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An Anti-Eavesdrop Transmission Scheduling Scheme Based on Maximizing Secrecy Outage Probability in Ad Hoc Networks

China Communications 2016年第1期13卷 176-184页

作者： WANG Yajun LIAO Tongqing WANG Chuanan School of Mathematical and Information Engineering Anhui Science and Technology University Ministry of Educational Key Laboratory of Intelligent Computing and Signal Processing Anhui University

In this paper,we consider a wireless ad hoc network consisting of multiple source nodes transmitting to their respective destinations,where an eavesdropper attempts to intercept their *** propose an optimal transmission scheduling scheme to defend against the eavesdropper,where a source node having the highest secrecy rate is scheduled to access the wireless medium for transmitting to its destination in an opportunistic *** be specific,the secrecy rate between a pair of the source and destination in the presence of an eavesdropper varies temporally due to the wireless fading *** proposed optimal transmission scheduling scheme opportunistically selects a source node with the highest secrecy rate to transmit its data for the sake of maximizing the security of the ad hoc network against eavesdropping *** comparison purposes,we also consider the conventional round-robin scheduling as a benchmark,where multiple source nodes take turns in accessing their shared wireless medium for transmitting to their respective *** derive closed-form secrecy outage probability expressions of both the round-robin scheduling and the proposed optimal scheduling schemes over Rayleigh fading *** results show that the proposed transmission scheduling scheme outperforms the conventional round-robin method in terms of its secrecy outage ***,upon increasing the number of source-destination pairs,the secrecy outage probability of the round-robin scheme keeps unchanged,whereas the secrecy outage performance of the proposed transmission scheduling significantly improves,showing the security benefits of exploiting transmission scheduling for protecting wireless ad hoc networks against eavesdropping.

关键词： transmission scheduling eavesdropping secrecy outage probability secrecy rate rayleigh fading

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Optimizing top-k retrieval:submodularity analysis and search strategies

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Frontiers of Computer science 2016年第3期10卷 477-487页

作者： Chaofeng SHA Keqiang WANG Dell ZHANG Xiaoling WANG Aoying ZHOU School of Computer Science Shanghai Key Laboratory of Intelligent Information ProcessingFudan University Shanghai Key Laboratory of Trustworthy Computing East China Normal University Department of Computer Science and Information Systems BirkbeckUniversity of London

The key issue in top-fc retrieval,finding a set of fc documents(from a large document collection) that can best answer a user's query,is to strike the optimal balance between relevance and *** this paper,we study the top-fc retrieval problem in the framework of facility location analysis and prove the submodularity of that objective function which provides a theoretical approximation guarantee of factor 1--for the(best-first) greedy search ***,we propose a two-stage hybrid search strategy which first obtains a high-quality initial set of top-fc documents via greedy search,and then refines that result set iteratively via local *** on two large TREC benchmark datasets show that our two-stage hybrid search strategy approach can supersede the existing ones effectively and efficiently.

关键词： top-k retrieval diversification submodular function maximization

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Anisotropic energy accumulation for stereoscopic image seam carving

Anisotropic energy accumulation for stereoscopic image seam ...

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International Conference on 3D Imaging (IC3D)

作者： Yuqing Lin Yuzhen Niu Shuai Zhang Junhao Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Seam carving is an image resizing method that aims at adapting the image to various display screens while reducing the distortion as much as possible. Severe visual distortion may be introduced by repeated removal or insertion of seams within a concentrated region of the image. To reduce such visual distortion, we propose a new AESSC method. First, we distribute the energy of each pixel on the seam to its adjacent 8-connected pixels when removing or inserting a seam. Second, since the information of each pixel is anisotropic, we use the Sobel operator to detect the direction that has the maximum edge information and continue the energy accumulation along this direction. Besides, we incorporate a 3D structure consistency constraint in the energy function and adopt a pixel visibility maintenance method. Experimental results show that the proposed method can effectively reduce visual distortion for stereo images while maintaining the geometric consistency.

关键词： Distortion Visualization Three-dimensional displays Stereo image processing Image edge detection Histograms Maintenance engineering

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Framework for adaptive computation offloading in IoT applications 17

Framework for adaptive computation offloading in IoT applica...

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9th Asia-Pacific Symposium on Internetware, Internetware 2017

作者： Chen, Shihong Liu, Bichun Chen, Xing Zhang, Ying Huang, Gang College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China

ISBN: (纸本)1595930361

The internet of things (IoT) attracts great interest in many application domains concerned with monitoring and control of physical phenomena. IoT applications try to provide more and more functionality and then they inevitably become so complex as to make the limits of devices worse, which may lead to poor performance of applications. Computation offloading is a promising way to improve the performance of an IoT application by executing some parts of the application on remote devices or servers. However, supporting such capability is not easy for application developers due to (1) adaptability: IoT applications often face changes of runtime environments so that the adaptation on offloading is needed. (2) effectiveness: when the device context changes, it needs to dynamically decide the deployment plan of computation tasks, and the reduced execution time must be greater than the network delay and extra overheads caused by offloading. This paper proposes a framework which supports IoT applications with adaptive computation offloading capability. First, a design pattern is proposed to enable an application to be computation offloaded on-demand. Second, an estimation model is presented to automatically decide the deployment plan for offloading. Third, a framework is implemented to support the design pattern and the estimation model. A thorough zxevaluation on the real-world application is proposed, and the results show that our approach can help reduce execution time by over 45% in most scenarios.

关键词： computation offloading

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Color correction for stereoscopic image based on matching and optimization

Color correction for stereoscopic image based on matching an...

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International Conference on 3D Imaging (IC3D)

作者： Xiaohua Zheng Yuzhen Niu Junhao Chen Yuzhong Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Stereoscopic 3D (S3D) image color correction is a major issue in the field of image processing. However, existing color correction algorithms have limitations. Global color correction algorithms cannot handle local color discrepancies, and local color correction algorithms are sensitive to matching quality between reference and target images. In this study, we propose an S3D image color correction algorithm that combines global and local color information to correct color discrepancies between S3D images. Sparse feature matching usually generates only a few matching features, producing error correction results in some local regions. Our algorithm uses dense stereo matching and global color correction algorithms to initialize color values, and improves the local color smoothness and global color consistency of the resulting image, while maintaining the initial color in that image as much as possible. Experimental results show that our algorithm performs better than do five state-of-the-art color correction algorithms.

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From social to individuals: A parsimonious path of multi-level models for crowdsourced preference aggregation

arXiv

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arXiv 2018年

作者： Xu, Qianqian Xiong, Jiechao Cao, Xiaochun Huang, Qingming Yao, Yuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing1000190 China Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Tencent AI Lab Shenzhen518057 BICMR-LMAM-LMEQF-LMP School of Mathematical Sciences Peking University Beijing100871 China University of Chinese Academy of Sciences Institute of Computing Technology of Chinese Academy of Sciences Beijing100190 China Department of Mathematics and by courtesy Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

In crowdsourced preference aggregation, it is often assumed that all the annotators are subject to a common preference or social utility function which generates their comparison behaviors in experiments. However, in reality annotators are subject to variations due to multi-criteria, abnormal, or a mixture of such behaviors. In this paper, we propose a parsimonious mixed-effects model, which takes into account both the fixed effect that the majority of annotators follows a common linear utility model, and the random effect that some annotators might deviate from the common significantly and exhibit strongly personalized preferences. The key algorithm in this paper establishes a dynamic path from the social utility to individual variations, with different levels of sparsity on personalization. The algorithm is based on the Linearized Bregman Iterations, which leads to easy parallel implementations to meet the need of large-scale data analysis. In this unified framework, three kinds of random utility models are presented, including the basic linear model with L2 loss, Bradley-Terry model, and Thurstone-Mosteller model. The validity of these multi-level models are supported by experiments with both simulated and real-world datasets, which shows that the parsimonious multi-level models exhibit improvements in both interpretability and predictive precision compared with traditional HodgeRank. Copyright © 2018, The Authors. All rights reserved.

关键词： Crowdsourcing

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Predicting protein inter-residue contacts using composite likelihood maximization and deep learning

arXiv

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arXiv 2018年

作者： Zhang, Haicang Zhang, Qi Ju, Fusong Zhu, Jianwei Sun, Shiwei Gao, Yujuan Xie, Ziwei Deng, Minghua Sun, Shiwei Zheng, Wei-Mou Bu, Dongbo Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Center for Quantitative Biology School of Mathematical Sciences Center for Statistical Sciences Peking University Beijing China Institute of Theoretical Physics Chinese Academy of Sciences Beijing China College of Life Science and Technology Huazhong University of Science and Technology Wuhan China

Accurate prediction of inter-residue contacts of a protein is important to calculating its tertiary structure. Analysis of co-evolutionary events among residues has been proved effective to inferring inter-residue contacts. The Markov random field (MRF) technique, although being widely used for contact prediction, suffers from the following dilemma: the actual likelihood function of MRF is accurate but time-consuming to calculate;in contrast, approximations to the actual likelihood, say pseudo-likelihood, are efficient to calculate but inaccurate. Thus, how to achieve both accuracy and efficiency simultaneously remains a challenge. In this study, we present such an approach (called clmDCA) for contact prediction. Unlike plmDCA using pseudo-likelihood, i.e., the product of conditional probability of individual residues, our approach uses composite-likelihood, i.e., the product of conditional probability of all residue pairs. Composite likelihood has been theoretically proved as a better approximation to the actual likelihood function than pseudo-likelihood. Meanwhile, composite likelihood is still efficient to maximize, thus ensuring the efficiency of clmDCA. We present comprehensive experiments on popular benchmark datasets, including PSICOV dataset and CASP-11 dataset, to show that: i) clmDCA alone outperforms the existing MRF-based approaches in prediction accuracy. ii) When equipped with deep learning technique for refinement, the prediction accuracy of clmDCA was further significantly improved, suggesting the suitability of clmDCA for subsequent refinement procedure. We further present successful application of the predicted contacts to accurately build tertiary structures for proteins in the PSICOV dataset. Accessibility: The software clmDCA and a server are publicly accessible through http://***/clmDCA/. Copyright © 2018, The Authors. All rights reserved.

关键词： Proteins

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Cross-media analysis and reasoning: advances and directions

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Frontiers of information Technology & Electronic Engineering 2017年第1期18卷 44-57页

作者： Yu-xin PENG Wen-wu ZHU Yao ZHAO Chang-sheng XU Qing-ming HUANG Han-qing LU Qing-hua ZHENG Tie-jun HUANG Wen GAO Institute of Computer Science and Technology Peking University Department of Computer Science and Technology Tsinghua University Institute of Information Science Beijing Jiaotong University National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of Sciences Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences Department of Computer Science and Technology Xi'an Jiaotong University School of Electronics Engineering and Computer Science Peking University

Cross-media analysis and reasoning is an active research area in computer science, and a promising direction for artificial intelligence. However, to the best of our knowledge, no existing work has summarized the state-of-the-art methods for cross-media analysis and reasoning or presented advances, challenges, and future directions for the field. To address these issues, we provide an overview as follows：（1） theory and model for cross-media uniform representation; （2） cross-media correlation understanding and deep mining; （3） cross-media knowledge graph construction and learning methodologies; （4） cross-media knowledge evolution and reasoning; （5） cross-media description and generation; （6） cross-media intelligent engines; and （7） cross-media intelligent applications. By presenting approaches, advances, and future directions in cross-media analysis and reasoning, our goal is not only to draw more attention to the state-of-the-art advances in the field, but also to provide technical insights by discussing the challenges and research directions in these areas.

关键词： Cross-media analysis Cross-media reasoning Cross-media applications

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The M-computations induced by accessibility relations in nonstandard models M of Hoare logic

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Frontiers of Computer science 2016年第4期10卷 717-725页

作者： Cungen CAO Yuefei SUI Zaiyue ZHANG Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Computer Science Jiangsu University of Sciences and Technology Zhenjiang 212003 China

Hoare logic is a logic used as a way of specifying semantics of programming languages, which has been extended to be a separation logic to reason about mutable heap structure. In a model M of Hoare logic, each program α induces an M-computable function fα M on the universe of M; and the M-recursive functions are defined on M. It will be proved that the class of all the M-computable functions fα M induced by programs is equal to the class of all the M- recursive functions. Moreover, each M-recursive function is ∑ 1 NM -definable in M, where the universal quantifier is a num- ber quantifier ranging over the standard part of a nonstandard model M.

关键词： Hoare logic recursive ：Function computable function nonstandard model of Peano arithmetic

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An Energy Efficient VM Migration Algorithm in Data Centers

An Energy Efficient VM Migration Algorithm in Data Centers

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2017 16th International Symposium on Distributed computing and Applications to Business,Engineering and science（DCABES 2017）

作者： Xiaodong Wu Yuzhu Zeng Guoxin Lin Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information ProcessingFujian Province University

In order to reduce operation and maintenance expense and also increase the resource utilization rate,server consolidation and virtualization solutions have been adopted in modern cloud computing data ***,the scheduling policies of virtual machine（VM） migration have been regarded as an effective method for energy *** this paper,we address the problem of VM consolidation in cloud data centers.A power aware scheduling algorithm THRUG,which is combined with a utilization threshold strategy and a VM selection policy,is *** tries to select the most appropriate VMs for migration each time when a physical machine（PM） is considered as being overloaded,such that the utilization of this PM is just not more than the utilization threshold,such that both the energy consumption and the number of VM migration can be *** experimental results show that compared with other algorithm,the proposed algorithm can effectively reduce the number of VM migrations as well as the energy consumption.

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