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Workshop on Proactive Failure Avoidance, Recovery, and Maintenance

作者： Rao, Xiang Wang, Huaimin Shi, Dianxi Chen, Zhenbang Cai, Hua Zhou, Qi Sun, Tingtao National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Computing Platform Alibaba Cloud Computing Corporation Hangzhou China

ISBN: (纸本)9781457703751

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.1 © 2011 IEEE.

关键词： Errors

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A construction technique of constant degree P2P systems towards efficient complex queries

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2011年第3期48卷 374-381页

作者： Wang, Xiaohai Peng, Yuxing Li, Dongsheng Key Laboratory of Science and Technology for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China

Constant degree peer-to-peer (P2P) system is turning into the P2P domain's promising hotspot due to constant degree digraphs having good propertis. However, it is often hard to convert a stardard constant degree digraph to a DHT schema. Thus, most researches focus on DHT's construction and maintenance, while leaving optimization and supporting to complex query behind. Underlying topology affects upper-layers' character a lot. For constant degree P2P topologies, their inherent property makes a constant degree P2P system built using classical technique be poor in the data locality, and unfit for efficient, low-cost complex queries. Aiming at this shortage, a general-purpose construction technique towards efficient complex queries is proposed, which adds an embedding transformation layer between data layer and DHT overlay. In this way, adjacent data are stored in overlay's adjacent peers and the data locality is improved, so that the number of peers referred in complex queries can be minimized with a limited time overhead. To validate this technology, the first constant degree P2P system based on Kautz digraph FissionE is reconstructed as a typical example, which includes re-allocating of resources, query algorithm and locality maintenance strategies. Experimental results show that this construction technique can ensure data locality, reduce query cost and lead to systems' efficiency without changing the underlying DHT layer.

关键词： Peer to peer networks

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An efficient two-level bitmap index for cloud data management

An efficient two-level bitmap index for cloud data managemen...

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2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011

作者： Bin, Huang Yu-Xing, Peng School of Computer Science Wuhan University Wuhan China National Laboratory of Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9781612844855

A Cloud may be seen as a type of flexible computing infrastructure consisting of many compute nodes, where resizable computing capacities can be provided to different customers. To fully harness the power of the Cloud, efficient data management is needed to handle huge volumes of data and support a large number of concurrent end users. To achieve that, a scalable and high-throughput indexing scheme is generally required. Such an indexing scheme must support parallel search to improve scalability. In this paper, we present a bitmap based indexing scheme for efficient data processing in the Cloud. Our approach can be summarized as follows. First, we build a local bitmap index for each compute node which only indexes data residing on the node. Second, we organize the compute nodes as a structured overlay and each node maintains a portion of the global index for the whole different data. The global index is also bitmap index to indicate the node each data resides in. Third, all bitmaps are compressed by adopting run-length coding for reducing storage requirement. We conduct extensive experiments on a LAN, and the results demonstrate that our indexing scheme is dynamic, efficient and scalable. © 2011 IEEE.

关键词： Information management

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Information recycling for social creativity

Information recycling for social creativity

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2011 3rd International Conference on Awareness Science and Technology, iCAST 2011

作者： Wu, Yilang Watanabe, Takanobu Distributed Parallel Processing Laboratory University of Aizu Aizu-wakamatsu 965-8580 Japan University Business Innovation Center University of Aizu Aizu-wakamatsu 965-8580 Japan

ISBN: (纸本)9781457708879

Social brainstorming has become a popular group creativity technique to create a large number of ideas for solving problems. The social computing, for its advance in information processing and network communication, collaborates the social intelligence and enhances the social creativity in brainstorming. However, facing the dilemma of quantity deficiency in idea pondering or quality submergence in idea deluge, cooperative participants essentially require needed information for their innovative work rather than unnecessary disturbance. Therefore, in purpose of enhancing the social creativity, we propose the needed information recycling based on multi-features in meta-data and also the similarity in social graph, helping participants keep a global and local image of previous work and focus on innovation tasks. Given an experimental demo, we discuss the essential merits of the novel brainstorming through the comprehensive but collaborative inter-merge of the social network and computer network, and conclude that the needed information recycling breeds the efficient and effective social creativity. © 2011 IEEE.

关键词： Image enhancement

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Speeding up Data Distribution of Bit Torrent-Like P2P Systems

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2011 International Conference on Advanced Materials and Information Technology processing(AMITP 2011)

作者： Jiqing Wu Yuxing Peng National Laboratory for Parallel and Distributed Processing National University of Defense Technology

ISBN: (纸本)9783037851555

Data distribution is the basic behavior of P2 P applications(file sharing and streaming service) and it is a key element affecting the performance of P2 P systems. However, there are few research works that focus on data distribution of P2 P applications from the view of whole system. In this paper we study the data distribution in P2 P applications in terms of decreasing the system distribution load. We define the distribution load of P2 P systems formally and analyze how to decrease the system load quickly by means of mathematical analysis. Moreover, we give a feasible fast distribution algorithm according to our theoretic conclusion. The experimental results show that our algorithm has significant improvement on data distribution speed and load balance.

关键词： data distribution P2P distribution load bittorrent-like

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Efficient approach for repeated patterns mining based on indent shape of HTML documents

Efficient approach for repeated patterns mining based on ind...

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3rd International Conference on Cyber-Enabled distributed Computing and Knowledge Discovery, CyberC 2011

作者： Zhu, Yanxu Yin, Gang Wang, Huaimin Shi, Dianxi Rao, Xiang Yuan, Lin School of Computer National Laboratory for Parallel and Distributed Processing National University of Defense Technology 410073 Changsha Hunan China College of Electronic Technology Information Engineering University 450004 Zhengzhou Henan China

ISBN: (纸本)9780769545578

Mining of repeated patterns from HTML documents is the key step towards Web-based data mining and knowledge extraction. Many web crawling applications need efficient repeated patterns mining techniques to generate their wrapper automatically. Existing approaches such as tree matching and string matching can detect repeated patterns with high precision, but their performance is still a challenge for practical web crawling applications. In this paper, we propose an efficient approach for mining repeated patterns based on indent shape of HTML document. Indent shape is a novel and simple model of HTML document, in which tandem repeated waves have strong association with the repeated patterns to be detected. By scanning an indent shape with a horizontal indent-line from bottom to top, the tandem repeated waves are identified by filtering the wave segments with low self-similarities. After that the boundary of HTML code corresponding to repeated patterns can be identified, which could be transformed to regular expressions formal-defined easily. Extensive experiments on two practical data sets retrieved from Internet show that our approach achieves high efficiency significantly, and its precision performance is also generally better than the existing approaches. © 2011 IEEE.

关键词： HTML

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A wikipedia based semantic graph model for topic tracking in blogosphere

A wikipedia based semantic graph model for topic tracking in...

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22nd International Joint Conference on Artificial Intelligence, IJCAI 2011

作者： Tang, Jintao Wang, Ting Lu, Qin Wang, Ji Li, Wenjie College of Computer National University of Defense Technology Changsha China Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong National Laboratory for Parallel and Distributed Processing Changsha China

ISBN: (纸本)9781577355120

There are two key issues for information diffusion in blogosphere: (1) blog posts are usually short, noisy and contain multiple themes, (2) information diffusion through blogosphere is primarily driven by the "word-of- mouth" effect, thus making topics evolve very fast. This paper presents a novel topic tracking approach to deal with these issues by modeling a topic as a semantic graph, in which the semantic relatedness between terms are learned from Wikipedia. For a given topic/post, the name entities, Wikipedia concepts, and the semantic relatedness are extracted to generate the graph model. Noises are filtered out through the graph clustering algorithm. To handle topic evolution, the topic model is enriched by using Wikipedia as background knowledge. Furthermore, graph edit distance is used to measure the similarity between a topic and its posts. The proposed method is tested by using the real-world blog data. Experimental results show the advantage of the proposed method on tracking the topic in short, noisy texts.

关键词： Blogs

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Toward optimal deployment of communication-intensive cloud applications

Toward optimal deployment of communication-intensive cloud a...

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International Conference on Cloud Computing

作者： Fan, Pei Wang, Ji Zheng, Zibin Lyu, Michael R. National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Dept. of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9780769544601

Strongly promoted by the leading industrial companies, cloud computing becomes increasingly popular in recent years. The growth rate of cloud computing surpasses even the most optimistic predictions. A cloud application is a large-scale distributed system that consist a lot of distributed cloud nodes. How to make optimal deployment of cloud applications is a challenging research problem. When deploying a cloud application to the cloud environment, cloud node ranking is one of the most important approaches for selecting optimal cloud nodes for the cloud application. Traditional ranking methods usually rank the cloud nodes based on their QoS values, without considering the communication performance between cloud nodes. However, such kind of node relationship is very important for the communication-intensive cloud applications (e.g., Message Passing Interface (MPI) programs), which have a lot of communications between the selected cloud nodes. In this paper, we propose a novel clustering-based method for selecting optimal cloud nodes for deploying communication-intensive applications to the cloud environment. Our method not only takes into account the cloud node qualities, but also the communication performance between different nodes. We deploy several well-known MPI programs on a real-world cloud and compare our method with other methods. The experimental results show the effectiveness of our cluster-based method. © 2011 IEEE.

关键词： Quality of service

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Using complex network features for fast clustering in the web 11

Using complex network features for fast clustering in the we...

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Proceedings of the 20th international conference companion on World wide web

作者： Tang, Jintao Wang, Ting Wang, Ji Lu, Qin Li, Wenjie School of Computer National University of Defense Technology Changsha China Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong National Laboratory for Parallel and Distributed Processing Changsha China

ISBN: (纸本)9781450305181

Applying graph clustering algorithms in real world networks needs to overcome two main challenges: the lack of prior knowledge and the scalability issue. This paper proposes a novel method based on the topological features of complex networks to optimize the clustering algorithms in real-world networks. More specifically, the features are used for parameter estimation and performance optimization. The proposed method is evaluated on real-world networks extracted from the web. Experimental results show improvement both in terms of Adjusted Rand index values as well as runtime efficiency. © 2011 Authors.

关键词： Parameter estimation

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Communication-Aware Task Partition and Voltage Scaling for Energy Minimization on Heterogeneous parallel Systems

Communication-Aware Task Partition and Voltage Scaling for E...

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IEEE International Conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Guibin Wang Wei Song National Laboratory for Parallel and Distributed Processing National University of Defense Technology China

Heterogeneous parallel systems have become popular in general purpose computing and even high performance computing fields. There are many studies focused on harnessing heterogeneous parallel processing for better performance. However the energy optimization for heterogeneous system has not been well studied. Owing to the differences in performance and energy consumption, the energy optimization technique for heterogeneous system is different from the existing methods designed for homogeneous system. Besides typical voltage scaling method, reasonable task partitioning is also an essential method for optimizing energy consumption on heterogeneous systems. Through partitioning a data parallel task and mapping sub-tasks onto several processors, one could achieve better performance and reduced energy consumption. As the computation cost reduces with specific accelerators, the communication overhead becomes more prominent. Therefore, the task partition optimization should holistically consider the computation improvement and communication overhead to achieve higher energy efficiency. Typically, task partition and voltage scaling are not orthogonal and influence the effect of each other in the energy optimization problem. In order to harness both two knobs efficiently, this paper proposes an integer linear programming (ILP) based energy-optimal solution designed for heterogeneous system. We present a case study of optimizing MGRID benchmark on a typical CPU-GPU heterogeneous system. The experimental results demonstrate that the proposed method could exploit the heterogeneity in different processors and achieve improved energy efficiency.

关键词： Graphics processing unit Energy consumption Power demand Optimization Kernel Schedules

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