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作者： Chen, Gang Jin, Hai Zou, Deqing Zhou, Bing Bing Qiang, Weizhong Hu, Gang Cluster and Grid Computing Lab. Services Computing Technology and System Lab. Huazhong University of Science and Technology Wuhan 430074 China Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney NSW 2006 Australia

ISBN: (纸本)9780769542201

When multiple instances of an application running on multiple virtual machines, an interesting problem is how to utilize the fault handling result from one application instance to heal the same fault occurred on other sibling instances, and hence to ensure high service availab.lity in a cloud computing environment. This paper presents SHelp, a lightweight runtime system that can survive software failures in the framework of virtual machines. It applies weighted rescue points and error virtualization techniques to effectively make applications bypass the faulty path. A two-level storage hierarchy is adopted in the rescue point database for applications running on different virtual machines to share error handling information to reduce the redundancy and to more effectively and quickly recover from future faults caused by the same bugs. A Linux prototype is implemented and evaluated using four web server applications that contain various types of bugs. Our experimental results show that SHelp can make server applications to recover from these bugs in just a few seconds with modest performance overhead. © 2010 IEEE.

关键词： Software reliability

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Economy-based data replication broker

Economy-based data replication broker

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e-Science 2006 - 2nd IEEE International Conference on e-Science and grid computing

作者： Lin, Henry Abawajy, J.H. Buyya, Rajkumar Grid Computing and Distributed Systems Lab. Dept. of Computer Science and Software Eng. University of Melbourne Melbourne VIC 3010 Australia Grid and Pervasive Computing Lab. School of Eng. and Information Technology Deakin University Geelong VIC 3072 Australia

ISBN: (纸本)0769527345

Data replication is one of the key components in data grid architecture as it enhances data access and reliability and minimises the cost of data transmission. In this paper, we address the problem of reducing the overheads of the replication mechanisms that drive the data management components of a data grid. We propose an approach that extends the resource broker with policies that factor in user quality of service as well as service costs when replicating and transferring data. A realistic model of the data grid was created to simulate and explore the performance of the proposed policy. The policy displayed an effective means of improving the performance of the grid network traffic and is indicated by the improvement of speed and cost of transfers by brokers. © 2006 IEEE.

关键词： Data reduction

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List scheduling method for service oriented grid applications

List scheduling method for service oriented grid application...

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2006 2nd International Conference on Semantics Knowledge and grid, SKG

作者： Chin, SungHo Lee, JongHyuk Yoon, TaeMyoung Yu, HeonChang Distributed and Grid Computing Lab. Department of Computer Science Education Korea University Anam-dong Sungbuk-ku Seoul 136-701 Korea Republic of

ISBN: (纸本)0769532055

Recently, grid computing environment has being changed to the service-oriented grid integrated with Web Services for supporting more open, scalab.e and flexible grid architecture. In this architecture, a grid application is the service-oriented grid application in which grid Services are executed according to the workflow of the grid application. This implies that the grid scheduling method needs to consider grid service characteristics. Although many grid scheduling methods have been developed, we need new grid scheduling method to reflect the service-oriented grid concept and to ensure performance of the grid application. Therefore, we propose the grid service performance model based on factors such as service availab.lity, accessibility, reliability, throughput, and slowdown, and develop grid scheduling method to increase performance of the service-oriented grid application. © 2006 IEEE.

关键词： Web services

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A Multi-Dimensional Assessment Model and Its Application in E-learning Courses of Computer Science 20

A Multi-Dimensional Assessment Model and Its Application in ...

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21st Annual Conference of the Special Interest Group in Information Technology Education, SIGITE 2020

作者： Luo, Jiwen Lu, Feng Wang, Tao Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha China 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 Wuhan China

ISBN: (纸本)9781450370455

Computer science is a practical discipline. It is always a great challenge to evaluate students' computer practice using computer-aided means for large scale students. We always need to address problems such as suspected plagiarism and deviation of the overall difficulty factor. In this paper, a multi-dimensional assessment model is designed for CS courses based on the detailed practice processing data in an E-learning system. The model comprehensively evaluates the students' learning process and results in three aspects of correctness, originality, and quality detection. Besides, the teacher can easily participate in the assessment according to their needs. The correctness is an essential requirement, and the originality is based on the clustering results of students' behaviors after clone detection to curb homework plagiarism. SonarQube is used to detect code quality and put forward higher requirements for codes. Manual participation intelligence has improved the flexibility and applicability of the model to a certain extent. We applied this model on the EduCoder online education platform and carried out a comprehensive analysis of 485 students in the Parallel Programming Principles and Practice Class of Huazhong University of Science and Technology. Experiment results confirm the distinction, rationality, and fairness of the model in assessing student performance. It not only gives students a credible, comprehensive score in large-scale online practical programming courses but also gives teachers and students corresponding suggestions based on the evaluation results. Furthermore, the model can be extended to other online education platforms. © 2020 ACM.

关键词： Students

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Dynamic service scheduling for workflow applications in service oriented grid

Dynamic service scheduling for workflow applications in serv...

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3rd International Conference on Semantics, Knowledge, and grid, SKG 2007

作者： Chin, SungHo Lee, JongHyuk Song, SeongJin Song, Byungkwen Yu, HeonChang Distributed and Grid Computing Lab. Department of Computer Science Education Korea University Anam-dong Sungbuk-ku Seoul 136-701 Korea Republic of Dept. of Information and Communication Seokyeong University Korea Republic of

ISBN: (纸本)0769530079

In the Service Oriented grid, a grid application can be composed of diverse grid Services which may be already deployed on grid sites, and dependencies between these grid Services can be described as the workflow graph. Though many grid scheduling methods have been developed, they have been studied based on static heterogeneous computing environment. For this reason, these heuristics cannot be directly applied to grid, which is more dynamic computing environment. Therefore, we develop the dynamic service scheduling method, which support that the workflow applications can be performed effectively in spite of dynamic grid nature. Lastly, we show that our proposed scheduling method outperforms than other conventional scheduling methods through the various experiments. © 2007 IEEE.

关键词： Scheduling

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Kidneygrid: A grid platform for integration of distributed kidney models and resources

KidneyGrid: A grid platform for integration of distributed k...

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4th International Workshop on Middleware for grid computing (MGC'06) held at the ACM/IFIP/USENIX International Middleware Conference

作者： Chu, Xingchen Lonie, Andrew Harris, Peter Thomas, S. Randall Buyya, Rajkumar Grid Computing and Distributed Systems Lab. Dept. of Computer Science and Software Eng. University of Melbourne Australia Department of Information Systems University of Melbourne Australia Unit Faculty of Medicine Dentistry and Health Sciences University of Melbourne Australia FRE 2873 CNRS/Université d'Evry - Val d'Essonnes 91000 Evry France

ISBN: (纸本)1595935819

In this paper, we present a grid computing platform that provides experimental scientists and analysts with access to computational simulations and knowledge databases hosted in separate lab.ratories around the world involved with human and animal kidney research. No single lab.ratory can develop these resources in isolation and the community of users should no longer need to be dependent upon the specific programming environment in which applications have been developed. This is a major innovation in life science and exploits the power of existing and planned high-bandwidth communications networks for collab.rative research and for shared access to knowledge resources. The innovation is developed within a specialist community of renal scientists but will be transferable to any other field of research requiring interaction between published literature and databases, theoretical models and simulations and the formulation of effective experimental design. © 2006 ACM.

关键词： grid computing

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A grid-enabled problem solving environment for in-silico screening in drug discovery

A grid-enabled problem solving environment for in-silico scr...

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5th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2010

作者： Hwang, Soonwook Lee, Sehoon Lee, Sangdo Kim, Jincheol Breton, Vincent Salzemann, Jean Nguyen, Hanh Thi Thanh Kim, Doman Grid and Distributed Computing Lab. Korea Institute of Science and Technology Information 52-11 Eoeun-Dong Deajeon Korea Republic of Laboratoire de Physique Corpuscule CNRS/IN2P3 Campus des Cezeaux 63177 Aubiere Cedex France Line 1 School of Biological Science and Technology Chonnam National University 300 Yongbong-Dong Gwangju Korea Republic of

ISBN: (纸本)9788988678299

WISDOM is an international initiative to deploy large-scale in-silico docking on a public grid infrastructure in an attempt to find potential drugs against neglected or emerging diseases such as Malaria and Avian Flu. Within the framework of the WISDOM initiative, large-scale deployments of in silico docking have been done on production grid infrastructures, demonstrating the relevance of large scale grids for high throughput virtual screening from scientific and grid deployment perspective. However, from the usability point of view, there still seems to be a lot to be done in order to be able to get the gridenabled large-scale virtual screening approach handier for nonexperts of grid computing. To address this issue, we have developed an intuitive and easy-to-use grid-enabled virtual screening tool called Drugscreener-G (DSG), aiming to help scientists in drug discovery including biologists and biochemists to more easily carryout large-scale deployment of molecular docking on grids without having to know details of grid middleware services and tools. With the help of DSG, scientists can easily have access to the PDB database, download and view the 3D structure of target proteins of their interest, launch and manage millions of in-silico docking simulations on the grid. To facilitate the analysis of docking results, visualization and molecular modeling tools such as Jmol and Chimera have been integrated into DSG as well. The DSG client tool is now being used and tested by biologists in Chonnam National University, one of long-time partners of the WISDOM collab.ration. With the help of tools like DSG, their long-time dream of large-scale virtual screening on their own at any time with any help from grid experts is to be made realized in the near future.

关键词： grid computing

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Intersecting-boundary-sensitive fingerprinting for tampering detection of DNN models 24

Intersecting-boundary-sensitive fingerprinting for tampering...

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Proceedings of the 41st International Conference on Machine Learning

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

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 lab.ls. 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 lab.ls. The IBSF code is availab.e at: https://***/CGCL-codes/IBSF.

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Detecting JVM JIT Compiler Bugs via Exploring Two-Dimensional Input Spaces

Detecting JVM JIT Compiler Bugs via Exploring Two-Dimensiona...

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International Conference on Software Engineering (ICSE)

作者： Haoxiang Jia Ming Wen Zifan Xie Xiaochen Guo Rongxin Wu Maolin Sun Kang Chen Hai Jin School of Cyber Science and Engineering Huazhong University of Science and Technology China Hubei Key Laboratory of Distributed System Security Services Computing Technology and System Lab Cluster and Grid Computing Lab. Hubei Engineering Research Center on Big Data Security National Engineering Research Center for Big Data Technology and System School of Informatics Xiamen University China School of Computer Science and Technology Huazhong University of Science and Technology China

Java Virtual Machine (JVM) is the fundamental software system that supports the interpretation and execution of Java bytecode. To support the surging performance demands for the increasingly complex and large-scale Java programs, Just-In-Time (JIT) compiler was proposed to perform sophisticated runtime optimization. However, this inevitably induces various bugs, which are becoming more pervasive over the decades and can often cause significant consequences. To facilitate the design of effective and efficient testing techniques to detect JIT compiler bugs. This study first performs a preliminary study aiming to understand the characteristics of JIT compiler bugs and the corresponding triggering test cases. Inspired by the empirical findings, we propose JOpFuzzer, a new JVM testing approach with a specific focus on JIT compiler bugs. The main novelty of JOpFuzzer is embodied in three aspects. First, besides generating new seeds, JOpFuzzer also searches for diverse configurations along the new dimension of optimization options. Second, JOpFuzzer learns the correlations between various code features and different optimization options to guide the process of seed mutation and option exploration. Third, it leverages the profile data, which can reveal the program execution information, to guide the fuzzing process. Such nov-elties enable JOpFuzzer to effectively and efficiently explore the two-dimensional input spaces. Extensive evaluation shows that JOpFuzzer outperforms the state-of-the-art approaches in terms of the achieved code coverages. More importantly, it has detected 41 bugs in OpenJDK, and 25 of them have already been confirmed or fixed by the corresponding developers.

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Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples

arXiv

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arXiv 2024年

作者： Zhou, Ziqi Li, Minghui Liu, Wei Hu, Shengshan Zhang, Yechao Wan, Wei Xue, Lulu Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab. China Cluster and Grid Computing Lab. China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

With the evolution of self-supervised learning, the pre-training paradigm has emerged as a predominant solution within the deep learning landscape. Model providers furnish pre-trained encoders designed to function as versatile feature extractors, enabling downstream users to harness the benefits of expansive models with minimal effort through fine-tuning. Nevertheless, recent works have exposed a vulnerability in pre-trained encoders, highlighting their susceptibility to downstream-agnostic adversarial examples (DAEs) meticulously crafted by attackers. The lingering question pertains to the feasibility of fortifying the robustness of downstream models against DAEs, particularly in scenarios where the pre-trained encoders are publicly accessible to the attackers. In this paper, we initially delve into existing defensive mechanisms against adversarial examples within the pre-training paradigm. Our findings reveal that the failure of current defenses stems from the domain shift between pre-training data and downstream tasks, as well as the sensitivity of encoder parameters. In response to these challenges, we propose Genetic Evolution-Nurtured Adversarial Fine-tuning (Gen-AF), a two-stage adversarial fine-tuning approach aimed at enhancing the robustness of downstream models. Gen-AF employs a genetic-directed dual-track adversarial fine-tuning strategy in its first stage to effectively inherit the pre-trained encoder. This involves optimizing the pre-trained encoder and classifier separately while incorporating genetic regularization to preserve the model’s topology. In the second stage, Gen-AF assesses the robust sensitivity of each layer and creates a dictionary, based on which the top-k robust redundant layers are selected with the remaining layers held fixed. Upon this foundation, we conduct evolutionary adaptability fine-tuning to further enhance the model’s generalizability. Our extensive experiments, conducted across ten self-supervised training methods and six

关键词： Topology

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