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International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Haibo Mi Huaimin Wang Gang Yin Hua Cai Qi Zhou Tingtao Sun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Company Hangzhou China

It is quite a headache for developers to online detect performance problems in large-scale cloud computing systems. The behavior and the hidden connections among the huge amount of runtime request execution paths in cloud computing systems usually contain useful information for performance problem detection. In this paper, we propose an approach to rapidly diagnose the source of performance degradation in large-scale non-stop cloud computing systems. The approach first groups the user requests into categories with a fast clustering algorithm; then applies the principal components analysis to extract the primary methods; finally compares the normal and abnormal behaviors of the primary methods to localize the main cause of performance problems. We conduct extensive experiments over a real-world enterprise system providing services for the public. The results show that our approach can locate the prime causes of performance problems accurately and efficiently.

关键词： Cloud computing Principal component analysis Instruments Degradation Servers Data mining Accuracy

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Ruan Jian Xue Bao/Journal of Software 2011年第1期22卷 132-148页

作者： Li, Hui-Ba Tian, Tian Peng, Yu-Xing Li, Dong-Sheng Lu, Xi-Cheng National Laboratory for Parallel and Distributed Computing Computer School National University of Defense Technology Changsha 410073 China Institute of Software Computer School National University of Defense Technology Changsha 410073 China

The Internet has become a vital information infrastructure for modern society. However, the concurrent nature of network introduces a wide-range of difficulties in traditional programming methodology in developing high-quality network programs that significantly reduce productivity. The influence of concurrency on the complexity of software development is comparable to the "concurrency crisis" of software brought by multi-core processors, but it receives much less attention here than what it deserves. There is no universal approach to cope with this issue, and there are even disagreements between different approaches. In this paper, the basic concurrency models and their implementations are introduced, and then the paper surveys the inherent complexities of these approaches, comparing their advantages and disadvantages. Finally, this paper offers an opinion on the possibilities for future research on this topic. © Copyright 2011, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Complex networks

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Identifying faults in large-scale distributed systems by filtering noisy error logs

Identifying faults in large-scale distributed systems by fil...

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International Conference on Dependable Systems and Networks Workshops (DSN-W)

作者： Xiang Rao Huaimin Wang Dianxi Shi Zhenbang Chen Hua Cai Qi Zhou Tingtao Sun National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Corporation Hangzhou China

Extracting fault features with the error logs of fault injection tests has been widely studied in the area of large scale distributed systems for decades. However, the process of extracting features is severely affected by a large amount of noisy logs. While the existing work tries to solve the problem by compressing logs in temporal and spatial views or removing the semantic redundancy between logs, they fail to consider the co-existence of other noisy faults that generate error logs instead of injected faults, for example, random hardware faults, unexpected bugs of softwares, system configuration faults or the error rank of a log severity. During a fault feature extraction process, those noisy faults generate error logs that are not related to a target fault, and will strongly mislead the resulted fault features. We call an error log that is not related to a target fault a noisy error log. To filter out noisy error logs, we present a similarity-based error log filtering method SBF, which consists of three integrated steps: (1) model error logs into time series and use haar wavelet transform to get the approximate time series; (2) divide the approximate time series into sub time series by valleys; (3) identify noisy error logs by comparing the similarity between the sub time series of target error logs and the template of noisy error logs. We apply our log filtering method in an enterprise cloud system and show its effectiveness. Compared with the existing work, we successfully filter out noisy error logs and increase the precision and the recall rate of fault feature extraction.

关键词： Time series analysis Noise measurement Feature extraction Wavelet transforms Computer crashes Complexity theory Approximation methods

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Hierarchical diagnostic approach for performance problems in cloud computing platforms

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Tongxin Xuebao/Journal on Communications 2011年第7期32卷 114-124页

作者： Mi, Hai-Bo Wang, Huai-Min Cai, Hua Yin, Gang Zhou, Qi Sun, Ting-Tao Zhou, Yang-Fan National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Computing Platform Alibaba Cloud Computing Company Hangzhou 310023 China Shenzhen Research Institute Chinese Univ. of Hong Kong Shenzhen 518057 China

A hierarchical diagnosis approach, namely Magnifier, was proposed, which models the execution path graph of a user request as component layer, module layer and function layer, and detects anomalies from higher layer to lower layer separately. Extensive experiments were conducted on the Alibaba cloud computing platform. The results indicate that, under the conditions of large volume of data and high complexity of execution paths, Magnifier can accurately and efficiently locate the prime causes of performance degradation.

关键词： Cloud computing

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Network and service management and diagnostics solution of a remote patient monitoring system

Network and service management and diagnostics solution of a...

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International Symposium on Logistics and Industrial Informatics, LINDI

作者： Miklos Kozlovszky Zsolt Meixner Gergely Windisch Judit Márton Sándor Ács Pál Bogdanov Anikó Boruzs Péter Kotcauer János Ferenczi Viktor Kozlovszky Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Budapest Hungary

We have developed a combined network and service management and diagnostics solution for our in-house developed remote patient monitoring system. The developed system has included into the ALPHA eHealth/remote patient monitoring system and was successfully used in our large Living Lab infrastructure operating in three different Hungarian regions with 40 patients. In this paper we will identify the key elements of the combined Network and Service Management solution of the remote patient monitoring system.

关键词： Sensors Biomedical monitoring Medical diagnostic imaging Software Patient monitoring Educational institutions

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GPGPU-based data parallel region growing algorithm for cell nuclei detection

GPGPU-based data parallel region growing algorithm for cell ...

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International Symposium on Computational Intelligence and Informatics

作者： Sándor Szénási Zoltán Vámossy Miklós Kozlovszky John von Neumann Faculty of Informatics Óbuda University Budapest Hungary Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary

Nowadays microscopic analysis of tissue samples is done more and more by using digital imagery and special immunodiagnostic software. These are typically specific applications developed for one distinct field, but some subroutines are commonly repeated, for example several applications contain steps that can detect cell nuclei in a sample image. The aim of our research is developing a new data parallel algorithm that can be implemented even in a GPGPU environment and that is capable of counting hematoxylin eosin (HE) stained cell nuclei and of identifying their exact locations and sizes (using a variation of the region growing method). Our presentation contains the detailed description of the algorithm, the peculiarity of the CUDA implementation, and the evaluation of the created application (regarding its accuracy and the decrease in the execution time).

关键词： Graphics processing unit Kernel Instruction sets Computer architecture Algorithm design and analysis Microprocessors Synchronization

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An Intelligent Broker Approach to Semantics-Based Service Composition

An Intelligent Broker Approach to Semantics-Based Service Co...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Yufeng Zhang Hong Zhu National Laboratory for Parallel and Distributed Processing Department of Computing Science National University of Defense Technology Changsha China Department of Computing and Electronics Oxford Brookes University Oxford UK

This paper proposes an intelligent broker approach to service composition and collaboration. The broker employs a planner to generate service composition plans according to service usage and workflow knowledge, dynamically searches for services according to the plan, then invokes and coordinates the executions of the selected services at runtime. A prototype called I-Broker has been implemented to support the approach, which can be instantiated by populating the knowledge-base with domain specific knowledge to form domain specific brokers. This paper also reports experiments that evaluate the scalability of the approach.

关键词： Knowledge based systems Ontologies Semantics Complexity theory Planning Scalability Prototypes

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An energy-efficient scheduling algorithm for sporadic real-time tasks in multiprocessor systems

An energy-efficient scheduling algorithm for sporadic real-t...

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13th IEEE International Workshop on FTDCS 2011, the 8th International Conference on ATC 2011, the 8th International Conference on UIC 2011 and the 13th IEEE International Conference on HPCC 2011

作者： Zhang, Dong-Song Chen, Fang-Yuan Li, Hong-Hua Jin, Shi-Yao Guo, De-Ke National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China School of Computing Science Simon Fraser University 8888 University Drive Burnaby BC V5A 1S6 Canada National Laboratory for Information System Engineering School of Information Systems and Management National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9780769545387

As the energy consumption of embedded multiprocessor systems becomes increasingly prominent, the real-time energy-efficient scheduling in multiprocessor systems becomes an urgent problem to reduce the system energy consumption while meeting real-time constraints. For a multiprocessor with independent DVFS and DPM at each processor, this paper proposes an energy-efficient real-time scheduling algorithm named LRE-DVFS-EACH, based on LRE-TL which is an optimal real-time scheduling algorithm for sporadic tasks. LRE-DVFS-EACH utilizes the concept of TL plane and the idea of fluid scheduling to dynamically scale the voltage and frequency of processors at the initial time of each TL plane as well as the release time of a sporadic task in each TL plane. Consequently, LRE-DVFS-EACH can obtain a reasonable tradeoff between the real-time constraints and the energy saving. LRE-DVFS-EACH is also adaptive to the change of workload caused by the dynamic release of sporadic tasks, which can obtain more energy savings. The experimental results show that compared with existing algorithms, LRE-DVFS-EACH can not only guarantee the optimal feasibility of sporadic tasks, but also achieve more energy savings in all cases, especially in the case of high workloads. © 2011 IEEE.

关键词： Real time systems

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Biomedical image processing with GPGPU using CUDA

Biomedical image processing with GPGPU using CUDA

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Proceedings of the International Convention MIPRO

作者： A. R. Firstauthor I. B. Secondauthor G. V. Thirdauthor P. B. Fourthauthor M. K. Fifthauthor Óbuda University/John von Neumann Faculty of Informatics Budapest Hungary Semmelweiss University/Znd Department of Internal Medicine Budapest Hungary MTA SZTAKI/Laboratory of Parallel and Distributed Computing Budapest Hungary

The main aim of this work is to show, how the GPGPUs can be used to speed up certain image processing methods. The algorithm explained in this paper is used to detect nuclei on (HE - hematoxilin eosin) stained colon tissue sample images, and includes a Gauss blurring, an RGB-HSV color space conversion, a fixed binarization, an ultimate erode procedure and a local maximum search. Since the images retrieved from the digital slides require significant storage space (up to few hundred megapixels), the usage of GPGPUs to speed up image processing operations is necessary in the interest of achieving reasonable processing time. The CUDA software development kit was used to develop algorithms to GPUs made by NVIDIA. This work focuses on how to achieve coalesced global memory access when working with three-channel RGB images, and how to use the on-die shared memory efficiently. The exact test algorithm also included a linear connected component labeling, which was running on the CPU, and with iterative optimization of the GPU code, we managed to achieve significant speed up in well defined test environment.

关键词： Graphics processing unit Instruction sets Image processing Kernel Optimization Memory management Pixel

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parallel biomedical image processing with GPGPUs in cancer research

Parallel biomedical image processing with GPGPUs in cancer r...

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International Symposium on Logistics and Industrial Informatics, LINDI

作者： Attila Reményi Sándor Szénási István Bándi Zoltán Vámossy Gábor Valcz Pál Bogdanov Szabolcs Sergyán Miklos Kozlovszky John von Neumann Faculty of Informatics Óbuda University Budapest Hungary 2nd Department of Internal Medicine Semmelweiss University Budapest Hungary Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary

The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) stained colon tissue sample images. Since pathologists are working with large number of high resolution images - thus require significant storage space -, one feasible way to achieve reasonable processing time is the usage of GPGPUs. The CUDA software development kit was used to develop processing algorithms to NVIDIA type GPUs. Our work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently.

关键词： Graphics processing unit Instruction sets Image processing Memory management Optimization Kernel Colon

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