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Improved locality-sensitive hashing method for the approximate nearest neighbor problem

Chinese Physics B 2014年第8期23卷 217-225页

作者：陆颖华马廷淮钟水明曹杰王新 Abdullah Al-Dhelaane Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology School of Computer & Software Nanjing University of Information Science & Technology School of Economic & Management Nanjing University of Information Science & Technology Huafeng Meteorological Media Group Computer Science Department College of Computer and Information Science King Saud University

In recent years, the nearest neighbor search （NNS） problem has been widely used in various interesting applications. Locality-sensitive hashing （LSH）, a popular algorithm for the approximate nearest neighbor problem, is proved to be an efficient method to solve the NNS problem in the high-dimensional and large-scale databases. Based on the scheme of p-stable LSH, this paper introduces a novel improvement algorithm called randomness-based locality-sensitive hashing （RLSH） based on p-stable LSH. Our proposed algorithm modifies the query strategy that it randomly selects a certain hash table to project the query point instead of mapping the query point into all hash tables in the period of the nearest neighbor query and reconstructs the candidate points for finding the nearest neighbors. This improvement strategy ensures that RLSH spends less time searching for the nearest neighbors than the p-stable LSH algorithm to keep a high recall. Besides, this strategy is proved to promote the diversity of the candidate points even with fewer hash tables. Experiments are executed on the synthetic dataset and open dataset. The results show that our method can cost less time consumption and less space requirements than the p-stable LSH while balancing the same recall.

关键词： approximate nearest neighbor problem locality-sensitive hashing

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CADEC: A Combinatorial Auction for Dynamic Distributed DNN Inference Scheduling in Edge-Cloud Networks

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IEEE Transactions on Mobile Computing 2025年

作者： Xu, Xiaolong Hu, Yuhao Cui, Guangming Qi, Lianyong Dou, Wanchun Nanjing University of Information Science and Technology School of Software Nanjing 210044 China Nanjing University of Information Science and Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software China Nanjing University State Key Laboratory for Novel Software Technology China China University of Petroleum (East China) College of Computer science and technology Qingdao China Georgia State University Department of Computer Science United States

Deep Neural Network (DNN) Inference, as a key enabler of intelligent applications, is often computation-intensive and latency-sensitive. Combining the advantages of cloud computing (abundant computing resources) and edge computing (fast transmission), edge-cloud collaborative DNN inference is a powerful solution to these problems. However, in edge-cloud networks with heterogeneous resources, how to obtain reasonable decisions on server selection, model partition and resource allocation for efficient distributed DNN inference is a hard challenge. Furthermore, it is non-trivial to design suitable resource prices to maximize the social welfare. These challenges even escalate in dynamic edge-cloud networks where decisions should be generated as soon as each user arrives without future information. Therefore, we design a combinatorial auction for dynamic distributed DNN inference scheduling, named CADEC. CADEC first constructs a bid set for each user based on convex optimization theory for optimal solution searching. Next, prices of resources in the edge-cloud network are adjusted according to changes in supply-demand relationship, and whether to admit the request of each user is decided. Finally, the dynamic distributed inference scheduling decisions are generated through the primal-dual algorithm to maximize the social welfare. Theoretical analysis shows the good competitive ratio and polynomial time complexity of CADEC. Results of simulation experiments present that CADEC improves social welfare by up to 46% compared with state-of-the-art distributed DNN inference schemes. © 2002-2012 IEEE.

关键词： Combinatorial auction distributed DNN inference dynamic scheduling edge-cloud networks resource pricing

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Precipitable water vapor retrieved from FY-3G/MWRI-RM observations using machine learning models

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Advances in Space Research 2025年

作者： Yuxin Liu Xinzhi Wang Yi Zhou Atta ur Rahman School of Remote Sensing and Geomatics Engineering Nanjing University of Information Science and Technology Nanjing 210044 China Jiangsu Province Engineering Research Center of Collaborative Navigation/Positioning and Smart Applications Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China

Water vapor is an essential component of the Earth’s atmosphere, and accurate retrieval of precipitable water vapor (PWV) is critical to understanding the Earth’s climate and hydrological cycle. In this study, we use the global Fengyun-3G/Micro-Wave Radiation Imager-Rainfall Mission (FY-3G/MWRI-RM) L1 data from October 2023 to August 2024 to construct a high-precision PWV retrieval model. Three machine learning algorithms are used to construct our models:Random Forests (RF), Light Gradient Boosting Machine (Light GBM), and Gradient Boosting Regression (GBR), due to their ability to handle complex relationships between brightness temperature data and PWV retrieval with high precision. Then, the precision of retrieved PWV is evaluated using the fifth generation of European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis (ERA5) PWV and radiosonde PWV. Light GBM demonstrated the highest accuracy with root-mean-square error (RMSE) of 2.151 mm over the ocean compared to ERA5 PWV, outperforming GBR and RF. RF demonstrated the highest accuracy with RMSE of 2.323 mm over land compared to ERA5 PWV, outperforming Light GBM and GBR. In addition, this study compares the FY-3G/MWRI-RM PWV with Advanced Microwave Scanning Radiometer 2 (AMSR2) TPW and AMSR2 PWL. FY-3G/MWRI-RM retrieved PWV demonstrated higher precision compared to AMSR2 water vapor products when validated against ERA5 PWV.

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A Novel Association Rule Mining Method for Streaming Temporal Data

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Annals of Data Science 2022年第4期9卷 863-883页

作者： Zheng, Hui Li, Peng He, Jing School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Jiangsu Nanjing China School of Software and Electrical Engineering Swinburne University of Technology Melbourne Australia

Streaming temporal data contains time stamps and values, challenging to quantify relationships of time stamps and corresponding values. Moreover, the characteristics and relationships of streaming temporal data are not invariable. Thus, it is impossible to analyse all data by a trained model at the beginning of data streams. Practically, the trained model to analyse streaming temporal data should change according to the increasing volume of data. Association rule mining, on the other hand, can find potential relationships from given data. This paper proposes an association rule mining method for streaming temporal data to discover potential relationships from streaming temporal data. Our experiments verify our proposed method. A public data set is applied to compare the performance of the proposed method and its counterpart. A small data set is also applied for two case studies to further illustrate our proposed method mine association rules with streaming temporal data with time stamps and corresponding values. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Association rule mining Streaming data Potential relationships Timestamp Value Data mining Association rule learning

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Research on Bayesian Network Based User's Interest Model

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Wuhan University Journal of Natural Sciences 2007年第5期12卷 809-813页

作者： ZHANG Weifeng XU Baowen CUI Zifeng XU Lei Department of Computer Science and Engineering Nanjing University of Posts and Telecommunications Nanjing 210003 JiangsuChina School of Computer Science and Engineering Southeast University Nanjing 210096 Jiangsu China Jiangsu Institute of Software Quality Nanjing 210096 Jiangsu China

It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users＇ interest models and some basic questions of users＇ interest （representation, derivation and identification of users＇ interest）, a Bayesian network based users＇ interest model is given. In this model, the users＇ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users＇ interested and not interested documents are used to train the Bayesian network. Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropriately reflect the user＇s interest, and has higher performance and good usability.

关键词： Bayesian network interest model feature selection

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Thread-sensitive pointer analysis for. inter-thread dataflow detection

Thread-sensitive pointer analysis for. inter-thread dataflow...

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11th IEEE International Workshop on Future Trends of Distributed Computing Systems

作者： Qian, Ju Xu, Baowen School of Computer Science and Engineering Southeast University Nanjing 210096 China Jiangsu Institution of Software Quality Nanjing 210096 China

ISBN: (纸本)9780769528106

Inter-thread dataflows are of great importance in analyzing concurrent programs. Suffering from the complexity of currency, it is still difficult to identify them from Java programs precisely and efficiently. A fundamental problem in inter-thread dataflow analysis is pointer analysis. Currently, pointer analyses can be classified into context-sensitive ones and context-insensitive ones. They are either too time consuming or too imprecise and hence not suitable for scalable and high precision inter-thread dataflow analysis. To change the situation, this paper proposes a thread-sensitive pointer analysis algorithm which only uses sequences of thread starts as calling contexts. As in inter-thread dataflow analysis, the major objective is analyzing interthread dataflows not intra-thread ones, the coarse-grained context-sensitivity can not only effectively speed up the analysis, but also preserve the analyze precision as much as possible.

关键词： pointer analysis concurrency inter-thread dataflow call graph

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Research on C5.0 algorithm improvement and the test in lightning disaster statistics

International Journal of Control and Automation

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International Journal of Control and Automation 2014年第1期7卷 181-190页

作者： Hou, Shuonan Hou, Rongtao Shi, Xinming Wang, Jun Yuan, Chengshang College of Information Science and Engineering Northeastern University ShenYang 110819 Liaoning China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 Jiangsu China

After analysis the importance of continuous attributes in the C5.0 algorithm processing, and consider the shortcomings of discretization method of C5 algorithm, this paper proposes a new method based on Rough set theory- information entropy- discernible matrix discretization (RSIEDM). The method uses rough, information entropy and Discernible matrix that can be more reasonable and more accurately to continuously attribute discretization, and making created decision tree have better accuracy. In the application of optimization of lightning disaster statistics and evaluation result of lightning disaster, the algorithm which has obtained a better effect. © 2014 SERSC.

关键词： Decision trees

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An effective scheme for biometric cryptosystems 2

An effective scheme for biometric cryptosystems

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2nd IEEE International Conference on computer and Communications, ICCC 2016

作者： Zhou, Yu Zhao, Bo Han, Jin Jun, Zheng School of Computer Science and Software Engineering East China Normal University Shanghai China School of Software and Microelectronics Peking University Beijing China Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology China

ISBN: (纸本)9781467390262

Compared with traditional cryptography, biometric cryptosystems provide more convenient and safe protection of keys. In this paper, an effective scheme for biometric cryptosystems based on the intersections of hyper-plane and hashed discrete space is proposed. Only genuine feature vectors, which are located on the hyper-plane, find the correct solution. Several tricks are provided to ensure the security of proposed scheme. Experiments have shown that our method achieved approximate performance compared with one of the latest methods based on fuzzy vault. However, our method is less complex than fuzzy vault based methods. © 2016 IEEE.

关键词： Cryptography

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Attribute-Based Access Control Scheme with Efficient Revocation in Cloud Computing

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China Communications 2016年第7期13卷 92-99页

作者： Zhihua Xia Liangao Zhang Dandan Liu Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology School of Computer and Software Nanjing University of Information Science & Technology Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science & Technology

Attribute-based encryption(ABE) supports the fine-grained sharing of encrypted *** some common designs,attributes are managed by an attribute authority that is supposed to be fully *** concept implies that the attribute authority can access all encrypted data,which is known as the key escrow *** addition,because all access privileges are defined over a single attribute universe and attributes are shared among multiple data users,the revocation of users is inefficient for the existing ABE *** this paper,we propose a novel scheme that solves the key escrow problem and supports efficient user ***,an access controller is introduced into the existing scheme,and then,secret keys are generated corporately by the attribute authority and access ***,an efficient user revocation mechanism is achieved using a version key that supports forward and backward *** analysis proves that our scheme is secure and efficient in user authorization and revocation.

关键词： access control ABE efficient revocation removing escrow cloud computing

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A Survey of Image Super Resolution Based on CNN 9th

A Survey of Image Super Resolution Based on CNN

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9th EAI International Conference on Cloud Computing, CloudComp 2019 and the 4th EAI International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019

作者： Xu, Qianxiong Zheng, Yu School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology NanjingJiangsu210044 China

ISBN: (纸本)9783030485122

With the advent of the information age in contemporary society, images are everywhere, no matter in military use or in daily life. Therefore, as a medium for people to obtain information, images have become more and more important. With the fast development of deep convolution neural networks (DCNNs), Single-Image Super-Resolution (SISR) becomes one of the techniques that have made great breakthroughs in recent years. In this paper, we give a brief survey on the task of SISR. In general, we introduce the SR problem, some recent SR methods, public benchmark datasets and evaluation metrics. Finally, we conclude by denoting some points that could be further improved in the future. © 2020, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Surveys

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