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FlexiFed: Personalized Federated Learning for Edge Clients with Heterogeneous Model Architectures 23

FlexiFed: Personalized Federated Learning for Edge Clients w...

引用

2023 World Wide Web Conference, WWW 2023

作者： Wang, Kaibin He, Qiang Chen, Feifei Chen, Chunyang Huang, Faliang Jin, Hai Yang, Yun School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing Technologies Swinburne University of Technology Australia School of Information Technology Deakin University Australia Faculty of Information Technology Monash University Australia Guangxi Key Lab of Human-machine Interaction and Intelligent Decision Nanning Normal University China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450394161

Mobile and Web-of-Things (WoT) devices at the network edge account for more than half of the world's web traffic, making a great data source for various machine learning (ML) applications, particularly federated learning (FL) which offers a promising solution to privacy-preserving ML feeding on these data. FL allows edge mobile and WoT devices to train a shared global ML model under the orchestration of a central parameter server. In the real world, due to resource heterogeneity, these edge devices often train different versions of models (e.g., VGG-16 and VGG-19) or different ML models (e.g., VGG and ResNet) for the same ML task (e.g., computer vision and speech recognition). Existing FL schemes have assumed that participating edge devices share a common model architecture, and thus cannot facilitate FL across edge devices with heterogeneous ML model architectures. We explored this architecture heterogeneity challenge and found that FL can and should accommodate these edge devices to improve model accuracy and accelerate model training. This paper presents our findings and FlexiFed, a novel scheme for FL across edge devices with heterogeneous model architectures, and three model aggregation strategies for accommodating architecture heterogeneity under FlexiFed. Experiments with four widely-used ML models on four public datasets demonstrate 1) the usefulness of FlexiFed;and 2) that compared with the state-of-the-art FL scheme, FlexiFed improves model accuracy by 2.6%-9.7% and accelerates model convergence by 1.24 × -4.04 ×. © 2023 ACM.

关键词： Speech recognition

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The content pollution in peer-to-peer live streaming systems: Analysis and implications

The content pollution in peer-to-peer live streaming systems...

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37th International Conference on Parallel Processing, ICPP 2008

作者： Yang, Sirui Jin, Hai Li, Bo Liao, Xiaofei Yao, Hong Tu, Xuping Services Computing Technology and System Lab. School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computer Science Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9780769533742

There has been significant progress in the development and deployment of Peer-to-Peer (P2P) live video streaming systems. However, there has been little study on the security aspect in such systems. Our prior experiences in Anysee exhibit that existing systems are largely vulnerable to intermediate attacks, in which the content pollution is a common attack that can significantly reduce the content availability, and consequently impair the playback quality. This paper carries out a formal analysis of content pollution and discusses its implications in P2P live video streaming systems. Specifically, we establish a probabilistic model to capture the progress of content pollution. We verify the model using a real implementation based on Anysee system;we evaluate the content pollution effect through extensive simulations. We demonstrate that (1) the number of polluted peers can grow exponentially, similar to random scanning worms. This is vital that with 1 % polluters, the overall system can be compromised within minutes;(2) the effective bandwidth utilization can be sharply decreased due to the transmission of polluted packets;(3) Augmenting the number of polluters does not imply a faster progress of content pollution, in which the most influential factors are the peer degree and access bandwidth. We further examine several techniques and demonstrate that a hash-based signature scheme can be effective against the content pollution, in particular when being used during the initial phase.1 © 2008 IEEE.

关键词： Pollution

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Secure Third Party Auditor for Ensuring Data Integrity in Cloud Storage

Secure Third Party Auditor for Ensuring Data Integrity in Cl...

引用

Symposia and Workshops on Ubiquitous, Autonomic and Trusted computing, UIC-ATC

作者： Salah H. Abbdal Hai Jin Deqing Zou Ali. A. Yassen Services Computing Technology and System Lab University of Science and Technology Wuhan China

Although cloud computing is extremely active over the Internet in the real world, it presents many security challenges, such as access control and data integrity, which refer to the fact that while users can deploy their files into the cloud server, no one knows exactly where they should be. Thus, users' data may be threatened by internal or external attacks. Recently, some proposed schemes are aiming to find solutions to these problems which directly affect the data under the cloud. These are based on a Third Party Auditor (TPA) as one of the most popular solutions, where users no longer have physical possession of the possibly large size of their outsourced data, and they consider that the TPA should be able to efficiently audit the cloud data storage without demanding local copies of data, and they introduce no additional on-line burden to the cloud user. Unfortunately, these schemes have assumed that the TPA is a trusted party for users. In fact, this assumption is critical, because the security aspect hinders widespread adoption of the cloud. However, users cannot ensure that either the TPA or the cloud server (CS) will not be impersonated by an attacker. So, the cloud user should be the only person (data owner) who has confidentiality about his data. We offer a new TPA model that differs from previous models and overcomes the above-mentioned issues. Our proposed scheme has three main components: the cloud user (data owner), the TPA, and the cloud server (CS), where only the user has the authority for his data and he deals with other components as services. The proposal enjoys several advantages such as preserving privacy and session key secrecy. Our proposed scheme combines the two important features of both efficiency and security concerns: (1) TPA functionalities, (2) complete confidentiality at the user side. Furthermore, our work includes many security features such as secure and efficient use of the TPA for correct data storage with supporting data dynami

关键词： Cloud computing Servers Cryptography Memory Conferences Metadata

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Intersecting-Boundary-Sensitive Fingerprinting for Tampering Detection of DNN Models 41

Intersecting-Boundary-Sensitive Fingerprinting for Tampering...

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41st International Conference on Machine Learning, ICML 2024

作者： Bai, Xiaofan He, Chaoxiang Ma, Xiaojing Zhu, Bin Benjamin Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China Microsoft United States School of Computer Science and Technology Huazhong University of Science and Technology China Cluster and Grid Computing Lab China

Cloud-based AI services offer numerous benefits but also introduce vulnerabilities, allowing for tampering with deployed DNN models, ranging from injecting malicious behaviors to reducing computing resources. Fingerprint samples are generated to query models to detect such tampering. In this paper, we present Intersecting-Boundary-Sensitive Fingerprinting (IBSF), a novel method for black-box integrity verification of DNN models using only top-1 labels. Recognizing that tampering with a model alters its decision boundary, IBSF crafts fingerprint samples from normal samples by maximizing the partial Shannon entropy of a selected subset of categories to position the fingerprint samples near decision boundaries where the categories in the subset intersect. These fingerprint samples are almost indistinguishable from their source samples. We theoretically establish and confirm experimentally that these fingerprint samples' expected sensitivity to tampering increases with the cardinality of the subset. Extensive evaluation demonstrates that IBSF surpasses existing state-of-the-art fingerprinting methods, particularly with larger subset cardinality, establishing its state-of-the-art performance in black-box tampering detection using only top-1 labels. The IBSF code is available at: https://***/CGCL-codes/IBSF. Copyright 2024 by the author(s)

关键词： HTTP

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AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis of the Femoral Head Detection 37

AsT: An Asymmetric-Sensitive Transformer for Osteonecrosis o...

引用

37th AAAI Conference on Artificial Intelligence, AAAI 2023

作者： Chen, Haoyang Liu, Shuai Lu, Feng Li, Wei Sheng, Bin Li, Mi Jin, Hai Zomaya, Albert Y. National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Department of Computer Science and Engineering Shanghai Jiao Tong University China Tongji Hospital Tongji Medical College Huazhong University of Science and Technology China

ISBN: (纸本)9781577358800

Early diagnosis of osteonecrosis of the femoral head (ONFH) can inhibit the progression and improve femoral head preservation. The radiograph difference between early ONFH and healthy ones is not apparent to the naked eye. It is also hard to produce a large dataset to train the classification model. In this paper, we propose Asymmetric-Sensitive Transformer (AsT) to capture the uneven development of the bilateral femoral head to enable robust ONFH detection. Our ONFH detection is realized using the self-attention mechanism to femoral head regions while conferring sensitivity to the uneven development by the attention-shared transformer. The real-world experiment studies show that AsT achieves the best performance of AUC 0.9313 in the early diagnosis of ONFH and can find out misdiagnosis cases firmly. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Large dataset

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Exploring the Impact of Processing Guarantees on Performance of Stream Data Processing

Exploring the Impact of Processing Guarantees on Performance...

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2017 17th IEEE International Conference on Communication technology (ICCT 2017)

作者： Syed Muhammad Abrar Akber Changfu Lin Hanhua Chen Fan Zhang Hai Jin Cluster and Grid Computing Lab Services Computing Technology and System Lab Big Data Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology

Processing semantics ensure tuple processing guarantees during system recovery from failures. It determines whether particular tuples are re-processed or not upon system recovery. Processing semantics facilitate to maintain real-time response as well as correctness of results in stream data processing. Existing literature is in real deficit to provide sufficient resources exclusively on processing semantics. This work focuses on reviewing processing semantics in stream data processing *** article aims at exploring the impact of processing guaran-tees on performance of stream data processing. We summarize current research directions to guarantee processing semantics,based on prominent stream processing engines. Furthermore,we compare throughput for a couple of representative stream processing engines under all possible processing *** experiments show that at-most once processing guarantee provides the highest throughput among other guarantees. Lastly,challenges for further research are also discussed in this paper.

关键词： stream data processing processing semantic processing guarantee at-least once at-most once exactly-once

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Adaptive multi-round scheduling strategy for divisible workloads in grid environments

Adaptive multi-round scheduling strategy for divisible workl...

引用

International Conference on Information Networking

作者： Yongcai Tao Hai Jin Song Wu Xuanhua Shi Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424445264

Scheduling is the key to divisible workload execution. UMR (uniform multi-round) algorithm potentially performs near optimal by improving overlap of communication and computation. However, it is questioned how a static schedule works effectively in dynamic grid environment. The paper proposes an adaptive divisible workload scheduling system, which can adjust the schedule in a proactive way. An adaptive UMR-based multi-round algorithm (called AUMR) is presented and evaluated. In AUMR, if the run-time resource monitor notifies the scheduler of any resource changes, the scheduler will evaluate its impact and adjust the schedule if necessary. The experiment results show a considerable performance improvement by AUMR in dynamic grid environment.

关键词： Adaptive scheduling Processor scheduling Grid computing Dynamic scheduling Monitoring Scheduling algorithm Robustness Delay Computers Clustering algorithms

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Evaluating Latency-Sensitive Applications' Performance Degradation in Datacenters with Restricted Power Budget

Evaluating Latency-Sensitive Applications' Performance Degra...

引用

International Conference on Parallel Processing

作者： Song Wu Chuxiong Yan Haibao Chen Hai Jin Wei Guo Zhen Wang Deqing Zou Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Tencent Inc

ISBN: (纸本)9781467375887

For datacenters with limited power supply, restricting the servers' power budget (i.e., the maximal power provided to servers) is an efficient approach to increase the server density (the server quantity per rack), which can effectively improve the cost-effectiveness of the datacenters. However, this approach may also affect the performance of applications in servers. Hence, the prerequisite of adopting the approach in datacenters is to precisely evaluate the application performance degradation caused by restricting the servers' power budget. Unfortunately, existing evaluation methods are inaccurate because they are either improper or coarse-grained, especially for the latency-sensitive applications widely deployed in datacenters. In this paper, we analyze the reasons why state-of-the-art methods are not appropriate for evaluating the performance degradation of latency-sensitive applications in case of power restriction, and we propose a new evaluation method which can provide a fine-grained way to precisely describe and evaluate such degradation. We verify our proposed method by a real-world application and the traces from Tencent's datecenter with 25328 servers. The experimental results show that our method is much more accurate compared with the state of the art, and we can significantly increase datacenter efficiency by saving servers' power budget while maintaining the applications' performance degradation within controllable and acceptable range.

关键词： Servers degradation of performance power budget evaluation method state of the art Budgets

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VMGrid: A Virtual Machine supported grid middleware

VMGrid: A Virtual Machine supported grid middleware

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IEEE International Conference on Granular computing (GRC)

作者： Song Wu Wei Zhu Wenbin Jiang Hai Jin Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424425129

Many grid middleware such as Globus Toolkit and GPE have started to support virtual machines. They implement the remote control of virtual machine by grid service and make use of virtual machinespsila function of quick deployment to construct the execution environment of grid application fast. In order to support virtual machine in grid environment, VMGrid (Virtual Machine Grid) is presented. All services in VMGrid are implemented based on secure shell host protocol (SSH) while Globus Toolkitpsilas Virtual Workspace is on WSRF. This paper gives a clear description of VMGrid. Some comparisons with Globus Toolkitpsilas Virtual Workspace in performance are made in this paper. Performance results show that VMGrid virtual workspace atomic services are more effective than that of Globus.

关键词： Virtual machining Middleware Grid computing Operating systems Software Libraries Computers

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A Semantic Double-Buffer Based Approach to Enhance Semantic Web Search

A Semantic Double-Buffer Based Approach to Enhance Semantic ...

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International Conference on the Digital Society

作者： Ling Chen Hai Jin Sheng Di Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan China

With the development of semantic Web, search efficiency is becoming a challenging issue. To address this problem, we design an approach which mainly has two features. First, we explore potential semantic relationship between different objects and make full use of them to build a semantic buffer on server end, enhancing search speed. Second, we put another relatively small semantic buffer on each client so as to adapt to each individual user's interests, further improving the whole search efficiency and reducing server's load. Through testing on a practical platform, we testified that this semantic double-buffer based search approach can not only effectively reduce user's request response time, but considerably release server's load, bringing a high scalability.

关键词： Semantic Web Testing Resource description framework Algorithm design and analysis Indexing Grid computing Computers Delay Scalability Information retrieval

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