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Towards context consistency by concurrent checking for Internetware applications

science China(Information sciences) 2013年第8期56卷 69-88页

作者： XU Chang LIU YePang CHEUNG S.C. CAO Chun LV Jian State Key Laboratory for Novel Software Technology Nanjing University Department of Computer Science and Technology Nanjing University Department of Computer Science and Engineering The Hong Kong University of Science and Technology

Internetware applications are emerging and being widely *** can adapt their behavior based on environmental contexts and deliver smart *** contexts can be subject to various noises,which cause them to be inaccurate,incomplete,or even to conflict with each *** is known as context inconsistency *** inconsistency can trigger unexpected behavior to applications,and therefore should be *** promising approach is to check contexts against consistency constraints so as to detect the occurrences of context inconsistency at *** techniques have attempted different ways to improve the checking efficiency or effectiveness with different trade-offs in space overhead or communication ***,none of them has exploited multi-core computing capability to systematically improve the checking *** this paper,we propose a novel concurrent checking technique Con-C to efficiently detect inconsistencies in huge volumes of dynamic ***-C derives checking subtasks for each consistency constraint based on its structure and *** achieves this in a fully automated way,and at the same time can guarantee its derived checking subtasks to be persistently *** evaluated Con-C by controlled experiments through a large-scale real-world *** reported promising results that Con-C improved the checking efficiency by extra 57.0%,in addition to what had been gained by incremental checking.

关键词： concurrent checking consistency constraint context inconsistency pervasive computing Internetware

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Combining Text Mining and Data Mining for Bug Report Classification

Combining Text Mining and Data Mining for Bug Report Classif...

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International Conference on software Maintenance (ICSM)

作者： Yu Zhou Yanxiang Tong Ruihang Gu Harald Gall College of Computer Science Nanjing University of Aeronautics and Astronautics State Key Lab. of Novel Software Technology Nanjing University China Department of Informatics University of Zurich Switzerland

Misclassification of bug reports inevitably sacrifices the performance of bug prediction models. Manual examinations can help reduce the noise but bring a heavy burden for developers instead. In this paper, we propose a hybrid approach by combining both text mining and data mining techniques of bug report data to automate the prediction process. The first stage leverages text mining techniques to analyze the summary parts of bug reports and classifies them into three levels of probability. The extracted features and some other structured features of bug reports are then fed into the machine learner in the second stage. Data grafting techniques are employed to bridge the two stages. Comparative experiments with previous studies on the same data -- three large-scale open source projects -- consistently achieve a reasonable enhancement (from 77.4% to 81.7%, 73.9% to 80.2% and 87.4% to 93.7%, respectively) over their best results in terms of overall performance. Additional comparative empirical experiments on other two popular open source repositories confirm the findings and demonstrate the benefits of our approach.

关键词： Feature extraction Text mining Training software Predictive models Bayes methods

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Fast and fine-grained counting and identification via constructive interference in WSNs

Fast and fine-grained counting and identification via constr...

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International Symposium on Information Processing in Sensor Networks (IPSN)

作者： Dingming Wu Chao Dong Shaojie Tang Haipeng Dai Guihai Chen State Key Laboratory for Novel Software Technology Nanjing University Nanjing China PLA University of Science and Technology Nanjing China Department of Computer and Information Science Temple University Philadelphia PA

Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.

关键词： Delays Estimation Propagation delay Accuracy Synchronization Hardware Receivers

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User Guided Automation for Testing Mobile Apps

User Guided Automation for Testing Mobile Apps

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Asia-Pacific Conference on software Engineering

作者： Xiujiang Li Yanyan Jiang Yepang Liu Chang Xu Xiaoxing Ma Jian Lu Dept. of Computer Science and Technology Nanjing University Nanjing China Dept. of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China State Key Lab for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781479974276

Mobile devices are gradually taking over traditional computers' dominance in human lives. With the ever-increasing shipment of mobile apps running on these devices, their quality issues become a severe challenge. Although automated testing techniques are being widely studied, they mostly fall short of handling mobile apps' complex interactions, e.g., A finger swipe or device shaking gesture, leading to inadequate testing. In this paper, we present a novel User Guided Automation (UGA) technique to address testing challenges incurred by such complex interactions. UGA exploits user insights to complement automated testing techniques by recording user-guided app executions, replaying apps to certain stop points, and systematically exploring state space from these stop points. We implemented our work as a prototype UGA tool on Android platform and evaluated it on seven real-world Android apps. Evaluation results show that UGA achieved 1.59-21.78× improvement in terms of method coverage over state-of-the-art automated techniques in testing mobile apps.

关键词： Testing Graphical user interfaces Mobile communication Androids Humanoid robots Automation computers

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A method of computing the hot topics' popularity on the internet combined with the features of the microblogs

A method of computing the hot topics' popularity on the inte...

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5th International Symposium on IT in Medicine and Education, ITME 2013

作者： Wei, Yongqing Zhang, Zhen Fei, Shaodong Du, Wentao Basic Education Department Shandong Police College Jinan 250014 China School of Information Science and Engineering Shandong Normal University Jinan 250014 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan 250014 China Shandong University of Finance and Economics Jinan 250014 China

ISBN: (纸本)9789400776173

The article puts forward a new formula of computing the popularity of the topics, which is based on the stream of the news on the internet. What's more, the features of the microblogs should be also considered and combined. The hot topics are sorted by the values of them, so the information of the topics is convenient and accurate to be acquired for the public. It is beneficial to the government to supervise the public opinion as well. The experiments are based on both news and the microblogs. Our system could figure out the value of the hot topics by the popularity among users, after that the topics will be sorted automatically. The results of the experiments have shown that the system worked well. © Springer science+Business Media Dordrecht 2014.

关键词： Social aspects

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Efficiently Collecting Histograms Over RFID Tags

Efficiently Collecting Histograms Over RFID Tags

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IEEE International Conference on computer Communications

作者： Lei Xie Hao Han Qun Li Jie Wu Sanglu Lu State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science College of William and Mary USA Department of Computer Information and Sciences Temple University USA

Collecting histograms over RFID tags is an essential premise for effective aggregate queries and analysis in large-scale RFID-based applications. In this paper we consider efficient collection of histograms from the massive number of RFID tags without the need to read all tag data. We first consider the problem of basic histogram collection and propose an efficient algorithm based on the idea of ensemble sampling. We further consider the problems of advanced histogram collection, respectively, with an iceberg query and a top-κ query. Efficient algorithms are proposed to tackle the above problems such that the qualified/unqualified categories can be quickly identified. Experiment results indicate that our ensemble sampling-based solutions can achieve a much better performance than the basic estimation/identification schemes.

关键词： Histograms Accuracy Sociology RFID tags Protocols

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FACIAL ACTION UNIT RECOGNITION BY RELATION MODELING FROM BOTH QUALITATIVE KNOWLEDGE AND QUANTITATIVE DATA

FACIAL ACTION UNIT RECOGNITION BY RELATION MODELING FROM BOT...

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IEEE International Conference on Multimedia and Expo Workshops

作者： Zhen Gao Shangfei Wang Chongliang Wu Jun Wang Qiang Ji Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute

ISBN: (纸本)9781479947164

In this paper, we propose to capture Action Unit (AU) relations existing in both qualitative knowledge and quantitative data through Credal Networks (CN). Each node of the CN represents an AU label, and the links and probability intervals capture the probabilistic dependencies among multiple AUs. The structure of CN is designed based on prior knowledge. The parameters of CN are learned from both knowledge and ground-truth AU labels. The AU preliminary estimations are obtained by an existing image-driven recognition method. With the learned credal network, we infer the true AU labels by combining the relationships among labels with the previous obtained estimations. Experimental results on the CK+ database and MMI database demonstrate that with complete AU labels, our CN model is slightly better than the Bayesian Network (BN) model, demonstrating that credal sets learned from data can capture uncertainty more reliably;With incomplete and error-prone AU annotations, our CN model outperforms the BN model, indicating that credal sets can successfully capture qualitative knowledge.

关键词： Prior knowledge Credal network AU recognition

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Thermal-Aware Task Placement with Dynamic Thermal Model in an Established Datacenter

Thermal-Aware Task Placement with Dynamic Thermal Model in a...

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International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS)

作者： Zhigang Jiang Wei Huang Ilsun You Zhuzhong Qian Sanglu Lu School of Computer Engineering Nanjing Institute of Technology China State Key Lab. for Novel Software Technology Nanjing University China School of Information Science Korean Bible University South Korea

ISBN: (纸本)9781479978915

Cooling system is one of the key components in data centers and consumes nearly half of the total energy. For the safety and efficiency of a data enter, cooling system should guarantee all the servers running in a suitable temperature. Thus, the cooling efficiency becomes lower as the occurrence of hot spots, because the whole cooling system will accordingly work in a strong cooling mode, which leads to overcooling. One of the key challenges toward this problem is to build an effective and efficient online task scheduling to balance the inlet temperature of the servers in a data enter. In this paper, we investigate the thermal model in a data enter, and we formulate the task placement problem to an optimization problem with the purpose to minimize the maximum inlet temperature of all servers. To get higher accuracy, we proposed a dynamic thermal model updated with the real data from temperature sensors. We solve the formulated problem in an approximate way and design a first-fit decreasing task placement algorithm with the idea of CPU budget. Finally, the effectiveness and accuracy of our algorithm are confirmed by experiments on a real test bed.

关键词： Servers Cooling Computational modeling Heating Atmospheric modeling Temperature sensors Steady-state

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Intactness verification in anonymous RFID systems

Intactness verification in anonymous RFID systems

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Kai Bu Jia Liu Bin Xiao Xuan Liu Shigeng Zhang College Computer Science and Technology Zhejiang University State Key Laboratory for Novel Software Technology Nanjing University Department of Computing The Hong Kong Polytechnic University School of Information Science and Engineering Central South University

Radio-Frequency Identification (RFID) technology has fostered many object monitoring systems. Along with this trend, tagged objects' value and privacy become a primary concern. A corresponding important problem is to verify the intactness of a set of tagged objects without leaking tag identifiers (IDs). However, existing solutions necessitate the knowledge of tag IDs. Without tag IDs as a priori, this paper studies intactness verification in anonymous RFID systems. We identify three critical solution requirements, that is, deterministic verification, anonymity preservation, and scalability. We propose Cardiff and Divar, two crypto-free, lightweight protocols that isolate tag IDs from intactness verification and satisfy solution requirements. Cardiff explores tag cardinality as intactness proof while Divar leverages Direct-Sequence Spread Spectrum (DSSS) enabled RFID. Both analytical and simulation results demonstrate that Cardiff and Divar can satisfy the requirements of accuracy, privacy, and scalability.

关键词： Radiofrequency identification Spread spectrum communication Servers Scalability Protocols Monitoring Privacy

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A Spin-Glass Model based Local Community Detection Method in Social Networks

A Spin-Glass Model based Local Community Detection Method in...

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25th International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Pan, Lei Wang, Chongjun Xie, Junyuan National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (纸本)9781479929719

Mining community structures has become a general problem which exists in many fields including: computer-science, Mathematics, Physics, Biology, Sociology and so on. It has developed rapidly and been used widely in many applications: web data mining, social network analysis, criminal network mining, protein interaction network analysis, metabolic network analysis, genetic network analysis, customers relationship mining and user online behavior analysis, etc. Most community detection algorithms try to obtain the global information of the network, but increasing large scale of the current network makes it computationally expensive. In the meanwhile, the different influence and different behavior of nodes in the network are ignored. In fact, if we know the local information of the network or the interested node, we can easily detect the local community. This paper proposes a multi-resolution local community detection algorithm named MRCDA which uses local structural information in the network to optimize the multi-resolution modularity based on the Potts spin-glass model. A local community can be detected through continuous optimization of the function by expanding from an initial influential node computed by a modified Page Rank sorting algorithm. The proposed MRCDA has been tested on both synthetic and real world networks and tested against other algorithms. The experiments demonstrate its efficiency and accuracy.

关键词： social network analysis community detection overlapping community local community multi-resolution

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