results show that compared to HAR and CAP, CMR reduces the restoring time by 27.2% and 29.3%, respectively. Moreover, the deduplication ratio is improved by 1.91% and 4.36%, respectively. © 2

关键词： Metadata

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Hemodynamics in renal arteries with partial coverage after endovascular aneurysm repair affected by renal orientations

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Medicine in Novel Technology and Devices 2023年第2期18卷 81-90页

作者： Jun Wen Xinhui Liu Jianguo Lei Jiarong Wang Xiyang Chen Tinghui Zheng Ding Yuan School of Computer Science and Technology Southwest University of Science and TechnologyMianyang621010China Institute of Civil Engineering and Architecture Southwest University of Science and TechnologyMianyang621010China Department of Vascular Surgery West China HospitalSichuan UniversityChengdu610041China Department of Applied Mechanics Sichuan UniversityChengdu610000China

Endovascular aortic repair(EVAR)has been increasingly used to treat abdominal aortic aneurysm(AAA)due to its lower mortality and shorter recovery ***,the complications caused by renal artery coverage remained a major *** this study,three types of renal orientation and five types of partial renal coverage degree were adopted to numerically investigate the flow pattern,wall shear stress distribution,and blood perfusion during a cardiac *** results show that as for the mild partial coverage(=<30%),the renal artery with a downward orientation suffered fewer unfavorable wall shear stress(WSS)distribution and more blood *** should be noted that the renal artery with horizontal orientation suffered more unfavorable WSS *** terms of severe coverage(≥50%),all of the renal arteries displayed highly disturbed wall shear distribution,resulting in a significant reduction in blood perfusion It was interesting to note that the artery with an upward orientation had a smaller rate of reduction in blood *** can be concluded that as for the mild renal coverage after EVAR,renal arteries with downward orientation may have the advantage of reducing the possibility of renal occlusion,while renal arteries with horizontal orientation may increase the unfavorable wall shear *** the other hand,as for serious coverage(≥50%),high risk of renal ischemia remains the main concern for all types of renal arteries due to highly disturbed wall shear distribution would significantly increase regardless of renal orientation.

关键词： Hemodynamics Orientation Follow-up Numerical simulation Renal artery

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Tools for Refactoring to Microservices: A Preliminary Usability Report

arXiv

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arXiv 2023年

作者： Fritzsch, Jonas Correia, Filipe Bogner, Justus Wagner, Stefan Institute of Software Engineering University of Stuttgart Germany Faculty of Engineering University of Porto Portugal Department of Computer Science Vrije Universiteit Amsterdam Netherlands

While Microservices are a preferred choice for modern cloud-based applications, the migration and architectural refactoring of existing legacy systems is still a major challenge in industry. To address this, academia has proposed many strategies and approaches that aim to automate the process of decomposing a monolith into functional units. In this study, we review existing migration approaches regarding techniques used and tool support. From 91 publications, we extracted 22 tools, 7 of which address service decomposition. To assess them from an end-user perspective, we investigated their underlying techniques, installation, documentation, usability and support. For 5 of them, we generated service cuts using reference applications. The results of our preliminary work suggest that the inspected tools pursue promising concepts, but lack maturity and generalizability for reliable use by industry. © 2023, CC BY.

关键词： Decomposition

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Pixel Memories: Do Lifelog Summaries Fail to Enhance Memory but Offer Privacy-Aware Memory Assessments? 25

Pixel Memories: Do Lifelog Summaries Fail to Enhance Memory ...

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2025 CHI Conference on Human Factors in Computing Systems, CHI 2025

作者： Elagroudy, Passant Rzayev, Rufat Machulla, Tonja-Katrin Le, Huy Viet Dingler, Tilman Lischke, Lars Clinch, Sarah Ward, Geoffrey Schmidt, Albrecht Kaiserslautern Germany RPTU Kaiserslautern Kaiserslautern Germany Interactive Media Lab Dresden TUD Dresden University of Technology Dresden Germany Institute for Media Research TU Chemnitz Chemnitz Germany University of Stuttgart Stuttgart Germany Industrial Design Engineering Delft University of Technology Delft Netherlands User Centric Data Science Vrije Universiteit Amsterdam Amsterdam Netherlands Department of Computer Science The University of Manchester Manchester United Kingdom Department of Psychology University of Essex Essex United Kingdom LMU Munich Munich Germany

ISBN: (纸本)9798400713941

We explore the metaphorical "daily memory pill"concept - a brief pictorial lifelog recap aimed at reviving and preserving memories. Leveraging psychological strategies, we explore the potential of such summaries to boost autobiographical memory. We developed an automated lifelogging memory prosthesis and a research protocol (Automated Memory Validation "AMV") for conducting privacy-aware, in-situ evaluations. We conducted a real-world lifelogging experiment for a month (n=11). We also designed a browser "Pixel Memories"for browsing one-week worth of lifelogs. The results suggest that daily timelapse summaries, while not yielding significant memory augmentation effects, also do not lead to memory degradation. Participants' confidence in recalled content remains unaltered, but the study highlights the challenge of users' overestimation of memory accuracy. Our core contributions, the AMV protocol and "Pixel Memories"browser, advance our understanding of memory augmentations and offer a privacy-preserving method for evaluating future ubicomp systems. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory architecture

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Grain Size Distribution Analysis of Landslide Dams Caused by Dynamic Accumulation of Weathered Rock Landslides Using Discrete Element Modelling 29th

Grain Size Distribution Analysis of Landslide Dams Caused by...

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29th International Conference on Computational and Experimental engineering and Sciences, ICCES 2023

作者： Peng, Ming Zhao, Qingxi Shen, Danyi Zhu, Yan Zhao, Qingxin Zhou, Jiawen Cai, Shuo Key Laboratory of Geotechnical & Underground Engineering of Ministry of Education Tongji University Shanghai China Department of Geotechnical Engineering College of Civil Engineering Tongji University Shanghai China Institute of Geotechnical Engineering College of Civil Engineering and Architecture Zhejiang University Hangzhou China Shanghai Research Center of Ocean & Shipbuilding Engineering China Shipbuilding NDRI Engineering Co. Ltd. Shanghai China State Key Laboratory Hydraulic & Mountain River Engineering Sichuan University Chengdu China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China

ISBN: (纸本)9783031425141

The differences in the structure and composition materials of landslide dams often lead to great dissimilarity in dam stability, which often depend on the dynamic accumulation process of landslide dam. In order to investigate the response of dynamic characteristics of landslide to the composition material distribution of landslide dams, the migration and accumulation process of rock slopes with two weathering degrees was simulated by bonded particles and micro-cracks based on discrete element modelling. A new reconstructed distribution identification method was proposed in this paper to quantify the grain size distribution of dam. The results showed that the composition materials of dam, formed by weakly weathered slope, was poorly sorted, with medium particles located in surface layer, coarse particles located in middle and fine particles located in bottom of the valley. The material composition of dam, formed by strongly weathered slope, was well sorted, which spatial distribution showed well reverse segregation structure. It was found that the differences in particle size distribution between two kinds of landslide dams were mainly manifested in fine particles and coarse particles. The kinetic disintegration in weakly weathered slope was weakened, due to the accumulation of force coupling below hard rock at substrate, which occurred because of the fragmentation of particles aside it. As a result, there are more coarse particles and fewer fine particles in grain size distribution of its accumulation dam. This paper contributes to a better understanding of the structure and materials distribution of landslide dams, and assists the prediction of the stability of landslide dams. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Particle size

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A Voxel-Enabled Robotic Assistant for Omnidirectional Conveyance

A Voxel-Enabled Robotic Assistant for Omnidirectional Convey...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Michael Angelo Carvajal Katiso Mabulu Muneer Lalji James Flanagan Rui Luo Samuel Hibbard Tanav Chinthapatla Rohan Bettadpur Salah Bazzi Mark Zolotas Kristian Kloeckl Taşkın Padır Institute for Experiential Robotics Northeastern University Boston MA USA Department of Art + Design School of Architecture Northeastern University Electrical and Computer Engineering Northeastern University

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Conventional bidirectional conveyance platforms use a flat translating belt or a series of spinning wheels or rollers to apply a shear force to payloads to move them. Wheel/roller-based conveyors in particular cannot double as a worktop when idle, do not support collision-free multi-object manipulation by default, and are not optimized to move objects that are either slippery or pliable—let alone both. This paper introduces a Voxel-Enabled Robotic Assistant (VERA), a network of intelligent table "partitions" whose topologically dynamic worktops enable omnidirectional conveyance; each partition is composed of a 2D array of "quadrants," axisymmetric modules that can be hot-swapped for maintenance or repairs; each quadrant contains a 2D array of "cells," unitary robotic submodules; each cell houses an independently controllable "voxel," the motorized rotary element that conveys an overhead object. The efficacy of a VERA prototype was determined by evaluating waypoint error as a range of payloads were maneuvered between trajectory waypoints. By conveying both pliable and rigid payloads having slippery textures, the faceted voxels outperformed those augmented to mimic the circular-profiled wheels/rollers of competitor systems. VERA also successfully performed collision-free multi-object planar manipulations planned by its pathfinding algorithm. In light of these results, VERA emerges as a promising material handling platform for use in "Future of Work" settings as the need for multi-purpose collaborative industrial robots continues to grow.

关键词： Visualization Translation Service robots Prototypes Wheels Trajectory Mobile robots Collision avoidance Robots Payloads

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Large Scale Model Enabled Semantic Communications Based on Robust Knowledge Distillation

Large Scale Model Enabled Semantic Communications Based on R...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Ding, Kuiyuan Liu, Fangfang Yang, Yang Chen, Mingzhe Guo, Caili Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering The Institute for Data Science and Computing Coral GablesFL33146 United States Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China

ISBN: (纸本)9798350351255

Large scale artificial intelligence (AI) models possess excellent capabilities in semantic representation and understanding, making them particularly well-suited for semantic encoding and decoding. However, the substantial scale of these AI models imposes unacceptable computational resources and communication delays. To address this issue, we propose a semantic communication scheme based on robust knowledge distillation (RKD-SC) for large scale model enabled semantic communications. In the considered system, a transmitter extracts the features of the source image for robust transmission and accurate image classification at the receiver. To effectively utilize the superior capability of large scale model while make the cost affordable, we first transfer knowledge from a large scale model to a smaller scale model to serve as the semantic encoder. Then, to enhance the robustness of the system against channel noise, we propose a channel-aware autoencoder (CAA) based on the Transformer architecture. Experimental results show that the encoder of proposed RKD-SC system can achieve over 93.3% of the performance of a large scale model while compressing 96.67% number of parameters. Code: https://***/echojayne/RKD-SC. © 2024 IEEE.

关键词： Channel coding

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Modelling of Frequency Dependence in Self-Rectifying Analog BiFeO3 Memristors

Modelling of Frequency Dependence in Self-Rectifying Analog ...

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IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Xianyue Zhao Alon Ascoli Ahmet Samil Demirkol Ioannis Messaris Ilia Polian Ronald Tetzlaff Nan Du Institute for Solid State Physics Friedrich Schiller University Jena Jena Germany Department of Quantum Detection Leibniz Institute of Photonic Technology Jena Germany Department of Electronics and Telecommunications Politecnico di Torino Turin Italy Institute of Circuits and Systems Dresden University of Technology Dresden Germany Institute of Computer Science and Computer Engineering University of Stuttgart Stuttgart Germany

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

Memristors, recognized as the fourth fundamental circuit element, exhibit highly nonlinear dynamic behavior, analog computing capabilities, and significant potential for chaotic systems and complex dynamics. Self-rectifying analog BiFeO 3 (BFO) memristors, with their high on/off ratio, excellent retention, and remarkable endurance, are particularly promising for these applications. In this work, we present the first demonstration of frequency-dependent measurements on BFO memristors. Our results reveal that the on/off ratio of hysteresis in I-V characteristics and the maximum current in the positive bias range significantly decrease with increasing frequency. We formulated a simplified mathematical model of BFO behavior, based on an exponential ionic drift model for the positive bias region and a diffusion/diode-like I-V behavior for the negative bias region, ensuring high simulation speed while achieving substantial agreement with experimental data. By adjusting model parameters to account for higher amplitudes, we achieved improved alignment with experimental data. Future work will focus on refining the model to better accommodate these dynamic processes and further exploring the relationship between applied bias magnitude and device performance, enhancing the predictive dynamical behavior of BFO memristive devices in practical applications.

关键词： Performance evaluation Current measurement Refining Memristors Predictive models Mathematical models Data models Frequency measurement Nonlinear dynamical systems Hysteresis

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Algorithms for Large-Scale Quasi-Real Time Monitoring of Architectural and Cultural Heritage Based on MT-DInSAR Data

Algorithms for Large-Scale Quasi-Real Time Monitoring of Arc...

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Experimental Vibration Analysis for Civil engineering Structures - EVACES 2023 - Volume 2

作者： Talledo, D.A. Miano, A. Di Carlo, F. Bonano, M. Mele, A. Stella, A. Lanari, R. Meda, A. Prota, A. Saetta, A. Department of Architecture and Arts University IUAV of Venice Dorsoduro 2206 Venice30123 Italy Department of Structures for Engineering and Architecture University of Naples Federico II Via Claudio 21 Naples80125 Italy Department of Civil Engineering and Computer Science Engineering University of Rome "Tor Vergata" Via del Politecnico 1 Rome00133 Italy - Institute for Electromagnetic Sensing of the Environment Via Diocleziano 328 Naples80124 Italy

ISBN: (纸本)9783031391088

Structural Health Monitoring (SHM) is a field of increasing interest and worthy of new approaches and innovative applications. Italian territory is rich of architectural and cultural heritage that needs to be managed, monitored and conserved. This work presents a possible framework for the monitoring of such heritage that is suitable for large scale analyses and permits a fast and quick assessment, useful to the stakeholders responsible for its management. The proposed algorithms are based on an appealing technique, that gained popularity during the last years in the field of SHM, represented by the advanced multi-temporal differential synthetic aperture radar interferometry. Although the exploitation of these technique for the SHM of architectural and cultural heritage is still an open issue, different applications available in literature show promising potentialities. The algorithms and procedures proposed in this work are applied to a case study area located in the historic centre of Rome (Italy) to show the potentialities of the method. To this aim, COSMO-SkyMed ascending and descending datasets are processed applying the small baseline method obtaining deformation time series and mean velocity maps of the permanent scatterers located in the investigated area, for both geometry acquisitions. The information from these datasets are then elaborated and integrated with information from other data sources in order to provide a first estimation of potentially critical elements within the analyzed stock at urban level. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Structural health monitoring

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ArmorCLIP: A hybrid defense strategy for boosting adversarial robustness in vision-language models

ArmorCLIP: A hybrid defense strategy for boosting adversaria...

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2024 International Conference on computer Application and Information Security, ICCAIS 2024

作者： Li, Yijun Liang, Yuhan Niu, Yumeng Shen, Qianhe Liu, Hangyu Computer Science and Technology Harbin Institute of Technology Guangdong Shenzhen518055 China Faculty of Engineering University of Bristol BristolBS8 1TH United Kingdom Beijing University of Civil Engineering and Architecture Beijing102612 China University of Toronto Mississauga MississaugaL5L 1C6 Canada Xi’an Tieyi ICC Shaanxi Xi’an710054 China

ISBN: (纸本)9781510689312

The robustness of Vision-Language Models (VLMs) such as Contrastive Language-Image Pretraining (CLIP) is critical for their deployment in safety-critical applications like autonomous driving, healthcare diagnostics, and security systems, where accurate interpretation of visual and textual data is essential. However, these models are highly susceptible to adversarial attacks, which can severely compromise their performance and reliability in real-world scenarios. Previous methods have primarily focused on improving robustness through adversarial training and generating adversarial examples using models like FGSM, AutoAttack, and DeepFool. However, these approaches often rely on strong assumptions, such as fixed perturbation norms or predefined attack patterns, and involve high computational complexity, making them challenging to implement in practical settings. In this paper, we propose a novel adversarial training framework that integrates multiple attack strategies and advanced machine learning techniques to significantly enhance the robustness of VLMs against a broad range of adversarial attacks. Experiments conducted on real-world datasets, including CIFAR-10 and CIFAR-100, demonstrate that the proposed method significantly enhances model robustness. The fine-tuned CLIP model achieved an accuracy of 43.5% on adversarially perturbed images, compared to only 4% for the baseline model. The neural network model achieved a high accuracy of 98% in these challenging classification tasks, while the XGBoost model reached a success rate of 85.26% in prediction tasks. © The Authors.

关键词： Adversarial machine learning

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