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作者： Shen, Jian Shen, Jun Li, Xiong Wei, Fushan Li, Jiguo Department of Jiangsu Engineering Center of Network Monitoring Jiangsu210044 China Technology and Engineering Center of Meteorological Sensor Network Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing Jiangsu210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China Hunan University of Science and Technology Hunan410082 China PLA Information Engineering University Henan450002 China Hohai University Nanjing210098 China

The rapid development of cloud storage has caused a wave of research craze. To improve cloud user experience, a large number of schemes are proposed with various practical performances, like long-term correct ensurence and dynamic support. In most works, however, authors seem to completely ignore that data owner alone could not have enough energy to discover and correct all inappropriate data outsourced. Others considered it and gave more than one user both read and write permissions, leading to chaotic management of multiusers. In this paper, we propose a novel algorithm, where data owner and authenticated assistants form a team to support data dynamics. Assistants are in charge of detecting problems of data and discussing a corresponding modification suggestion, while data owner is responsible for the implementation of the modification. Additionally, our algorithm supports identity authentication, malicious assistant revocation, and lazy update. Sufficient numerical analysis validates the performance of our algorithm. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Cloud storage

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An Economy-mode Framework for Task Offloading in Fog Computing networks

An Economy-mode Framework for Task Offloading in Fog Computi...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Beibei Wang Fei Shen Xujie Li Fei Qin Feng Yan Siyuan Zhou College of computer and information Hohai University Nanjing China Shanghai Research Center for Wireless Communications Shanghai China Key Lab for Wireless Sensor network and Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China The School of Electronic and Electrical Communication Engineering University of Chinese Academy of Sciences Beijing China National Mobile Communications Research Laboratory Southeast University Nanjing China

In the fog network, by offtoading the computing tasks to the fog nodes (FNs) located at the edge of the network, the task processing delay of the terminal nodes (TNs) can be reduced significantly. However, not all the FNs are willing to help TNs for free. Therefore, an economy-mode framework for task offtoading in the fog network is required to motivate the FNs. In this paper, we formulate the task offtoading problem based on Stackelberg game. The TN with computing tasks acts as the leader and its strategy is the optimal unit computing price. Each FN with idle resources acts as the follower and its strategy is the sharable optimal proportion of computing capability. Firstly, the leader predicts the followers' strategies and provides the unit computing price. Next, given the price, the followers will do exactly what the leader wishes, which is the system optimal point. By maximizing the utility functions of both the TN and FNs, a win-win solution is obtained. The numerical simulations indicate the importance of our proposed economy-mode framework for task offtoading.

关键词： Task analysis Delays Games Energy consumption Edge computing Computational modeling Wireless communication

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Intra/Inter-frame Joint WPP Coding Algorithm on Multicore Platform

Intra/Inter-frame Joint WPP Coding Algorithm on Multicore Pl...

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2018 3rd International Conference on Electrical, Automation and Mechanical engineering(EAME 2018)

作者： Chuanwei Yin Dong Hu Tao Gu Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

Although wavefront parallel processing(WPP) proposed in the HEVC standard and various inter frame WPP algorithms can achieved comparatively high parallelism, their scalability for its parallelism is still very limited due to various dependencies introduced in spatial and temporal prediction in HEVC. In this paper, through pixel correlation analysis, establishment of CTU node model, multi-core resource allocation strategy, we proposed an intra/inter-frame joint WPP coding algorithm for multi-core platform which can significantly improve the parallelism, while achieved good results in bit rate, PSNR, and acceleration ratio. Experiments on standard HD test sequence show that the proposed algorithm can lead to up to 2x, 1.3x speed up compared with the original WPP and IWF parallelism.

关键词： video coding HEVC multicore platform high parallelism WPP

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A Novel Multi-level Wavelet Image Coding Algorithm by Full Sub-band Compressed Sensing

A Novel Multi-level Wavelet Image Coding Algorithm by Full S...

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2018 3rd International Conference on Electrical, Automation and Mechanical engineering(EAME 2018)

作者： Weiping Qiu Dong Hu Yongyang He Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

The performance of wavelet transform based image compressed sensing coding algorithms severely rely on the level of wavelet transform. To this end, this paper investigated the combination of mutil-level wavelet full sub-band in compressed sensing framework. Firstly, we constructed a full sub-band coefficient sparse vector of mutil-level discrete wavelet transform. Secondly, we designed a weight matrix to improve measurement matrix. Finally, sparsity vector was processed by compressed sensing to get the measured value. Compared with the exiting algorithms, the experimental results of the proposed algorithm show that the PSNRs of reconstructed images is improve up to 1～2 dB under the same objective quality.

关键词： image coding wavelet transform compressed sensing full sub-band coefficient sparsity vector

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Layered Compression Scheme for Efficient Data Collection of sensory Data

Layered Compression Scheme for Efficient Data Collection of ...

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International Conference on Computer Communication and networks

作者： Siguang Chen Shujun Zhang Bin Xu Jing Hu Vijayakumar Varadarajan Jiangsu Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunications Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China Information Center Jiangsu China Tobacco Industry Co. Ltd. Nanjing China School of Computing Science and Engineering VIT University Chennai India

Although the existing compressed sensing (CS) based spatio-temporal data compression schemes can significantly decrease communication consumption for data collection, they ignore the data correlation among different clusters over spatial dimension. Actually, the discovery and utilization of spatial correlation among different clusters can further increase the compression rate (or improve the recovery effect). In this paper, we propose a layered compression scheme for efficient data collection of sensory data (LCS-EDC). In the proposed scheme, first, we design a multi-layer network architecture to support the exploration of spatio-temporal correlations, especially for exploring the spatial correlation among different clusters. And then, we construct the specific projection methods respectively for exploring the temporal correlation in sensory nodes, spatial correlation (intra-cluster) in cluster heads and spatial correlation (inter-cluster) in processing nodes. Meanwhile, the detailed solving method is developed to recover original data and achieve the approximate data collection in sink node. Finally, simulation results indicate that the proposed layered compression scheme has better recovery performance as compared with traditional clustered compression schemes (i.e., achieving efficient data collection with high quality).

关键词： Compressed sensing data correlation multi-layer architecture data collection recovery error

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A Fast Quality Scalable Video Coding Method Based on Compressed Sensing

A Fast Quality Scalable Video Coding Method Based on Compres...

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2018 3rd International Conference on Electrical, Automation and Mechanical engineering(EAME 2018)

作者： Min Sun Dong Hu Jianyu Ding Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry's Engineering Research Center of Ubiquitous Network and Heath Service Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications

This paper presents a fast quality scalable video coding method based on compressed sensing(CS). The proposed method obtained the coding scheme of the enhancement MJU by using the interlayer and spatial correlation and kept the base layer's coding scheme unchanged. And the part in the enhancement layer which needed to be fine quantified was combined with the compressed sensing theory selectively which based on the sparsity of the signal and the complexity of the reconstruction. In order to satisfy the coding syntax structure of the reference software, the measurement value got by compressed sensing was complemented by 0 s and the flag bit was set to distinguish the special sub-blocks coded by CS. Experimental results show that the proposed algorithm can effectively improve the efficiency of scalable video coding and reduce the computational complexity.

关键词： video coding compressed sensing quality scalable video coding

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Towards a Smart Manufacturing Maturity Assessment Framework: A Socio-Technical Perspective

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Journal of Physics: Conference Series 2019年第4期1345卷

作者： Lei Yue Pengfei Niu Yifang Fang Zhonghua Han Sensor and Network Control Center Instrumentation Technology and Economy Institute Beijing 100055 China Information Center Instrumentation Technology and Economy Institute Beijing 100055 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang 110016 China

Researchers of information technology (IT) have often suggested that there is no clear relevance between the IT investment and return on investment (ROI) of enterprises. This phenomenon is called 'productivity paradox'. However, research on smart manufacturing capability maturity did not reflect empirically the fact that enterprises rarely benefit from information systems. Therefore, the aim of this article attempts to explore how humans and technologies are related and propose a smart manufacturing maturity assessment framework that can reveal the interaction between humans and technologies. This research addressed two questions, (a) what domains can be identified for smart manufacturing, and (b) how to harmonize all of the technical and social factors affecting maturity and benefits. A complicated concept 'socio-technical system' was surveyed for interpreting how enterprises benefit from technologies. Results of this study showed a smart manufacturing maturity assessment framework from the socio-technical perspective. As an explanation, the understanding of manufacturing operations management (MOM) capability maturity model (CMM) within the framework in the case study and its results were presented. To conclude, this study may be regarded as a meta-model or reference model for specific maturity models, as well as has the merit of offering valuable insights into the maturity assessment.

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BDTMS: Binomial Distribution-based Trust Management Scheme for Healthcare-oriented Wireless sensor network

BDTMS: Binomial Distribution-based Trust Management Scheme f...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Weidong Fang Chunsheng Zhu Wei Chen Wuxiong Zhang Joel J. P. C. Rodrigues Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology CAS Shanghai China Department of Electrical and Computer Engineering University of British Columbia Vancouver BC Canada School of Computer Science and Technology China University of Mining and Technology Xuzhou China Shanghai Research Center for Wireless Communication Shanghai China Instituto de Telecomunicações Portugal

Healthcare-oriented wireless sensor network (HWSN) is one of the applications of wireless sensor networks in e-health. It not only can better achieve the physiological information of people, but also more efficiently reduce the Iatency regarding information collection and transmission. However, similar to other distributed networks, it also faces enormous security challenges, especially from internal attacks. It is difficult to distinguish many attack behaviors from interference in the complex healthcare scenarios, such as On-Off attack. In this paper, we propose a Binomial Distribution-based Trust Management Scheme (BDTMS) for HWSN. The proposed method can rapidly detect and effectively defend against On-Off attacks. In addition, the proposed method is also applicable to defending against bad mouthing attacks. Simulation results show that, compared with the Time-window-based Resilient Trust Management Scheme (TRTMS), our proposed BDTMS achieves better performance in defending against On-Off attack under obstacle movement, especially with higher detection accuracy.

关键词： Wireless sensor networks Medical services Wireless communication Interference Encryption

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Application of composite hermitian operator eigenfunctions on analysis of RCS

Application of composite hermitian operator eigenfunctions o...

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2016 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2016

作者： Wang, You-Bao Wang, Xiang Rao, Yue-Fei Xiao, Shun Jiangsu Key Laboratory of Meteorological Observation and Information Processing Jiangsu Technology and Engineering Center of Meteorological Sensor Network Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9781467381949

The technique to integrate the composite hermitian operator eigenfunctions (CHOEs) with the general asymptotic waveform evaluation (GAWE) is proposed for computing the radar cross section (RCS) of a perfect electric conductor (PEC). In the analysis, the orthogonal and complete properties of the CHOEs are used to construct the solution space of a matrix equation. Hence, the solution of the equation can be obtained by combining the based-vectors of the solution space with a set of coefficients, which can be determined by the GAWE technique at a given frequency. The results of numerical examples prove that the novel technique is effective in computing RCS. © 2016 IEEE.

关键词： Radar cross section

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Exploiting Meta-Path with Attention Mechanism for Fine-Grained User Location Prediction in LBSNs

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Journal of Physics: Conference Series 2019年第1期1284卷

作者： Zhixiao Wang Wenyao Yan Wendong Wang Ang Gao Lei Yu Shaobo Yang GaoYang Nie School of Computer Science and Engineering Xi'an University of Technology 710048 Xi'an China Telematics Group the University of Goettingen 37077 Goettingen Germany Shaanxi Key Laboratory of Network Computing and Security 710048 Xi'an China School of Electronic and Information Engineering Xi'an Jiaotong University 710048 Xi'an China College of Xi'an Innovation Yan'an University 710100 Xi'an China Yan'an University Yan'an 716000 China National Satellite Meteorological Center China Meteorological Administration Beijing 100081 China

Based on the huge volumes of user check-in data in LBSNs, users' intrinsic mobility patterns can be well explored, which is fundamental for predicting where a user will visit next given his/her historical check-in records. As there are various types of nodes and interactions in LBSNs, they can be treated as Heterogeneous Information network (HIN) where multiple semantic meta-paths can be extracted. Inspired by the recent success of meta-path context based embedding techniques in HIN, in this paper, we design a deep neural network framework leveraging various meta-path contexts for fine-grained user location prediction. Experimental results based on two real-world LBSN datasets demonstrate the best effectiveness of the proposed approach using various evaluation metrics than others.

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