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1st International Workshop on Crowd-Based Software Development Methods and Technologies, CrowdSoft 2014

作者： Yang, Cheng Wang, Tao Yin, Gang Wang, Huaimin Wu, Ming Xiao, Ming Key Lab. of Parallel and Distributed Computing Colledge of Computer National University of Defence Technology ChangSha Hunan China

ISBN: (纸本)9781450332248

With the dramatic growing of mobile application markets, users can find apps with any function they desire in these markets. However, the huge amounts of apps make it quite a challenge for users to discover good applications efficiently. Previous studies recommend applications based on the download history, user ratings or app usage records. Most of these studies fail to capture users' personal interests in mobile applications precisely. In this paper, we leverage apps as features for describing user's personal interests and propose a novel approach to do personalized recommendation. We introduce a Small-Crowd model to distinguish apps at reflecting users' personal interests, and design a weighting method to rank the installed apps for users by combining the global download information with fine-grained app usage records. The extensive experiments validate the effectiveness of our approach which outperforms state-of-the-art method. Copyright 2014 ACM.

关键词： Mobile computing

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Rethinking benchmarking for NVM-based file systems 16

Rethinking benchmarking for NVM-based file systems

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7th ACM SIGOPS Asia-Pacific Workshop on Systems, APSys 2016

作者： Dong, Mingkai Yu, Qianqian Zhou, Xiaozhou Hong, Yang Chen, Haibo Zang, Binyu Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China

ISBN: (纸本)9781450342650

Fast, byte-addressable NVM promises near-cache latency and near memory bus throughput for file systems, which is evident by recent development of a number of NVM file systems (NVMFS). However, a key approach to measuring their performance, file system benchmarks, remains unchanged as those for disk-based file systems (DFS). In this paper, we analyze the pitfalls of using DFS benchmarks to evaluate NVMFS and propose several changes to existing DFS benchmarks to better characterize the performance of NVMFS. © 2016 ACM.

关键词： Benchmarking

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Data dependence-based optimistic data consistency maintenance method

Data dependence-based optimistic data consistency maintenanc...

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6th IEEE International Conference on Computer and Information Technology, CIT 2006

作者： Zhou, Jing Wang, Yijie Li, Sikun National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology China

ISBN: (纸本)076952687X

Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to that, an optimistic data consistency method is proposed. In our method, data object is partitioned into data blocks by fixed size, as the basic unit of data management. Updates are compressed by Bloom filter technique and propagated in double-path. Negotiation algorithms detect and reconcile update conflicts, and dynamic data management algorithms accommodate dynamic data processing. The results of the performance evaluation show that our method is an efficient method to achieve consistency, good dynamic property, and strong robustness. © 2006 IEEE.

关键词： Information technology

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DMSA: Decentralized and Multi-keyword Selective Data Sharing and Acquisition 22

DMSA: Decentralized and Multi-keyword Selective Data Sharing...

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22nd IEEE International Symposium on parallel and distributed Processing with Applications, ISPA 2024

作者： Lin, Moheng Shi, Peichang Fu, Xiang Jiang, Feng Yi, Guodong National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Science Changsha410073 China Xiangjiang Lab Changsha410073 China

ISBN: (纸本)9798331509712

Blockchain technology has been extensively uti-lized in decentralized data-sharing applications, with the immutability of blockchain providing a witness for the circulation of data. However, current blockchain data-sharing solutions still fail to address the simultaneous screening needs of both the sender and receiver with multi-keywords. Without the capability to support bilateral simultaneous filtering, the disclosure of reasons for matching failures could inadvertently expose sensitive user data. Therefore, the challenge lies in enabling ciphertexts with multiple keywords and receivers with multiple interests to achieve mutual and simultaneous matching. Based on the technical foundations of SE (Searchable Encryption), MABE (Multi-Attribute Based Encryption), and polynomial fitting, this paper proposes a scheme called DMSA (Decentralized and Multi-keyword selective Sharing and selective Acquisition). This scheme can satisfy soundness, enabling ciphertexts carrying multiple keywords and receivers representing multiple interests to match each other simultaneously. We conducted a security analysis that confirms the security of DMSA against chosen-plaintext attacks. Our experimental results demonstrate a significant efficiency improvement, with a 67% increase over single-keyword data-sharing schemes and a 16% enhancement compared to the existing multi-keyword data-sharing solution. © 2024 IEEE.

关键词： Ciphertext

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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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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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Evaluating bug severity using crowd-based knowledge: An exploratory study 15

Evaluating bug severity using crowd-based knowledge: An expl...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Yin, Gang Wang, Tao Yu, Yue Wang, Huaimin Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

In bug tracking system, the high volume of incoming bug reports poses a serious challenge to project managers. Triaging these bug reports manually consumes time and resources which leads to delaying the resolution of important bugs. StackOverow is the most popular crowdsourcing Q&A community with plenty of bug-related posts. In this paper, we explore the correlation between bug severity and the crowd attributes of linked posts. Two typical types of projects' bug repositories are studied here, e.g. Mozilla (user-centric project) and Eclipse (developer-centric project). Our results show that the bug severity is consistent with the crowd- based knowledge both in Mozilla and Eclipse, i.e. the linked posts of severe bugs have higher score etc. in StackOverow than non-severe bugs. This interesting phenomenon inspires us that we can optimize the existing evaluation methods of bug severity by incorporating the crowd-based knowledge from a third-party in future. © 2015 ACM.

关键词： StackOverflow crowd-based knowledge Bugzilla Bug severity

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Exploring the use of @-mention to assist software development in GitHub 15

Exploring the use of @-mention to assist software developmen...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Zhang, Yang Wang, Huaimin Yin, Gang Wang, Tao Yu, Yue Key Lab. of Parallel and Distributed Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

Recently, many researches propose that social media tools can promote the collaboration among developers, which are beneficial to the software development. Nevertheless, there is little empirical evidence to confirm that using @-mention has indeed a beneficial impact on the issues in GitHub. In this paper, we analyze the data from GitHub and give some insights on how @-mention is used in the issues (general- issues and pull-requests). Our statistical results indicate that, @-mention attracts more participants and tends to be used in the difficult issues. @-mention favors the solving process of issues by enlarging the visibility of issues and facilitating the developers' collaboration. In addition to this global study, our study also build a @-network based on the @-mention database we extract. Through the @-network, we can mine the relationships and characteristics of developers in GitHub's issues. © 2015 ACM.

关键词： Social networking (online)

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NUMA-aware graph-structured analytics 2015

NUMA-aware graph-structured analytics

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20th ACM SIGPLAN Symposium on Principles and Practice of parallel Programming, PPoPP 2015

作者： Zhang, Kaiyuan Chen, Rong Chen, Haibo Shanghai Key Laboratory of Scalable Computing and Systems Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China

ISBN: (纸本)9781450332057

Graph-structured analytics has been widely adopted in a number of big data applications such as social computation, web-search and recommendation systems. Though much prior research focuses on scaling graph-analytics on distributed environments, the strong desire on performance per core, dollar and joule has generated considerable interests of processing large-scale graphs on a single server-class machine, which may have several terabytes of RAM and 80 or more cores. However, prior graph-analytics systems are largely neutral to NUMA characteristics and thus have suboptimal performance. This paper presents a detailed study of NUMA characteristics and their impact on the efficiency of graph-analytics. Our study uncovers two insights: 1) either random or interleaved allocation of graph data will significantly hamper data locality and parallelism;2) sequential inter-node (i.e., remote) memory accesses have much higher bandwidth than both intra- and inter-node random ones. Based on them, this paper describes Polymer, a NUMA-aware graph-analytics system on multicore with two key design decisions. First, Polymer differentially allocates and places topology data, application-defined data and mutable runtime states of a graph system according to their access patterns to minimize remote accesses. Second, for some remaining random accesses, Polymer carefully converts random remote accesses into sequential remote accesses, by using lightweight replication of vertices across NUMA nodes. To improve load balance and vertex convergence, Polymer is further built with a hierarchical barrier to boost parallelism and locality, an edge-oriented balanced partitioning for skewed graphs, and adaptive data structures according to the proportion of active vertices. A detailed evaluation on an 80-core machine shows that Polymer often outperforms the state-of-the-art single-machine graph-analytics systems, including Ligra, X-Stream and Galois, for a set of popular real-world and synthetic grap

关键词： Random access storage

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Continuous probabilistic reverse skyline monitoring over uncertain data streams

Continuous probabilistic reverse skyline monitoring over unc...

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2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013

作者： Yang, Yong Tao Wang, Yi Jie Guo, Min Li, Xiao Yong National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9783037858202

Reverse skyline is useful for supporting many applications, such as marketing decision, environmental monitoring. Since the uncertainty of data is inherent in many scenarios, there is a need for processing probabilistic reverse skyline queries. In this paper, we study the problem of efficiently processing these queries on uncertain data streams. We first show the formal definitions of reverse skyline probability and probabilistic reverse skyline. Then we propose a new algorithm called CPRS to maintain the most recent N uncertain data elements and to process continuous queries on them. CPRS is based on R-tree, and efficient pruning techniques, one of which is based on a new structure named Characteristic Rectangle, are incorporated into it to handling the extra computing complexity arising from the uncertainty of data. Finally, extensive experiments demonstrate that our techniques are very efficient in handling uncertain data streams. © (2013) Trans Tech Publications, Switzerland.

关键词： Decision trees

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False-positive probability and compression optimization for tree-structured bloom filters

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ACM Transactions on Modeling and Performance Evaluation of computing Systems 2016年第4期1卷 1–39页

作者： Fu, Yongquan Biersack, Ernst National Key Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Sanyi Road Changsha Hunan Province410073 China CAIPY Valbonne06560 France

Bloom filters are frequently used to to check the membership of an item in a set. However, Bloom filters face a dilemma: the transmission bandwidth and the accuracy cannot be optimized simultaneously. This dilemma is particularly severe for transmitting Bloom filters to remote nodes when the network bandwidth is limited. We propose a novel Bloom filter called BloomTree that consists of a tree-structured organization of smaller Bloom filters, each using a set of independent hash functions. BloomTree spreads items across levels that are compressed to reduce the transmission bandwidth need. We show how to find optimal configurations for BloomTree and investigate in detail by how much BloomTree outperforms the standard Bloom filter or the compressed Bloom filter. Finally, we use the intersection of BloomTrees to predict the set intersection, decreasing the false-positive probabilities by several orders of magnitude compared to both the compressed Bloom filter and the standard Bloom filter. © 2016 ACM 2376-3639/2016/09-ART19 $15.00

关键词： Genetic algorithms

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