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12th International Conference on Genetic and Evolutionary Computing, ICGEC 2018

作者： Wu, Tsu-Yang Chen, Chien-Ming Wang, King-Hang Wu, Jimmy Ming-Tai Pan, Jeng-Shyang Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou350118 China Shenzhen518055 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9789811358401

In order to solve the integrity verification of outsourced file in cloud, we based on the concept of regenerating code (RC) to propose a new public auditing scheme with data recovery in this paper. With the advantage of RC, our scheme provides a (k,n) recovery functionality, i.e., only encoded data blocks from any k cloud servers, user can recover the original data files, where n denotes the total number of cloud servers and k ≤ n. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Recovery

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Security analysis of a public key authenticated encryption with keyword search scheme 14th

Security analysis of a public key authenticated encryption w...

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14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2018

In order to solve the security problem that off-line keyword guessing attacks existed in PEKS or dPEKS scheme, Huang and Li introduced a new security model called PAEKS. In this paper, we show that their scheme didn’... 详细信息

ISBN: (纸本)9783030037444

关键词： Search engines

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Collaborative Three-Tier Architecture Non-contact Respiratory Rate Monitoring using Target Tracking and False Peaks Eliminating Algorithms

arXiv

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arXiv 2020年

作者： Mo, Haimiao Ding, Shuai Yang, Shanlin Vasilakos, Athanasios V. Zheng, Xi The School of Management Hefei University of Technology Anhui Hefei23009 China The Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education China The National Engineering Laboratory of Big Data Distribution and Exchange Technologies China Grimstad Norway The College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China The School of Computing Macquarie University Sydney Australia

Monitoring the respiratory rate is crucial for helping us identify respiratory disorders. Devices for conventional respiratory monitoring are inconvenient and scarcely available. Recent research has demonstrated the ability of non-contact technologies, such as photoplethysmography and infrared thermography, to gather respiratory signals from the face and monitor breathing. However, the current non-contact respiratory monitoring techniques have poor accuracy because they are sensitive to environmental influences like lighting and motion artifacts. Furthermore, frequent contact between users and the cloud in real-world medical application settings might cause service request delays and potentially the loss of personal data. We proposed a non-contact respiratory rate monitoring system with a cooperative three-layer design to increase the precision of respiratory monitoring and decrease data transmission latency. To reduce data transmission and network latency, our three-tier architecture layer-by-layer decomposes the computing tasks of respiration monitoring. Moreover, we improved the accuracy of respiratory monitoring by designing a target tracking algorithm and an algorithm for eliminating false peaks to extract high-quality respiratory signals. By gathering the data and choosing several regions of interest on the face, we were able to extract the respiration signal and investigate how different regions affected the monitoring of respiration. The results of the experiment indicate that when the nasal region is used to extract the respiratory signal, it performs experimentally best. Our approach performs better than rival approaches while transferring fewer data. © 2020, CC BY.

关键词： Edge computing

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BookChain: Library-Free Book Sharing Based on Blockchain technology

BookChain: Library-Free Book Sharing Based on Blockchain Tec...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Jiajie Zeng Xiaohai Dai Jiang Xiao Wenhui Yang Weifeng Hao Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728152127

ISBN: (纸本)9781728152134

Modern bookcrossing leverages the mobile networks to help readers share books via convenient connection, and thus expedites the dissemination of information. However, the lack of traceability has significantly hindered the wide adoption of mobile bookcrossing, leading to loss of books. Meanwhile, the managerial inefficiency of current mobile bookcrossing systems becomes another obstacle for advancing the book circulation. To overcome these problems, we propose to leverage the promising blockchain technology with the merits of its immutability and cryptographic smart contract. In this paper, we present BookChain, a traceable and efficient blockchain-based innercampus book sharing system. BookChain stores the complete sharing data of an interested book permanently on blockchain, such that every reader can trace the borrowing history, which reduces the potential for loss of book. BookChain also introduces the use of smart contract to automate the circulation of books with minimal human intervention, resulting in the improvement of efficiency. The experimental results show the effectiveness and low-cost of the proposed system under high concurrent users.

关键词： Contracts Web servers Web pages

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FLoc: Fingerprint-Based Indoor Localization System under a Federated Learning Updating Framework

FLoc: Fingerprint-Based Indoor Localization System under a F...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Yuxiang Liu Huichuwu Li Jiang Xiao Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781728152127

ISBN: (纸本)9781728152134

Fingerprinting-based indoor localization via WiFi has achieved a great breakthrough in the past decade. However, it suffers from an inherent problem that the localization accuracy declines sharply over time due to the dynamic environment and unstable WiFi devices. Researchers have designed many methods to update the localization model, e.g., crowdsourcing-based model updating, in order to maintain the localization accuracy. Unfortunately, they have not taken the privacy into consideration during the updating process. This will lead to a threat that the eavesdroppers could guess the location providers' private information according to the updating model. For the goal of maintaining the localization accuracy without the risk of privacy breaching, we proposed FLoc, a fingerprinting-based indoor localization system which updates the localization model via a federated learning framework. In FLoc, every provider maintains a local localization model in their own device. They will regularly encrypt the updating parameters and share them to a common model server. At the model server, it aggregates the encrypted information of the local models to maintain a general model, which will be sent back to the local devices for next updating iteration. We evaluate FLoc in an APs unknown laboratory corridor. The experiment results show that FLoc has a comparable localization performance. Moreover, it can successfully protect the providers' privacy, since the information transferred is all encrypted.

关键词： Mobile handsets Privacy Fingerprint recognition Servers Wireless fidelity databases Computational modeling

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HiNUMA: NUMA-Aware data Placement and Migration in Hybrid Memory Systems

HiNUMA: NUMA-Aware Data Placement and Migration in Hybrid Me...

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IEEE International Conference on Computer Design: VLSI in Computers and Processors, (ICCD)

作者： Zhuohui Duan Haikun Liu Xiaofei Liao Hai Jin Wenbin Jiang Yu Zhang National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Non-uniform memory access (NUMA) architectures feature asymmetrical memory access latencies on different CPU nodes. Hybrid memory systems composed of non-volatile memory (NVM) and DRAM further diversify memory access latencies due to the relatively large performance gap between NVM and DRAM. Traditional NUMA memory management policies fail to manage hybrid memories effectively and may even hurt application performance. In this paper, we present HiNUMA, a new NUMA abstraction for memory allocation and migration in hybrid memory systems. HiNUMA advocates NUMA topologyaware hybrid memory allocation policies for the initial data placement. HiNUMA also proposes a new NUMA balancing mechanism called HANB for memory migration at runtime. HANB considers both data access frequency and memory bandwidth utilization to reduce the cost of memory accesses in hybrid memory systems. We evaluate the performance of HiNUMA with several typical workloads. Experimental results show that HiNUMA can effectively utilize hybrid memories, and deliver much higher application performance than conventional NUMA memory management policies and other state-of-the-art work.

关键词： Nonvolatile memory Random access memory Bandwidth Memory management Resource management Task analysis Memory architecture

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Reasoning Based Workload Performance Prediction in Cloud data Centers

Reasoning Based Workload Performance Prediction in Cloud Dat...

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IEEE International Conference on Cloud Computing technology and Science

作者： Adeel Aslam Hanhua Chen Jiang Xiao Hai Jin National Engineering Research Center for Big Data Technology and System Cluster and Grid Computing Lab Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Cloud computing provides utility-based and scalable services to end-users. In the past decade, the demands for resource management in cloud computing have increased substantially which lead to certain challenges such as optimal resource utilization, power consumption, and service level agreement violations. Workload performance prediction serves as an assistance to address these issues. In this paper, we propose a prediction model based on clustered Case-Based Reasoning (CBR). The proposed model determines the performance metrics for workload prior to the co-operation of autonomic computing characteristics. Thus, CBR provides optimal scheduling of resources and workload monitoring for cloud data centers. In order to validate the proposed CBR-based prediction model, we perform a series of experiments and evaluate the effectiveness in terms of precision, recall, f-measure, and mean square error rate. We generate the cases for CBR using traces from the Google cluster data center. Moreover, we also validate our proposed prediction model against Support Vector Machine (SVM) prediction scheme. Experimental results show that the proposed CBR outperforms the SVM-based approach and yields 10% improvement in terms of precision.

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Energy Saving Strategy of Power System Cluster Based on Container Virtualization

Energy Saving Strategy of Power System Cluster Based on Cont...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Ran Zheng Hao Wang Hai Jin Dechao Xu Yong Chen Xiaomeng Li Yufei Rao Zhenan Zhang National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory of Power Grid Safety and Energy Conservation China Electric Power Research Institute Haidian District Beijing China State Grid Henan Electric Power Company Electric Power Research Institute Zhengzhou China

ISBN: (数字)9781728167824

ISBN: (纸本)9781728167831

With the continuous development of power grids, the scale of supercomputing clusters has also gradually increased to carry a large number of power system simulation calculations, and the problem of high energy consumption has appeared. To solve this problem, we propose a container virtualization-based supercomputing cluster for power system. We analyze the impact of containers on power simulation calculations and compare the energy consumption effects of various container scheduling and migration algorithms on clusters. Experiments show that compared to virtual machines with hypervisor, which consumes massive resources and reduces performances by 28.4%, the performance degradation of container on power simulation calculation is 1.3%, which can be ignored. The energy consumption of load-concentration or resource-and-load-balance container scheduling algorithms is up to 4.0% lower and at least 2.2% lower than other algorithms. In container migration, the method combining autoregressive model with most-correlation and resource-andload-balance algorithms is better than other methods, which not only minimizes energy consumption, but also has lowest number of migrations and SLA violations. Experiments verify the feasibility and advantages of container migration in power system computing clusters.

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Research on the MEG of depression patients based on multivariate TE partial information decomposition

Research on the MEG of depression patients based on multivar...

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作者： Zihan Chen Yunjie Fang Wei Yan Jun Wang Jin Li Fengzhen Hou Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Department of Psychiatry The Affiliated Brain Hospital of Nanjing Medical University College of Physics and Information Technology Shaanxi Normal University Key Laboratory of Biomedical Functional Materials China Pharmaceutical University

Transfer entropy（TE） has been broadly used in the field of *** this paper,the partial information decomposition algorithm is employed to decompose multivariate TE into synergistic,redundant and unique *** this work,the synergistic part is believed as more suitable as the computation *** recorded the magnetoencephalogram（MEG） data of 6 subjects with depression and 13 normal subjects under different emotional stimulations,and studied the coupling between multiple symmetric channels in the frontal area in the brain of *** experimental results show that under different emotional stimulations,normal people present significant difference from the depression patients,especially in the right frontal ***,under negative emotional stimulation,the difference in synergistic value between normal people and depression patients is *** synergistic value of depression patients has become bigger,which indicates that the brain complexity of depression patients has grown,and their brain activities have increased.

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Exploring the Pan-Relationship Between Disease and Symptom Related to Coronary Heart Disease from Chinese Electronic Medical Records 15th

Exploring the Pan-Relationship Between Disease and Symptom R...

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Yang, Ronggen Wang, Yichen Wang, Bo Gong, Lejun Faculty of Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing211169 China Jiangsu Key Lab of Big Data Security and Intelligent Processing School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210046 China School of Geography and Bioinformatics Nanjing University of Posts and Telecommunication Nanjing China

ISBN: (纸本)9783030267650

Electronic Medical Records (EMRs) arises from the clinical treatment process, which reflects a patient’s physical condition, the disease, the treatment process, etc. It has an important significance for the recovery of the patient. As the amount of electronic medical records continues to increase, people are actively looking for ways to get the valid data contained in electronic medical records. More effective methods are urgently needed for processing EMRs. In this paper, 108 real EMRs of coronary heart disease were analyzed, through named entity recognition and entity relation extraction. Pan-relationship between entities was defined in the process. Experimental results showed the analysis of pan-relation between coronary heart disease and symptom is helpful for treatment of coronary heart disease. © 2019, Springer Nature Switzerland AG.

关键词： Diseases

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