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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Qijun Liu Zhenghua Wang Hanchang Sun Hao Guo Wanlin Liu Yunping Zhu National Laboratory of Parallel & Distributed Processing National University of Defence Technology Changsha China State Key Laboratory of Proteomics Beijing Proteome Research Center Beijing Institute of Radiation Medicine Beijing China

To conduct a systemic analysis of biological networks function distribution and function modules, we present a semiautomatic method to achieve independent and intact GO slim (InitGO) based on graph operations and GO hierarchy structure. Our method is packed into a user-friendly Cytoscape plugin named InitGO. The application of InitGO to yeast transcriptional factors regulatory network shows that the network has function modularity, offering evidence that our method is effective for defining function modules. InitGO plugin and source codes are available on request from the authors.

关键词： Ontologies Biological information theory Independent component analysis Fungi Data visualization Systems biology Bioinformatics Laboratories distributed processing Transfer functions

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Revealing the functional modularity of yeast transcriptional regulatory network by using a novel topological measurement

Revealing the functional modularity of yeast transcriptional...

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International Conference on Computer Science and Information Technology (CSIT)

作者： Qijun Liu Zhenghua Wang Mansheng Li Dong Li Yunping Zhu National Laboratory of Parallel & Distributed Processing National University of Defence Technology Changsha China State Key Laboratory of Proteomics Beijing Proteomics Research Center Beijing Institute of Radiation Medicine Beijing China

It has been reported that function implementations in biological systems, including transcriptional regulatory networks (TRN), show modular architecture. Analyzing functional modularity of biological networks can describe characteristics of function implementation and their "position" in biology systems from the systems perspective. Defining functional modules naturally, we bring up a novel measurement, cohesive degree (CD), to characterize the modularity. From this character, we know that not all of the corresponding modules of function annotations take on good modularity. Considering the ratio of the non-cohesive (zero-CD value) modules, TRN's functional modularity is also weaker than that of other biological network and integral ones. And, this is not caused by data integrity, but by the topology of itself. In fact, the modularity implementation of biological systems is mainly accomplished through the cooperation of several types of networks, not by TRN alonely.

关键词： Fungi Biochemistry Biological systems Proteins Gene expression Laboratories Electronic mail Proteomics Network topology Systems biology

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An Efficient Label Routing on High-Radix Interconnection Networks

An Efficient Label Routing on High-Radix Interconnection Net...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Fei Lei Dezun Dong Xiangke Liao College of Computer National University of Defense Technology China National Laboratory for Parallel and Distributed Processing National University of Defense Technology China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China

ISBN: (纸本)9781538632086

Cost-effective adaptive routing has a significant impact on overall performance for high-radix hierarchical topologies, such as Dragonfly, which achieve a lower network diameter than traditional topologies, Torus and Fat tree, but exhibit a lower degree of adaptiveness for shortest-path rout- ing. Existing adaptive routing methods for those hierarchical topologies improve the adaptiveness by increasing path length, i.e. local or global adaptive routing, and thus suffer from complex and costly deadlock avoidance. This work aims to maximize the routing adaptiveness at the minimum cost of deadlock avoidance. We propose a label routing method for high-radix hierarchical networks. This label routing utilizes a co-design methodology and coordinates the two pipelines, input queue and routing computation, in the router microarchitec- ture. Packets in the input buffer are labeled by our routing algorithm depending on network states. We reorganize the input buffer and develop a label routing algorithm, named Green-Red Routing, GRR. GRR relaxes the requirement of using virtual channels to eliminate routing deadlock, and mitigates buffer resources dedicated to deadlock avoidance. GRR manages the buffer resources and balance its utilization elaborately, and achieve fully adaptive routing efficiently. We conduct extensive experiments to evaluate the performance of GRR on Dragonfly and compare it with state-of-the-art works. The results show that GRR achieves 10%-35% higher performance than existing routing algorithms under most traffic patterns.

关键词： Routing System recovery Network topology Topology Resource management Adaptive systems Organizations

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RoSAS: Deep Semi-supervised Anomaly Detection with Contamination-resilient Continuous Supervision

arXiv

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arXiv 2023年

作者： Xu, Hongzuo Wang, Yijie Pang, Guansong Jian, Songlei Liu, Ning Wang, Yongjun National Key Laboratory of Parallel and Distributed Computing China College of Computer National University of Defense Technology Hunan Changsha410073 China School of Computing and Information Systems Singapore Management University Singapore178902 Singapore College of Information and Communications National University of Defense Technology Hubei Wuhan430010 China

Semi-supervised anomaly detection methods leverage a few anomaly examples to yield drastically improved performance compared to unsupervised models. However, they still suffer from two limitations: 1) unlabeled anomalies (i.e., anomaly contamination) may mislead the learning process when all the unlabeled data are employed as inliers for model training;2) only discrete supervision information (such as binary or ordinal data labels) is exploited, which leads to suboptimal learning of anomaly scores that essentially take on a continuous distribution. Therefore, this paper proposes a novel semi-supervised anomaly detection method, which devises contamination-resilient continuous supervisory signals. Specifically, we propose a mass interpolation method to diffuse the abnormality of labeled anomalies, thereby creating new data samples labeled with continuous abnormal degrees. Meanwhile, the contaminated area can be covered by new data samples generated via combinations of data with correct labels. A feature learning-based objective is added to serve as an optimization constraint to regularize the network and further enhance the robustness w.r.t. anomaly contamination. Extensive experiments on 11 real-world datasets show that our approach significantly outperforms state-of-the-art competitors by 20%-30% in AUC-PR and obtains more robust and superior performance in settings with different anomaly contamination levels and varying numbers of labeled anomalies. The source code is available at https://***/xuhongzuo/rosas/. © 2023, CC BY.

关键词： Contamination

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Direct method-green's theory: From PDE to BIE in the geometric transformation

Direct method-green's theory: From PDE to BIE in the geometr...

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Li-Na Yang Tao-Shen Li Yuan Yan Tang Jia Xu Jian-Jia Pan Hui-Wu Luo Xian-Wei Zheng Electronics and Information Guangxi University Nanning China Department of Computer and Information Science University of Macau Macau Guangxi Colleges and Universities Key Laboratory of Parallel and Distributed Computing Nanning China

ISBN: (纸本)9781509029181

In this research, we apply the Green's theory for converting the partial differential equation to the boundary integral equation for geometric transformation. Green's theory is designed specifically for integral equation. It is efficient in detecting the singularity point to the geometric transformation that has been verified. Experimental results show that the Green's theory has good performance.

关键词： Mathematical model Integral equations Pattern recognition Image restoration Wavelet analysis Partial differential equations Boundary conditions

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Bi-Objective Scheduling Algorithm for Hybrid Workflow in JointCloud

Bi-Objective Scheduling Algorithm for Hybrid Workflow in Joi...

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IEEE International Conference on Joint Cloud computing (JCC)

作者： Rui Li Huaimin Wang Peichang Shi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China State Key Laboratory of Complex & Critica Software Environment College of Computer Science National University of Defense Technology Changsha China

ISBN: (数字)9798350387339

ISBN: (纸本)9798350387346

Big data workflows are widely used in IoT, recommended systems, and real-time vision applications, and they continue to grow in complexity. These hybrid workflows consist of both resource-intensive batch jobs and latency-sensitive stream jobs. Examples include the data analytics workflow, which incorporates batch data transformations and low-latency querying, and the machine learning workflow, which processes stream data feature extraction before performing batch training and low-latency inference. However, existing research on workflow scheduling primarily focuses on either stream or batch workflows, neglecting the efficient scheduling of hybrid workflows that respect their diverse resource requirements and the costly data transfers between *** this article, we propose a hybrid workflow model that defines the optimal placement of hybrid workflows (OHWP) as a bi-objective optimization problem. Our proposed model takes into account parameters related to inter-communication between stream and batch jobs, as well as the heterogeneous resources in JointCloud environment. Additionally, we present OHWP-PS (OHWP on a Pruned Space), a scheduling algorithm for hybrid workflows that minimizes both cost and latency by improving the initial population and dynamically updating the search space. The results demonstrate that the proposed OHWP-PS algorithm is effective and competitive across all experiments.

关键词： Training Scheduling algorithms Machine vision Heuristic algorithms Machine learning Feature extraction Remote working

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A data-driven mechanism for large-scale data distribution

A data-driven mechanism for large-scale data distribution

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Proceedings of the Biannual World Automation Congress

作者： Peichang Shi Yiying Li Bo Ding Longquan Jiang Hui Liu Jie Zhang National Key Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha Hunan CN National Key Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 China National University of Defense Technology Changsha Hunan CN China Electr. Equip. & Syst. Eng. Co. Ltd. China

As The integration of Physical space and cyberspace, the large-scale data distributing to diversification terminal which is geographical distribution of mass has become a huge challenge. When the data size can't be processed by the technology for traditional scope, how to deal with the user quality of service and efficient use of system resources has become an important issue of concern, with the resources becoming limited. This paper presents a data-driven mechanism for large-scale data distribution which is consists of four core part of the data production, data collection and pre-processing, data analysis engine, data consumption, aims to excavate the valuable information to improve the efficiency of resource use and accurate fault location for the Large-scale data distribution system. At the same time, this paper studies the resource scheduling optimization with analyzing data driven for the system behavior and Fault location with analyzing data-driven environment, which proves the effectiveness for the operation of the Large-scale data distribution system optimization by the data-driven working.

关键词： Servers Monitoring distributed databases Big data Real-time systems Business

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Toward Wisdom-Evolutionary and Primitive-Concise 6G:A New Paradigm of Semantic Communication Networks

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Engineering 2022年第1期8卷 60-73页

作者： Ping Zhang Wenjun Xu Hui Gao Kai Niu Xiaodong Xu Xiaoqi Qin Caixia Yuan Zhijin Qin Haitao Zhao Jibo Wei Fangwei Zhang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Peng Cheng Laboratory Shenzhen 518066China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China The School of Electronic Engineering and Computer Science Queen Mary University of LondonLondon E14NSUK College of Electronic Science and Technology National University of Defense TechnologyChangsha 410073China School of Humanities Beijing University of Posts and TelecommunicationsBeijing 100876China

The sixth generation(6G)mobile networks will reshape the world by offering instant,efficient,and intelligent hyper-connectivity,as envisioned by the previously proposed Ubiquitous-X 6G *** hyper-massive and global connectivity will introduce tremendous challenges into the operation and management of 6G networks,calling for revolutionary theories and technological *** this end,we propose a new route to boost network capabilities toward a wisdom-evolutionary and primitive-concise network(WePCN)vision for the Ubiquitous-X 6G *** particular,we aim to concretize the evolution path toward the WePCN by first conceiving a new semantic representation framework,namely semantic base,and then establishing an intelligent and efficient semantic communication(IE-SC)network *** the IE-SC architecture,a semantic intelligence plane is employed to interconnect the semantic-empowered physical-bearing layer,network protocol layer,and application-intent layer via semantic information *** proposed architecture integrates artificial intelligence and network technologies to enable intelligent interactions among various communication objects in *** features a lower bandwidth requirement,less redundancy,and more accurate intent *** also present a brief review of recent advances in semantic communications and highlight potential use cases,complemented by a range of open challenges for 6G.

关键词： 6G Semantic information Semantic communication Intelligent communication

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Teracluster LSSC-II--Its designing principles and applications in large scale numerical simulations

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中国科学A辑（英文版） 2004年第z1期47卷 53-68页

作者： Zhang Linbo Chen Shiyi LI Xinliang CAO Jianwen ZHANG Wensheng GONG Xingao State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing 100080 China Department of Mechanical Engineering The Johns Hopkins University and Center for Computational Science and Engineering Peking University Beijing 100875 China Institute of Mechanics Chinese Academy of SciencesBeijing 100080 China Parallel Computing Laboratory Institute of Software Chinese Academy of Sciences Beijing 100080 China Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing 100080 China Surface Physics Laboratory National Key Laboratory Fudan University Shanghai 200433 Institute of Solid State Physics Chinese Academy of Sciences Hefei 230031 China

The teracluster LSSC-II installed at the State key laboratory of Scientific and Engineering computing, Chinese Academy of Sciences is one of the most powerful PC clusters in China. It has a peek performance of 2Tflops. With a Linpack performance of 1.04Tflops, it is ranked at the 43rd place in the 20th TOP500 List (November 2002), 51st place in the 21st TOP500 List (June 2003), and the 82nd place in the 22nd TOP500 List (November 2003) with a new Linpack performance of 1.3Tflops. In this paper, we present some design principles of this cluster, as well as its applications in some large-scale numerical simulations.

关键词： high performance computing PC cluster large scale numerical simulations

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Secure Live Migration of SGX Enclaves on Untrusted Cloud

Secure Live Migration of SGX Enclaves on Untrusted Cloud

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International Conference on Dependable Systems and Networks (DSN)

作者： Jinyu Gu Zhichao Hua Yubin Xia Haibo Chen Binyu Zang Haibing Guan Jinming Li Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Institute of Parallel and Distributed Systems (IPADS) Shanghai Jiao Tong University Huawei Technologies Inc.

ISBN: (纸本)9781538605431

The recent commercial availability of Intel SGX (Software Guard eXtensions) provides a hardware-enabled building block for secure execution of software modules in an untrusted cloud. As an untrusted hypervisor/OS has no access to an enclave's running states, a VM (virtual machine) with enclaves running inside loses the capability of live migration, a key feature of VMs in the cloud. This paper presents the first study on the support for live migration of SGX-capable VMs. We identify the security properties that a secure enclave migration process should meet and propose a software-based solution. We leverage several techniques such as two-phase checkpointing and self-destroy to implement our design on a real SGX machine. Security analysis confirms the security of our proposed design and performance evaluation shows that it incurs negligible performance overhead. Besides, we give suggestions on the future hardware design for supporting transparent enclave migration.

关键词： Program processors Hardware Security Virtual machine monitors Cloud computing Context

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