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检索条件"任意字段=21st International Symposium on Computer Architecture and High Performance Computing"

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CROA: A content-based recommendation optimization algorithm for personalized knowledge services 21

CROA: A content-based recommendation optimization algorithm ...

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21st IEEE international Conference on high performance computing and Communications, 17th IEEE international Conference on Smart City and 5th IEEE international Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Sun, Xiao Xu, Xiaolong Xia, Fei Jiangsu Key Laboratory Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Information and communication Branch State Grid Jiangsu Electric Power Company Nanjing China

ISBN: (纸本)9781728120584

Information explosion is a typical feature of the Big data. Learners can easily find a wide variety of knowledge information online. However, the expansion of information also makes it difficult for learners to retrieve the information they want and fall into the problem of knowledge overload. In order to solve this problem effectively, we propose a content-based recommendation optimization algorithm for personalized knowledge services (CROA). First, the feature vector model is established, where each item information is represented by specific words and key information is highlighted by weighting. Second, a dynamic user vector model is then established to capture the latest preference information of the user. Finally, the feature vector model is combined with the multi-user comparison results thereby obtaining a list of recommendations. Experimental results indicate that CROA outstands in knowledge recommendation mechanism and can also alleviate knowledge overload. © 2019 IEEE.

关键词： Optimization

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Fast recovery for single link failure with segment routing in SDNs 21

Fast recovery for single link failure with segment routing i...

引用

作者： Wang, Shishuang Xu, Hongli Huang, Liusheng Yang, Xuwei Liu, Jianchun School of Computer Science and Technology University of Science and Technology of China Hefei230027 China

ISBN: (纸本)9781728120584

Link failure is a major problem that must be addressed, which occurs frequently in large networks. In a software-defined network, the recovery scheme for single link failure can be divided into two categories: proactive and reactive. For reactive scheme, it takes a long time to recover due to the controller participation. Though the proactive scheme can achieve faster recovery, it may consume a large number of forwarding rules, which is typically limited on switches due to expensiveness and power hungry. Therefore, this paper proposes a proactive recovery scheme for single link failure based on segment routing with less forwarding rules. In the proposed scheme, we regard the affected flows through the same link as an aggregated flow and use the link protection methods to achieve link failures recovery. The link protection methods calculate backup paths for each link of the working path, so we propose the backup paths calculation problem and formulate it as an mixed integer non-linear programming model. To solve the problem and avoid link congestion, we design an efficient algorithm to select the most appropriate backup path. In addition, due to the limitation of the maximal number of MPLS labels that the packet header can hold, we design an algorithm to divide the working and backup path into segments to meet the hardware requirements. The simulation results show that the proposed algorithms outperform CAFFE and SPR by 14.7% and 77.1% on recovery time, and outperform CAFFE by 21.5% on forwarding rules consumption. Moreover, the proposed scheme does not cause congestion in post-recovery network. © 2019 IEEE.

关键词： Integer programming

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MRDGC: A parallel approach for the identification of master regulators based on the differently expressed genes and the regulatory capacity of regulators 21

MRDGC: A parallel approach for the identification of master ...

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作者： Sun, Mingming Luo, Jiawei Tu, Nguyen Hoang College of Computer Science and Electronic Engineering Hunan University Changsha China Collaboration and Innovation Center Digital Chinese Medicine in Hunan Province Hunan University Changsha China Faculty of Information and Technology Hanoi University of Industry Hanoi Viet Nam

ISBN: (纸本)9781728120584

Master regulators play a major role in most survival and development process of living organisms. Identifying the master regulators provides great insight into analyzing diseases and designing drugs. Many computational strategies for master regulators identification have been put forward based on the expression profiles and single relations among transcription factors (TFs), microRNAs (miRNAs) and genes. However, the regulatory relations are sparse and most methods can only recognize one of transcription factors or miRNAs with inaccurate parameters. In this article, we present a novel nonparametric parallel approach for the identification of master regulators based on the differentially expressed genes and the regulatory capacity of regulatory factors, called MRDGC. The regulators having significant meaning in Wilcoxon rank-sum test are selected as candidate master regulators in parallel and the master regulators are the TOP k candidate master regulators ranked ascending by statistical values. In the computational experiments, MRDGC achieves good robustness and outperforms most of methods in breast and thyroid cancer. Moreover, a detailed case study on breast cancer demonstrates the ability of MRDGC for uncovering master regulators. MRDGC is implemented in MATLAB and available to download at https://***/sunmingming99/MRDGC. © 2019 IEEE.

关键词： Transcription factors

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A source code analysis method with parallel acceleration for mining MPI application communication counts 21

A source code analysis method with parallel acceleration for...

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作者： Zhang, Rui Xiao, Limin Yan, Baicheng Wei, Bing Zhou, Yi Wang, Dong School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781728120584

MPI(Message Passing Interface) applications are widely used to solve complex problems in the field of science and engineering. In addition to calculation information concerns, communication information is also an important focal point for MPI application analysis. The communication information is generally obtained through manual reviewing the source code, which is impractical for complex applications. Another way is to develop an instrumentation library and compile the target application with the library. Despite the communication information can be accurately obtained by this type of methods, the target application must be executed. To address these issues, in this paper, a source code analysis method is proposed to get the MPI applications communication information, which does not need to execute the target application and can work with general computers. Furthermore, a parallel strategy is presented to accelerate the source code analysis process. Two frequently-used communication patterns are used to evaluate the proposed method. The experimental results show that the method proposed in this paper not only can be ran on general computers, but also reduce the analysis overhead, and can also achieve efficiency advantages in the MPI applications with large message size. © 2019 IEEE.

关键词： Message passing

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An adaptive flow table adjustment algorithm for SDN 21

An adaptive flow table adjustment algorithm for SDN

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作者： Xu, Xiaolong Hu, Liuyun Lin, Haowei Fan, Zexuan School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China Jiangsu Key Laboratory of Big Data Security Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781728120584

SDN (Software-defined networking) are important for current network systems, such as cloud systems. The characteristics of flow in SDN and the impact of flow table entries and controllers on data packet transmission are analyzed. We propose an adaptive flow table adjustment algorithm for SDN called CFC (Combine flow table and controller). It is important for CFC to monitor the network traffic in real time. According to the proportion of active flow entries in the OpenFlow switch, the value of idle-timeout will be set dynamically based on the characteristics of different data flows. When the switch forwards packets, it will minimize the calculation load of controller, and allocate a reasonable value of idle-timeout to the idle flow table entries. So it can delete discarded flow table entries in time and improve the hit rate of data packets. The experiments show that the utilization rate of the flow table resource is enhanced. With the improvement of data packets' forwarding rate, the average throughput of the network has also increased. At the same time, it can also cope with the burst traffic in SDN and ensure them to be forwarded normally and effectively. © 2019 IEEE.

关键词： Controllers

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performance Evaluation of 5G mmWave Networks with Physical-Layer and Capacity-Limited Blocking

Performance Evaluation of 5G mmWave Networks with Physical-L...

引用

IEEE Workshop on high performance Switching and Routing

作者： Jingjin Wu Meiqian Wang Yin-Chi Chan Eric W. M. Wong Taejoon Kim Department of Statistics BNU-HKBU United International College Zhuhai Guangdong P. R. China Department of Electrical Engineering City University of Hong Kong Hong Kong SAR P. R. China Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

The following topics are dealt with: telecommunication traffic; IP networks; virtualisation; telecommunication computing; telecommunication network routing; computational complexity; telecommunication scheduling; clou... 详细信息

ISBN: (数字)9781728148465

ISBN: (纸本)9781728148472

关键词： 5G mobile communication stochastic processes Computational modeling Physical layer Wireless networks Interference performance evaluation

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An aging-aware routing algorithm for improving reliability in noc-based multicore systems 21

An aging-aware routing algorithm for improving reliability i...

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作者： Yin, Lu Zhang, Yi Zhou, Junlong Chang, Qing Sun, Jin School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9781728120584

As the interconnection scale of network-on-chip (NoC)-based multicore systems becomes more complicated and the characteristic size of the transistor continues to shrink, aging-induced reliability issues has become the main concerns in today's NoC design paradigm. Considering the NBTI aging effect upon NoC routers, this paper proposes an aging-aware routing algorithm that aims to improve the reliability of NoC system while optimizing routing power consumption. The proposed method introduces an concept of aging factor (AF) to evaluate the stress level for each router. We further formulate a rigorous optimization model that imposes a constraint upon NoC router's utilization according to its AF metric. The optimization model is to determine an optimized routing solution such that the total power consumption for all routers is minimized under the AF constraints. To solve the formulated optimization problem, we develop an efficient routing algorithm based upon the search strategy of ant colony optimization. The routing solution obtained by the aging-aware algorithm is beneficial for improving the reliability of NoC system by ensuring lower utilization of stressed routers. Experimental results demonstrate that, compared with the non-aging-aware routing strategy, the proposed algorithm can significantly improve system reliability with an insignificant increase in total power consumption. © 2019 IEEE.

关键词： Network-on-chip

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Multi-resource fair allocation for cloud federation 21

Multi-resource fair allocation for cloud federation

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作者： Zhang, Gengwei Lu, Runhao Wu, Weigang School of Data and Computer Science Sun Yet-Sen University Guangzhou China Guangdong Province Key Lab. of Big Data Analysis and Processing Sun Yet-Sen University Guangzhou China

ISBN: (纸本)9781728120584

Since the number of tasks submitted by user changes with time, the cloud data center cannot meet all resource requests in time when the load is high, and the idle resources are not effectively utilized at low load. Cloud federation can be established to share resources between different Cloud Service Providers (CSPs), enabling load balance between clouds. CSPs in the cloud federation are independent and their individual benefit need to be guaranteed when sharing resources with others. In this paper, we establish a two-level asynchronous scheduling model within and between the clouds, and introduce high priority queues in the cloud to prioritize the tasks sent by the federation scheduler. Due to the heterogeneity of resource requirements of user tasks, we design two multi-resource fair scheduling algorithms for cloud and federation. Within the cloud, we add the dynamically adjusted weighting factor to the Dominant Resource Fairness (DRF) to increase the priority of user whose task is outsourced. We define the dominant share and dominant contribution of the cloud. The priority of the cloud is the difference between the dominant share and the dominant contribution, which ensure the incentive and fairness of the cloud. Based on the open source container management system Kubernetes, we develop a cloud federation prototype system to implement our algorithm, and conduct performance evaluations through experiments. The results show that, compared with the existing fair allocation algorithm, the multi-resource fair allocation mechanism proposed in this paper can guarantee users' QoS of each CSP. © 2019 IEEE.

关键词： Scheduling

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An apache spark-based platform for predicting the performance of undergraduate students 21

An apache spark-based platform for predicting the performanc...

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作者： Mai, Thong Le Do, Phat Thanh Chung, Minh Thanh Thoai, Nam Faculty of Computer Science and Engineering Ho Chi Minh University of Technology Viet Nam

ISBN: (纸本)9781728120584

Nowadays, Education Data Mining (EDM) plays a very important role in higher education institutions. Plenty of algorithms have been employed to measure student's GPA in the next semester's courses. The results can be used to early identify dropout students or help students choose the elective courses which are appropriate for them. The most widely used methods are machine learning, however, the problem is the accuracy which can be changed from dataset to dataset. More importantly, the performance of prediction models can be affected by the characteristic of dataset associated with the applied model. In this paper, we build a distributed platform on Spark to predict missing grades of elective courses for undergraduate students. The paper compares several methods that are based on the combination of Collaborative Filtering & Matrix Factorization (namely Alternative Least Square). We evaluate the performance of these algorithms using a dataset provided by Ho Chi Minh University of Technology (HCMUT). The dataset consists of information about undergraduate students from 2006 to 2017. Depending on the characteristics of our dataset, the paper highlights that Alternative Least Square with non-negative constraint achieves the better results than others in comparison. © 2019 IEEE.

关键词： Forecasting

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Towards optimal incentive-driven verification in social sensing based smart city applications 21

Towards optimal incentive-driven verification in social sens...

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作者： Vance, Nathan Zhang, Daniel Zhang, Yang Wang, Dong Department of Computer Science and Engineering University of Notre Dame Notre DameIN United States

ISBN: (纸本)9781728120584

Social sensing has emerged as a new smart city application paradigm that achieves low deployment costs by leveraging privately owned edge devices for data collection and processing. Unfortunately, such an application paradigm is vulnerable to result spoofing, where attackers fabricate computation results and convince the server that they are valid. This problem has not been adequately addressed due to three important challenges. First, the raw data originates at the edge, and therefore the application server cannot directly verify the computed results sent by the edge devices without receiving the raw data as well. Second, personally owned edge devices can easily collude to convince the server that fabricated results are real, even under sophisticated scrutiny. Third, the high level of churn common in such systems nullifies established reputation-based schemes. To address the above challenges we develop a novel incentive-driven verification system in which risk is minimized under a budget constraint. We compare our solution to state-of-the-art computation verification schemes through an extensive evaluation. The results show that our solution achieves the least risk of computation spoofing under a constrained budget when compared to all of the baselines. © 2019 IEEE.

关键词： Edge computing

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