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arXiv 2022年

作者： Wei, Kang Li, Jun Ma, Chuan Ding, Ming Wei, Sha Wu, Fan Chen, Guihai Ranbaduge, Thilina School of Electrical and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China Ministry of Education China Data61 CSIRO SydneyNSW2015 Australia Beijing100191 China The Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

Recently, federated learning (FL) has emerged as a promising distributed machine learning (ML) technology, owing to the advancing computational and sensing capacities of end-user devices, as well as the increasing concerns on users' privacy. As a special architecture in FL, vertical FL (VFL) is capable of constructing a hyper ML model by embracing sub-models from different types of clients. These sub-models are trained locally by vertically partitioned data with distinct attributes. Therefore, the design of VFL is fundamentally different from that of conventional FL, raising new and unique research issues. In this paper, we aim to discuss key challenges in VFL with effective solutions, and conduct experiments on real-life datasets to shed light on these issues. Specifically, we first propose a general framework on VFL, and highlight the key differences between VFL and conventional FL. Then, we discuss research challenges rooted in VFL systems from four aspects, i.e., security and privacy risks, expensive computation and communication costs, possible structural damage caused by model splitting, and system heterogeneity. Afterwards, we develop solutions to addressing the aforementioned challenges, and conduct extensive experiments to showcase the effectiveness of the proposed solutions. Copyright © 2022, The Authors. All rights reserved.

关键词： Federated learning

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Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification

Seq-Masks: Bridging the gap between appearance and gait mode...

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IEEE Visual Communications and Image Processing (VCIP)

作者： Zhigang Chang Zhao Yang Yongbiao Chen Qin Zhou Shibao Zheng Institute of Image Processing and Network Engineering Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781728173221

Video-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods focus on exploring appearance information, thus, vulnerable against illumination changes, scene noises, camera parameters, and especially clothes/carrying variations. Gait recognition provides an implicit biometric solution to alleviate the above headache. Nonetheless, it experiences severe performance degeneration as camera view varies. In an attempt to address these problems, in this paper, we propose a framework that utilizes the sequence masks (SeqMasks) in the video to integrate appearance information and gait modeling in a close fashion. Specifically, to sufficiently validate the effectiveness of our method, we build a novel dataset named MaskMARS based on MARS. Comprehensive experiments on our proposed large wild video Re-ID dataset MaskMARS evidenced our extraordinary performance and generalization capability. Validations on the gait recognition metric CASIA-B dataset further demonstrated the capability of our hybrid model. Our codes and dataset MaskMARS will be open-sourced as a strong baseline.

关键词： Measurement Mars Image recognition Codes Visual communication Surveillance Video sequences

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Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification

arXiv

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arXiv 2021年

作者： Chang, Zhigang Yang, Zhao Chen, Yongbiao Zhou, Qin Zheng, Shibao Institute of Image Processing and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China

关键词： Gait analysis

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Reversible Data Hiding With Secret Encrypted Image Sharing and Adaptive Coding

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IEEE Internet of Things Journal 2025年

作者： Fang, Guangtian Wang, Feng Zhao, Chenbin Qin, Chuan Chang, Ching-Chun Chang, Chin-Chen Fujian University of Technology College of Computer Science and Mathematics Fuzhou350118 China Fujian University of Technology College of Computer Science and Mathematics Key Laboratory of Big Data Mining and Applications Fuzhou350118 China Monash University Faculty of IT Department of Software Systems and Cybersecurity VIC3800 Australia Ministry of Education School of Cyber Science and Engineering Key Laboratory of Aerospace Information Security and Trusted Computing Wuhan430072 China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200093 China Feng Chia University Information and Communication Security Research Center Taichuang 40724 Taiwan Feng Chia University Department of Information Engineering and Computer Science Taichung40724 Taiwan

To ensure the security of image information and facilitate efficient management in the cloud, the utilization of reversible data hiding in encrypted images (RDHEI) has emerged as pivotal. However, most existing RDHEI schemes suffer from lower security and limited embedding capacity. To tackle these challenges, we propose a reversible data hiding with secret encrypted image sharing and adaptive coding scheme. Specifically, in the encryption phase, we introduce an improved secret sharing (SS) encryption method based on the chinese remainder theorem for polynomials (CRTP). This method not only improves the security of encrypted images but also vacates a larger room for embedding. In the embedding phase, we introduce an adaptive coding embedding approach using XOR preservation (XORP) and huffman coding, which provides high embedding capacity. Experimental results and security analysis demonstrate that our proposed encryption method achieves optimal values in security indicators for encrypted images, such as information entropy, histograms, NPCR and UACI. The proposed embedding method is superior to some state-of-the-art schemes in terms of embedding capacity. Furthermore, in datasets BOSSBase and BOWS2, the average embedding rates of the proposed embedding approach can reach 2.1745 bpp and 2.0656 bpp, respectively. © 2025 IEEE.

关键词： adaptive coding chinese remainder theorem for polynomials encrypted images Reversible data hiding secret sharing

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Priority Policy in Multi-Queue Data Center Networks via per-Port ECN Marking

Priority Policy in Multi-Queue Data Center Networks via per-...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Akbar Majidi Xiaofeng Gao Nazila Jahanbakhsh Jiaqi Zheng Guihai Chen Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (数字)9781728154534

ISBN: (纸本)9781728154541

Explicit Congestion Notification (ECN) as a main part of the Internet congestion control was originally designed with a single queue in mind. But, nowadays data centers industry trends to have multiple queues per-port in its switches. This type of mismatch can affect the scheduling schemes and hence leads to remarkable performance degradation in multi-queue switches. For instance, when some of the queue buffers of the switch exceed the considered thresholds, all the packets belonging to the same shared port could get ECN mark. To cope with this challenge, we propose Priority-ECN, a first systematic solution to this problem. The first intuition of Priority-ECN lies in the fact that if any packet gets marked, it should be prioritized to pass a route quicker than the others to notify the condition of the network in an early stage. This presents a full view of instantaneous demand from all senders. The second intuition is that if any packet gets marked in the queue buffer, Priority-ECN will not consider them in the marking decision again in the output port buffer. The third intuition is to reach the goal of high throughput without sacrificing the latency. So, we use an approach similar to Cut Payload (CP), which drops the payloads of packets, rather than the metadata, when a queue reaches the threshold. We do so through dual couple buffer in output port and catch the advantage of CP to implement an efficient scheme to obtains near optimal flow completion times across different flow sizes with very low latency.

关键词： Throughput Data centers Transport protocols Standards Payloads Market research Job shop scheduling

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SMedBERT: A knowledge-enhanced pre-trained language model with structured semantics for medical text mining

arXiv

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arXiv 2021年

作者： Zhang, Taolin Cai, Zerui Wang, Chengyu Qiu, Minghui Yang, Bite He, Xiaofeng School of Software Engineering East China Normal University Alibaba Group Shanghai Key Laboratory of Trsustworthy Computing School of Computer Science and Technology East China Normal University Dxy Shanghai Research Institute for Intelligent Autonomous Systems

Recently, the performance of Pre-trained Language Models (PLMs) has been significantly improved by injecting knowledge facts to enhance their abilities of language understanding. For medical domains, the background knowledge sources are especially useful, due to the massive medical terms and their complicated relations are difficult to understand in text. In this work, we introduce SMedBERT, a medical PLM trained on large-scale medical corpora, incorporating deep structured semantics knowledge from neighbours of linked-entity. In SMedBERT, the mention-neighbour hybrid attention is proposed to learn heterogeneousentity information, which infuses the semantic representations of entity types into the homogeneous neighbouring entity structure. Apart from knowledge integration as external features, we propose to employ the neighbors of linked-entities in the knowledge graph as additional global contexts of text mentions, allowing themto communicate via shared neighbors, thus enrich their semantic representations. Experiments demonstrate that SMedBERT significantly outperforms strong baselines in various knowledge-intensive Chinese medical tasks. It also improves the performance of other tasks such as question answering, questionmatching and natural language inference. Copyright © 2021, The Authors. All rights reserved.

关键词： Knowledge graph

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Timed data plane update in data center network 25

Timed data plane update in data center network

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25th IEEE International Conference on Parallel and Distributed systems, ICPADS 2019

作者： Liu, Yuxiang Gao, Xiaofeng Zheng, Jiaqi Chen, Guihai Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781728125831

software-Defined Networks make it more principled and formal to operate and verify networks, which decouple the control plane and the data plane and introduce flexibility and programmability into the network. The SDN control plane needs to frequently update the data plane. However, the decoupled control and data planes face new challenges. The network is still an asynchronous distributed system in rule updates. If the update operations are not carefully scheduled, it may result in blackhole, congestions, and violate the consistency properties. Motivated by the tightly synchronized SDNs, we proposed TIDERS Algorithm for consistent network updates in 'timed SDNs'-where one node update can be scheduled at specific time. In TIDERS, we use synchronized time technique to achieve fast network updates while guaranteeing consistency properties. We focus on congestion-free in scheduling the update operations. To achieve this, we first set up a flow-based dependency graph and transform it into switch-operation level dependency graph. Based on operation dependency graph, we generate an update schedule and gradually optimize it to finally get a fast update schedule. After that, we conduct a series of simulations comparing our approach with several other methods to evaluate it. © 2019 IEEE.

关键词： Flow graphs

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Chronus+: Minimizing Switch Buffer Size during Network Updates in Timed SDNs

Chronus+: Minimizing Switch Buffer Size during Network Updat...

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International Conference on Distributed computing systems

作者： Xin He Jiaqi Zheng Haipeng Dai Yuhu Sun Wanchun Dou Guihai Chen State Key Laboratory for Novel Software Technology Nanjing University China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China

ISBN: (数字)9781728170022

ISBN: (纸本)9781728170039

Although the logically-centralized perspective is offered in software-Defined Networks (SDNs), the data plane is still distributed in nature. Update commands sent by the centralized controller are executed asynchronously and independently in each switch. The timed SDNs enable synchronous and coordinate update operations as each update command can be triggered by a pre-defined time point. Prior work on timed update mainly focuses on how to produce a congestion-free update sequence, whereas finding a congestion-free timed update sequence may be too long to be applied in practice, even worse, such an update order may not exist. In this paper, we propose Chronus + , a timed update system that utilizes switch buffer to shorten the update time while minimizing the switch buffer size during updates. We formulate the Minimum Switch Buffer Size Problem (MSBSP) as an optimization program and show its hardness. A set of efficient algorithms is proposed to determine a timed update sequence in polynomial time. Extensive evaluations in Mininet and large-scale simulations show that Chronus + can reduce the update time by at least 17% and the switch buffer by at least 27% compared with state-of-the-art approaches.

关键词： Conferences Computational modeling Distributed databases Switches Control systems Optimization

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Mining Robust Frequent Items in Data Streams

Mining Robust Frequent Items in Data Streams

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IEEE International Conference on Joint Cloud computing (JCC)

作者： Rui Xia Haipeng Dai Zhanchao Du Meng Li Alex X. Liu Guihai Chen State Key Laboratory for Novel Software Technology Nanjing University Nanjing CHINA Institute of Manned Space System Engineering China Academy of Space Technology Beijing CHINA Shanghai key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai CHINA

ISBN: (数字)9781728169811

ISBN: (纸本)9781728169828

This paper studies the problem of robust frequent items mining in data streams that generalizes the traditional frequent items mining by considering the noise of datasets. That is, different items may correspond to the same entity because of noise; examples include different images of the same object and fluctuated data in the same setting measured by sensors. Our objective is to identify those items that correspond to the same entity and have an aggregated frequency exceeding a given threshold, which named as robust frequent items. To the best of our knowledge, there is no existing works on mining robust frequent items in a data stream. In this paper, we first propose a scheme by applying sampling and spatial partition to address the problem in low dimensional spaces. Furthermore, we extend the above algorithmic framework to high dimensional spaces by incorporating the locality sensitive hashing scheme to deal with the approximate nearest neighbor problem. We conduct evaluations using synthetic datasets and compare our scheme with two prior adapted schemes. Our results demonstrate that the efficiency of our algorithms outperforms the adaptive Space Saving by 14.8% and 9.8% in terms of precision and recall, respectively.

关键词： Noise measurement Robustness Data mining Partitioning algorithms Approximation algorithms Two dimensional displays Sensors

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The Quantum Internet (Technical Version)

arXiv

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arXiv 2025年

作者： Rohde, Peter P. Huang, Zixin Ouyang, Yingkai Huang, He-Liang Su, Zu-En Devitt, Simon Ramakrishnan, Rohit Mantri, Atul Tan, Si-Hui Liu, Nana Harrison, Scott Radhakrishnan, Chandrashekar Brennen, Gavin K. Baragiola, Ben Q. Dowling, Jonathan P. Byrnes, Tim Munro, William J. Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW Australia Hearne Institute for Theoretical Physics Louisiana State University Baton Rouge United States School of Mathematical and Physical Sciences Macquarie University NSW2109 Australia School of Mathematical and Physical Sciences University of Sheffield SheffieldS3 7RH United Kingdom Henan Key Laboratory of Quantum Information and Cryptography Henan Zhengzhou450000 China Hefei National Laboratory for Physical Sciences at Microscale Department of Modern Physics University of Science & Technology of China Hefei China CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information & Quantum Physics University of Science & Technology of China Hefei China CAS-Alibaba Quantum Computing Laboratory Shanghai China InstituteQ Aalto University Espoo02150 Finland Indian Institute of Science Bangalore India Singapore University of Technology & Design Singapore Centre for Quantum Technologies National University of Singapore Singapore Horizon Quantum Ireland 24 Fitzwilliam Place Dublin 2 D02 T296 Ireland Institute of Natural Sciences Shanghai Jiao Tong University Shanghai200240 China School of Mathematical Sciences Shanghai Jiao Tong University Shanghai200240 China Ministry of Education Key Laboratory in Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai200240 China Shanghai Artificial Intelligence Laboratory Shanghai China University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai200240 China Leibniz Institute for Research & Information in Education Frankfurt am Main Germany Department of Computer Science and Engineering NYU Shanghai 567 West Yangsi Road Shanghai200124 China Centre of Excellence in Engineered Quantum Systems Macquarie University NSW Australia Centre for Quantum Computation and Communication Technology School of Science RMIT University VIC

The desire to share and unite remote digital assets motivated the development of the classical internet, the enabler of the entire 21st century economy and our modern way of life. As we enter the quantum era, it is to be expected there will be a similar demand for networking quantum assets, motivating a global quantum internet for bringing together the world's quantum resources, leveraging off their exponential trajectory in capability. We present models for quantum networking, how they might be applied in the future, and the implications they will have. Socially, economically, politically and geostrategically, the upcoming era of quantum supremacy will be as significant for the 21st century as the transistor was for the 20th. The inherently different scaling in the computational power of quantum computers fundamentally changes the dynamics of how they will operate in the future. Given their high expected initial cost, a client/server model for outsourcing computation will be essential for enabling the accessibility and proliferation of this technology, and ensuring its economic viability. We therefore anticipate the emergence of cloud quantum computing, a model for outsourcing quantum computations to the network. We argue that economic efficiency will mandate that all future quantum computers be united into a single global virtual quantum computer, offering exponentially more power to all network participants than if they were to keep their resources to themselves. This model for the allocation of computational resources is uniquely quantum, with no classical analogue, completely altering the economic landscape for the future of computation. Given the sensitivity of much of the data to which future quantum computers are going to foreseeably be applied, protocols for encrypted quantum computation will be essential - the outsourcing of computations that neither an eavesdropper nor even the server performing the computation can spy upon. This will enable new models fo

关键词： Outsourcing

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