检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

1,417 篇 会议
44 册 图书
28 篇 期刊文献

馆藏范围

1,489 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

972 篇 工学
- 891 篇 计算机科学与技术...
- 487 篇 软件工程
- 377 篇 信息与通信工程
- 114 篇 电气工程
- 89 篇 控制科学与工程
- 39 篇 电子科学与技术（可...
- 31 篇 生物工程
- 28 篇 动力工程及工程热...
- 21 篇 机械工程
- 20 篇 仪器科学与技术
- 19 篇 生物医学工程（可授...
- 18 篇 网络空间安全
- 16 篇 环境科学与工程（可...
- 15 篇 建筑学
- 10 篇 安全科学与工程
- 8 篇 化学工程与技术
218 篇 管理学
- 164 篇 管理科学与工程(可...
- 78 篇 工商管理
- 75 篇 图书情报与档案管...
203 篇 理学
- 124 篇 数学
- 43 篇 系统科学
- 34 篇 生物学
- 25 篇 统计学（可授理学、...
- 24 篇 物理学
- 11 篇 化学
18 篇 法学
- 14 篇 社会学
10 篇 经济学
- 10 篇 应用经济学
10 篇 医学
- 10 篇 临床医学
- 8 篇 基础医学(可授医学...
9 篇 教育学
- 9 篇 教育学
2 篇 军事学
1 篇 农学

主题

112 篇 distributed comp...
92 篇 distributed comp...
55 篇 computer science
55 篇 cloud computing
50 篇 application soft...
48 篇 peer to peer com...
44 篇 computer network...
41 篇 computer archite...
41 篇 mobile computing
40 篇 conferences
40 篇 costs
40 篇 middleware
35 篇 protocols
33 篇 quality of servi...
33 篇 computational mo...
30 篇 software enginee...
30 篇 bandwidth
29 篇 internet
29 篇 hardware
28 篇 resource managem...

机构

6 篇 college of compu...
5 篇 seikei universit...
5 篇 ibm thomas j. wa...
5 篇 inria rennes
5 篇 3-30-1 wajiro-hi...
4 篇 nanyang technol ...
4 篇 universidad carl...
4 篇 tokyo denki univ...
4 篇 rissho universit...
4 篇 school of electr...
3 篇 college of compu...
3 篇 school of big da...
3 篇 department of co...
3 篇 zhejiang univers...
3 篇 department of co...
3 篇 school of cybers...
3 篇 ohio state univ ...
3 篇 university of pi...
3 篇 tennessee tech u...
3 篇 rwth aachen univ...

作者

8 篇 michael alexande...
6 篇 stephen l. scott
6 篇 barolli leonard
6 篇 mario cannataro
6 篇 takizawa makoto
4 篇 xhafa fatos
4 篇 alexandru costan
4 篇 liu yh
4 篇 emmanuel jeannot
4 篇 shibata yoshitak...
4 篇 marco danelutto
4 篇 uehara minoru
4 篇 mikkilineni rao
4 篇 r. guerraoui
4 篇 beniamino martin...
4 篇 josef weidendorf...
4 篇 durresi arjan
3 篇 li zengxiang
3 篇 alfredo cuzzocre...
3 篇 m. takizawa

语言

1,481 篇 英文
5 篇 其他
2 篇 俄文
1 篇 中文

检索条件"任意字段=Proceedings - 24th International Conference on Distributed Computing Systems Workshops"

共 1489 条记录，以下是261-270 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

A Zone Reference Model for Enterprise-Grade Data Lake Management

A Zone Reference Model for Enterprise-Grade Data Lake Manage...

引用

international conference on Enterprise distributed Object computing (EDOC)

作者： Corinna Giebler Christoph Gröger Eva Hoos Holger Schwarz Bernhard Mitschang University of Stuttgart Stuttgart Germany Robert Bosch GmbH Stuttgart Germany

ISBN: (数字)9781728164731

ISBN: (纸本)9781728164748

Data lakes are on the rise as data platforms for any kind of analytics, from data exploration to machine learning. they achieve the required flexibility by storing heterogeneous data in their raw format, and by avoiding the need for pre-defined use cases. However, storing only raw data is inefficient, as for many applications, the same data processing has to be applied repeatedly. To foster the reuse of processing steps, literature proposes to store data in different degrees of processing in addition to their raw format. To this end, data lakes are typically structured in zones. there exists various zone models, but they are varied, vague, and no assessments are given. It is unclear which of these zone models is applicable in a practical data lake implementation in enterprises. In this work, we assess existing zone models using requirements derived from multiple representative data analytics use cases of a real-world industry case. We identify the shortcomings of existing work and develop a zone reference model for enterprise-grade data lake management in a detailed manner. We assess the reference model's applicability through a prototypical implementation for a real-world enterprise data lake use case. this assessment shows that the zone reference model meets the requirements relevant in practice and is ready for industry use.

关键词： Lakes Data models Data analysis Analytical models Industries Business Real-time systems

来源：评论

学校读者我要写书评

暂无评论

ETRA: Efficient three-Stage Resource Allocation Auction for Mobile Blockchain in Edge computing 24

ETRA: Efficient Three-Stage Resource Allocation Auction for ...

引用

24th IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Xia, Chengpeng Chen, Hui Liu, Xuelian Wu, Jigang Chen, Long Guangdong Univ Technol Sch Comp Sci & Technol Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781538673089

Blockchain technology is emerging in various fields, to guarantee security of digital currency and internet of things. In this paper, we provide incentive to encourage edge servers to serve mobile users for the mobile blockchain application. We formulate the problem as a resource allocation problem, then we propose a three-stage auction to implement resource allocation specially designed for mobile blockchain, and introduce the group-buying mechanism to motivate mobile users. We prove that our auction scheme is truthful, individual rationality, and computational efficiency. We compare proposed scheme with TACD and HAF mechanisms, and simulation results show that the social welfare achieved by our scheme is higher than that of TACD and HAF mechanisms.

关键词： mobile blockchain edge computing auction resource allocation mining

来源：评论

学校读者我要写书评

暂无评论

Mobility-Aware Video Prefetch Caching and Replacement Strategies in Mobile-Edge computing Networks 24

Mobility-Aware Video Prefetch Caching and Replacement Strate...

引用

24th IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Liu, Wei Jiang, Yisheng Xu, Shanjie Cao, Guangyi Du, Wei Cheng, Yu Wuhan Univ Technol Sch Comp Sci Wuhan Hubei Peoples R China

ISBN: (纸本)9781538673089

the drastic increase of mobile video traffic has resulted in communication delay and slow download speed. In the 5G wireless networks, caching or prefetching video at mobile edge servers can take advantage of the high-speed local link to alleviate the load of the core network. However, the trade-off between data prefetching and cache replacement strategy is still a challenge in Mobile-edge computing networks, especially when the users are mobile and cache size is constrained. To address this, we design a mobility-aware utility function based on the user's moving probability and the popularity of video clips. then, we formulate the optimization problem as an integer linear programming (ILP) with a set of knapsack constraints to develop an efficient dynamic programming algorithm. Compared with the baseline algorithm, the results of simulation experiment show that our approach can not only raise the hit rate by 24.93%, but also control the cost effectively. In the meantime, video distortion reduction is increased by 21.26% on average as well.

关键词： Mobile edge computing replacement strategy mobility-aware prefetching and caching trade-off

来源：评论

学校读者我要写书评

暂无评论

Collecting, Monitoring, and Analyzing Facility and systems Data at the National Energy Research Scientific computing Center 19

Collecting, Monitoring, and Analyzing Facility and Systems D...

引用

48th international conference on Parallel Processing (ICPP)

作者： Bautista, Elizabeth Romanus, Melissa Davis, thomas Whitney, Cary Kubaska, theodore Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Rutgers State Univ New Brunswick NJ USA Energy Efficiency HPC Working Grp EE HPC WG Berkeley CA USA

ISBN: (纸本)9781450371964

As high-performance computing (HPC) resources continue to grow in size and complexity, so too does the volume and velocity of the operational data that is associated with them. At such scales, new mechanisms and technologies are required to continuously gather, store, and analyze this data in near-real time from heterogeneous and distributed sources without impacting the underlying data center operations or HPC resource utilization. In this paper, we describe our experiences in designing and implementing an infrastructure for extreme-scale operational data collection, known as the Operations Monitoring and Notification Infrastructure (OMNI) at the National Energy Research Scientific computing (NERSC) center at Lawrence Berkeley National Laboratory. OMNI currently holds over 522 billion records of online operational data (totaling over 125TB) and can ingest new data points at an average rate of 25,000 data points per second. Using OMNI as a central repository, facilities and environmental data can be seamlessly integrated and correlated with machine metrics, job scheduler information, network errors, and more, providing a holistic view of data center operations. To demonstrate the value of real-time operational data collection, we present a number of real-world case studies for which having OMNI data readily available led to key operational insights at NERSC. the case results include a reduction in the downtime of an HPC system during a facility transition, as well as a $2.5 million electrical substation savings for the next-generation Perlmutter HPC system.

关键词： data centers operations monitoring high-performance computing data collection operational data analytics time series data Green HPC

来源：评论

学校读者我要写书评

暂无评论

the Case of a Novel Operational distributed Storage Service for Big Data in a Semiconductor Wafer Fabrication Foundry 24

The Case of a Novel Operational Distributed Storage Service ...

引用

24th IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Chang, Andy R. K. Chen, Yu-Ling Huang, Yen-Zhou Hsiao, Hung-Chang Hsu, Michael Lee, Chia-Chee Lee, Hsin-Yin Shih, Wei-An Su, Huan-Ping Tsai, Chia-Ping Tseng, Kuan-Po United Microelect Corp Div Informat Technol Hsinchu Taiwan Natl Cheng Kung Univ Comp Sci & Informat Engn Tainan Taiwan Apache HBase Committer & Project Management Comm Tainan Taiwan

ISBN: (纸本)9781538673089

We present in this paper a novel infrastructural service based on Hadoop for big data storage and computing in a Taiwan's semiconductor wafer fabrication foundry. the service is named Hadoop data service (HDS), which has been built and operated in production systems for 3.5 years. It evolves over time by incrementally accommodating users' requirements. HDS is a web-based distributed big data storage facility. Users simply rely on HDS to access data objects stored in Hadoop with the HTTP protocol. In addition, HDS is scalable and reliable. Moreover, HDS is efficient and effective by intelligently selecting either Hadoop distributed file system (HDFS) or database (HBase) for publishing data objects. Specifically, HDS is transparent to existing analytics and data inquiry applications, such as Spark and Hive. this paper discusses the design and implementation features for HDS. the performance metrics of HDS are also demonstrated.

关键词： Hadoop Big data storage distributed file systems distributed databases Web service computing Middleware

来源：评论

学校读者我要写书评

暂无评论

An Efficient Segment Grouping Approach for Active Disk-based Storage systems 24

An Efficient Segment Grouping Approach for Active Disk-based...

引用

24th IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Xu, Quanqing Xi, Weiya Yong, Khai Leong Jin, Chao ASTAR Inst High Performance Comp Singapore Singapore ASTAR Data Storage Inst Singapore Singapore ASTAR Inst Infocomm Res Singapore Singapore

ISBN: (纸本)9781538673089

Active storage is an excellent big data storage and analysis platform by exploring storage nodes' computing resources since it especially fits read-intensive operations. Active disks have a similar idea with active storage except utilizing the computing resources embedded in disk drives. Active disk-based storage systems have to evenly distribute data and workload among many storage devices so that we could efficiently use available resources to maximize system performance. We propose an efficient Segment Grouping (SG) approach in this paper. SG is a pseudo-random data distribution approach that is designed for active disk-based storage architecture. It is excellent at load balancing because it utilizes hash functions. Any party can independently compute the location of any data segment. SG efficiently maps segment objects to storage devices using the hash functions, and it only needs a compact and hierarchical description of storage devices in the active disk-based storage system. It only needs knowledge of the segment placement policy, and all the required nietadata is little and mostly static. Our experimental results demonstrate that it is efficient and scalable by conducting performance evaluation.

关键词： Disk drives Hash functions Computer architecture Metadata distributed databases Reed-Solomon codes Load management

来源：评论

学校读者我要写书评

暂无评论

GraphEL: A Graph-based Ensemble Learning Method for distributed Diagnostics and Prognostics in the Industrial Internet of things 24

GraphEL: A Graph-based Ensemble Learning Method for Distribu...

引用

24th IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Zhou, Chongyu tham, Chen-Khong Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore

ISBN: (纸本)9781538673089

Ensemble learning (EL) methods have been shown to be effective for diagnostics and prognostics in industrial systems. By combining the learning ability of different base learners, EL has the potential to reduce the total complexity of the learning system while solving a difficult problem satisfactorily. Recent advantages in Industrial Internet of things (IIoT) and edge computing technologies have started a new paradigm of distributed diagnostics and prognostics. However, existing EL methods that mainly focus on a centralized setting cannot adapt to the edge computing scenario, which significantly constrains the application of these EL methods in real industrial environments. In this paper, we present a new approach to EL called Graph-based Ensemble Learning (GraphEL) to enable distributed diagnostics and prognostics in real industrial environments. Comparing with existing methods, the proposed GraphEL framework builds different base learners for different subsystems. Furthermore, a graphical model is constructed to define the correlation structures among the outputs of different base learners in the ensemble such that they can be collaboratively trained to optimize the learning performance of the ensemble. Via simple message passing, the proposed GraphEL framework can be executed in a fully distributed manner which is suitable for edge computing. the performance of the proposed GraphEL framework is evaluated using two real-world industrial data sets where we demonstrate the advantages of GraphEL compared to existing EL methods.

关键词： Industrial Internet of things (IIoT) smart manufacturing diagnostics and prognostics distributed ensemble learning

来源：评论

学校读者我要写书评

暂无评论

Dewing in Fog: Incentive-Aware Micro computing Cluster Formation for Fog computing 24

Dewing in Fog: Incentive-Aware Micro Computing Cluster Forma...

引用

24th IEEE international conference on Parallel and distributed systems (ICPADS)

作者： Luo, Siqi Zhou, Zhi Chen, Xiang Wu, Weigang Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538673089

Fog computing is envisioned as a promising approach for supporting emerging mission-critical applications on capacity and battery constrained mobile devices. By harvesting and collaborating a massive crowd of devices in close proximity for computation and communication resource sharing, it enables significant potentials in low-latency and energy-efficient mobile task execution. It is readily acknowledged, however, that without an efficient incentive mechanism that stimulates resources sharing among devices, the benefits of fog computing cannot be fully realized. Leveraging coalitional game theory, this work presents an efficient incentive mechanism to incentivize mutually-beneficial resource cooperation among the devices for collaborative task execution. Specially, to prevent the overexploiting and free-riding behaviors that harm resource-rich device's willingness to collaborate, the proposed mechanism groups the devices into multiple micro computing clusters (MCC). Within each MCC, devices can exchange mutually beneficial actions by helping to compute or transmit tasks, making all of them better off. the solution of the MCC formation is devised by a network-assisted mechanism, which is further proven to admit nice properties such as top coalition and core solution.

关键词： Fog computing Micro computing cluster coalitional game collaborative task offloading energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices 19

Seer: Leveraging Big Data to Navigate the Complexity of Perf...

引用

24th international conference on Architectural Support for Programming Languages and Operating systems (ASPLOS)

作者： Gan, Yu Zhang, Yanqi Hu, Kelvin Cheng, Dailun He, Yuan Pancholi, Meghna Delimitrou, Christina Cornell Univ Ithaca NY 14853 USA

ISBN: (纸本)9781450362405

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as cloud services transition from monolithic designs to microservices. Detecting QoS violations after they occur in systems with microservices results in long recovery times, as hotspots propagate and amplify across dependent services. We present Seer, an online cloud performance debugging system that leverages deep learning and the massive amount of tracing data cloud systems collect to learn spatial and temporal patterns that translate to QoS violations. Seer combines lightweight distributed RPC-level tracing, with detailed low-level hardware monitoring to signal an upcoming QoS violation, and diagnose the source of unpredictable performance. Once an imminent QoS violation is detected, Seer notifies the cluster manager to take action to avoid performance degradation altogether. We evaluate Seer both in local clusters, and in large-scale deployments of end-to-end applications built with microservices with hundreds of users. We show that Seer correctly anticipates QoS violations 91% of the time, and avoids the QoS violation to begin with in 84% of cases. Finally, we show that Seer can identify applicationlevel design bugs, and provide insights on how to better architect microservices to achieve predictable performance.

关键词： cloud computing datacenter performance debugging QoS deep learning data mining tracing monitoring microservices resource management

来源：评论

学校读者我要写书评

暂无评论

Sparse Gradient Compression for distributed SGD 24th

Sparse Gradient Compression for Distributed SGD

引用

24th international conference on Database systems for Advanced Applications (DASFAA)

作者： Sun, Haobo Shao, Yingxia Jiang, Jiawei Cui, Bin Lei, Kai Xu, Yu Wang, Jiang Peking Univ Sch Elect & Comp Engn Shenzhen Peoples R China BUPT Beijing Key Lab Intelligent Telecommun Software & Beijing Peoples R China Peking Univ Ctr Data Sci Beijing Peoples R China Natl Engn Lab Big Data Anal & Applicat Beijing Peoples R China Tencent Inc Shenzhen Peoples R China

ISBN: (纸本)9783030185794;9783030185787

Communication bandwidth is a bottleneck in distributed machine learning, and limits the system scalability. the transmission of gradients often dominates the communication in distributed SGD. One promising technique is using the gradient compression to reduce the communication cost. Recently, many approaches have been developed for the deep neural networks. However, they still suffer from the high memory cost, slow convergence and serious staleness problems over sparse high-dimensional models. In this work, we propose Sparse Gradient Compression (SGC) to efficiently train both the sparse models and the deep neural networks. SGC uses momentum approximation to reduce the memory cost with negligible accuracy degradation. then it improves the accuracy with long-term gradient compensation, which maintains global momentum to make up for the information loss caused by the approximation. Finally, to alleviate the staleness problem, SGC updates model weight with the accumulation of delayed gradients at local, called local update technique. the experiments over the sparse high-dimensional models and deep neural networks indicate that SGC can compress 99.99% gradients for every iteration without performance degradation, and saves the communication cost up to 48x.

关键词： distributed computing system distributed optimization algorithm Gradient compression

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共149页 << < 23 24 25 26 27 28 29 30 31 32 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：