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

1,077 篇 会议
3 篇 期刊文献
1 册 图书

馆藏范围

1,081 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

814 篇 工学
- 735 篇 计算机科学与技术...
- 330 篇 软件工程
- 307 篇 信息与通信工程
- 190 篇 电气工程
- 91 篇 控制科学与工程
- 77 篇 动力工程及工程热...
- 61 篇 生物工程
- 57 篇 交通运输工程
- 37 篇 安全科学与工程
- 33 篇 仪器科学与技术
- 30 篇 机械工程
- 30 篇 环境科学与工程（可...
- 30 篇 网络空间安全
- 21 篇 电子科学与技术（可...
- 13 篇 生物医学工程（可授...
- 11 篇 材料科学与工程（可...
- 9 篇 建筑学
- 9 篇 化学工程与技术
173 篇 理学
- 81 篇 数学
- 63 篇 生物学
- 33 篇 化学
- 29 篇 统计学（可授理学、...
- 15 篇 物理学
- 14 篇 系统科学
136 篇 管理学
- 114 篇 管理科学与工程(可...
- 58 篇 工商管理
- 51 篇 图书情报与档案管...
20 篇 医学
- 18 篇 临床医学
- 13 篇 基础医学(可授医学...
15 篇 经济学
- 15 篇 应用经济学
11 篇 法学
4 篇 农学
3 篇 教育学

主题

278 篇 edge computing
77 篇 internet of thin...
66 篇 mobile edge comp...
64 篇 cloud computing
54 篇 multi-access edg...
45 篇 image edge detec...
45 篇 computational mo...
42 篇 reinforcement le...
42 篇 deep learning
38 篇 machine learning
34 篇 resource allocat...
30 篇 task offloading
30 篇 federated learni...
28 篇 iot
27 篇 real-time system...
26 篇 performance eval...
25 篇 computation offl...
25 篇 delays
25 篇 quality of servi...
24 篇 computer archite...

机构

6 篇 college of compu...
6 篇 queens univ sch ...
5 篇 minist educ engn...
5 篇 chongqing univ c...
5 篇 hefei univ techn...
5 篇 university of ch...
5 篇 peng cheng lab p...
4 篇 beijing univ tec...
4 篇 faculty of infor...
4 篇 tianjin univ col...
4 篇 virginia tech de...
4 篇 natl tech univ a...
4 篇 beijing jiaotong...
3 篇 univ thessaly vo...
3 篇 school of comput...
3 篇 shenzhen institu...
3 篇 school of electr...
3 篇 school of inform...
3 篇 inner mongolia u...
3 篇 school of comput...

作者

8 篇 xia yunni
6 篇 shi lei
6 篇 brandic ivona
5 篇 gao yongqiang
5 篇 peng qinglan
5 篇 shi yi
4 篇 wu yuan
4 篇 lalis spyros
4 篇 marozzo fabrizio
4 篇 ma yong
4 篇 taleb tarik
4 篇 zhang li
3 篇 hong-linh truong
3 篇 masouros dimosth...
3 篇 li yang
3 篇 dai fei
3 篇 tang bing
3 篇 mohanty saraju p...
3 篇 xu jing
3 篇 trihinas demetri...

语言

1,069 篇 英文
11 篇 其他
1 篇 西班牙文

检索条件"任意字段=2022 International Conference on Edge Computing and Applications, ICECAA 2022"

共 1081 条记录，以下是41-50 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：

Towards Elasticity in Heterogeneous edge-dense Environments 42

Towards Elasticity in Heterogeneous Edge-dense Environments

引用

42nd IEEE international conference on Distributed computing Systems (ICDCS)

作者： Huang, Lei Liang, Zhiying Sreekumar, Nikhil Kaushik, Sumanth Chandra, Abhishek Weissman, Jon Univ Minnesota Minneapolis MN 55455 USA

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

edge computing has enabled a large set of emerging edge applications by exploiting data proximity and offloading computation-intensive workloads to nearby edge servers. However, supporting edge application users at scale poses challenges due to limited point-of-presence edge sites and constrained elasticity. In this paper, we introduce a densely-distributed edge resource model that leverages capacity-constrained volunteer edge nodes to support elastic computation offloading. Our model also enables the use of geo-distributed edge nodes to further support elasticity. Collectively, these features raise the issue of edge selection. We present a distributed edge selection approach that relies on client-centric views of available edge nodes to optimize average end-to-end latency, with considerations of system heterogeneity, resource contention and node churn. Elasticity is achieved by fine-grained performance probing, dynamic load balancing, and proactive multi-edge node connections per client. Evaluations are conducted in both real-world volunteer environments and emulated platforms to show how a common edge application, namely AR-based cognitive assistance, can benefit from our approach and deliver low-latency responses to distributed users at scale.

关键词： edge computing edge elasticity heterogeneity volunteer computing

来源：评论

学校读者我要写书评

暂无评论

PhD Forum Abstract: Deep Learning Model Composition for edge Intelligence 8

PhD Forum Abstract: Deep Learning Model Composition for Edge...

引用

8th IEEE international conference on Smart computing (SMARTCOMP)

作者： Nimi, Sumaiya Tabassum Univ Missouri Kansas City MO 64110 USA

ISBN: (纸本)9781665481526

The high demands the Deep Learning based applications pose on the computation resources stagger their deployment, particularly in the constrained settings of the end devices. As a result, device-edge collaborative computation setups have emerged as a popular solution these days for the utilization of AI capabilities at the end devices. However we noted several limitations in the existing solutions: (1) It was not considered whether it was not necessary to analyze all the incoming samples, particularly considering that in real-life experience many of the incoming samples could be Out-of-Distribution (OOD) to the training data distribution of the considered deep learning models and (2) Device-edge collaborative inference for multitasking deep learning models was not studied. In this extended abstract, we explore two device-edge collaborative setups we have developed towards addressing these limitations.

关键词： Deep learning Analytical models Computational modeling conferences Collaboration Training data Multitasking

来源：评论

学校读者我要写书评

暂无评论

CSM-DBEN: Container Storage Manager for Data Backup on edge Nodes 13

CSM-DBEN: Container Storage Manager for Data Backup on Edge ...

引用

13th IEEE international conference on Cloud computing Technology and Science (CloudCom)

作者： Hung, Wei-Cheng Lee, Che-Rung Natl Tsing Hua Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781665463676

edge computing that distributes computing resources close to data sources has become one of the most efficient architectures to solve the latency and the massive connection problems. On top of edge nodes, applications are usually packed in containers to enable fast deployment and multi-tenancy. However, the limited computing resource of edge nodes and application specific containerization make systematic data resilience difficult on edge nodes. In this paper, we present a container storage manager for data backup on edge nodes (CSM-DBEN), which provides the live storage backup and recovery for container volumes in the system level of edge nodes. CSM-DBEN leverages virtual machines (VM) to support better security, data isolation, and storage layering. For remote backups, CSM-DBEN performs data encryption and compression for data transmission to enhance the security and bandwidth efficiency. It also dynamically adjusts the data backup frequency, based on the prediction of disk failures, to reduce the system overhead. Experiments show that the incremental data backup time of CSM-DBEN is reduced by 75% similar to 80% compared to the commonly used rdiff-backup system.

关键词： edge computing storage management container data resilience disk failure prediction

来源：评论

学校读者我要写书评

暂无评论

Scheduling Continuous Operators for IoT edge Analytics with Time Constraints 8

Scheduling Continuous Operators for IoT edge Analytics with ...

引用

8th IEEE international conference on Smart computing (SMARTCOMP)

作者： Ntumba, Patient Georgantas, Nikolaos Christophides, Vassilis Inria Paris Paris France ENSEA ETIS Cergy France

ISBN: (纸本)9781665481526

Data stream processing and analytics (DSPA) engines are used to extract in (near) real-time valuable information from multiple IoT data streams. Deploying DSPA applications at the IoT network edge through edge/Fog architectures is currently one of the core challenges for reducing both network delays and network bandwidth usage to reach the Cloud. In this paper, we address the problem of scheduling continuous DSPA operators to Fog-Cloud nodes featuring both computational and network resources. We are paying particular attention to the dynamic workload of these nodes due to variability of IoT data stream rates and the sharing of nodes' resources by multiple DSPA applications. In this respect, we propose TSOO, a resource-aware and time-efficient heuristic algorithm that takes into account the limited Fog computational resources, the real-time response constraints of DSPA applications, as well as, congestion and delay issues on Fog-to-Cloud network resources. Via extensive simulation experiments, we show that TSOO approximates an optimal operators' placement with a low execution cost.

关键词： IoT (edge) data stream Fog Cloud continuous operator scheduling real time queuing model

来源：评论

学校读者我要写书评

暂无评论

An Open-World Time-Series Sensing Framework for Embedded edge Devices 28

An Open-World Time-Series Sensing Framework for Embedded Edg...

引用

28th IEEE international conference on Embedded and Real-Time computing Systems and applications (RTCSA)

作者： Bukhari, Abdulrahman Hosseinimotlagh, Seyedmehdi Kim, Hyoseung Univ Calif Riverside Riverside CA 92521 USA

ISBN: (数字)9781665453448

ISBN: (纸本)9781665453448

The rapid advancement of IoT technologies has generated much interest in the development of learning-based sensing applications on embedded edge devices. However, these efforts are being challenged by the need to adapt to unforeseen conditions in an open-world environment. Updating a learning model suffers from the lack of training data as well as the high computational demand beyond that available on edge devices. In this paper, we propose an open-world time-series sensing framework for making inferences from time-series sensor data and achieving incremental learning on an embedded edge device with limited resources. The proposed framework is able to achieve two essential tasks, inference and learning, without requiring access to a powerful cloud server. We discuss the design choices made to ensure satisfactory learning performance and efficient resource usage. Experimental results demonstrate the ability of the system to incrementally adapt to unforeseen conditions and to effectively run on a resource-constrained device.

关键词： IoT embedded edge devices time-series sensing open-world learning

来源：评论

学校读者我要写书评

暂无评论

edgeOrcher: Predictive Function Orchestration for Serverless-based edge Native applications 43

EdgeOrcher: Predictive Function Orchestration for Serverless...

引用

43rd IEEE international conference on Distributed computing Systems (ICDCS)

作者： Liang, Yunkai Zhou, Zhi Chen, Xu Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou Peoples R China

ISBN: (纸本)9798350339864

Serverless computing is becoming prevalent to develop resource-demanding and delay-sensitive edge native applications across the edge and cloud. The unique pricing mechanism of serverless computing brings new opportunities to reduce the cost of edge native applications, by orchestrating function fusion and placement across the edge and cloud. However, function fusion potentially increases the latency of the serverless workflow. To navigate this performance-cost tradeoff, we present an online predictive function orchestration framework which leverages predictions to dynamically optimize the function fusion and placement. Preliminary evaluation results verify the efficacy of the proposed framework.

关键词： Delay-sensitive applications

来源：评论

学校读者我要写书评

暂无评论

edgeFaaSBench: Benchmarking edge Devices Using Serverless computing 6

EdgeFaaSBench: Benchmarking Edge Devices Using Serverless Co...

引用

6th IEEE international conference on edge computing and Communications (IEEE edge)

作者： Rajput, Kaustubh Rajendra Kulkarni, Chinmay Dilip Cho, Byungjin Wang, Wei Kim, In Kee Univ Georgia Comp Sci Athens GA USA Aalto Univ Communicat & Networking Espoo Finland Univ Texas San Antonio San Antonio TX USA

ISBN: (数字)9781665481403

ISBN: (纸本)9781665481403

Due to the development of small-size, energy-efficient, and powerful CPUs and GPUs for single board computers, various edge devices are widely adopted for hosting real-world applications, including real-time object detection, autonomous driving, and sensor stream processing. At the same time, serverless computing receives increasing attention as a new application deployment model because of its simplicity, scalability, event-driven processing, and short-lived computation. Therefore, there is a growing demand for applying serverless computing to edge computing environments. However, due to the lack of characterization of serverless edge computing (e.g., application performance and impact from resource heterogeneity), researchers and practitioners have to conduct tedious measurements to understand the performance of serverless applications on edge devices in non-systematic ways. We create edgeFaaSBench, a novel benchmark suite for serverless computing on edge devices, to bridge this gap. edgeFaaSBench is developed on top of Apache OpenFaaS with Docker Swarm and can run various serverless benchmark workloads on edge devices with different hardware specifications (e.g., GPUs). edgeFaaSBench contains 14 different benchmark workloads running on heterogeneous edge devices and captures various system-level, application-level, and serverless-specific metrics, including system utilization, response time, cold/warm start times, and impact of concurrent function executions. Experimental studies are conducted on two widely used edge devices, Raspberry Pi 4B and Jetson Nano, to show edgeFaaSBench's capabilities to benchmark serverless computing on edge devices.

关键词： Benchmarking and Performance Evaluation edge computing Serverless computing

来源：评论

学校读者我要写书评

暂无评论

A computing Power Resource Modeling Approach for computing Power Network 31

A Computing Power Resource Modeling Approach for Computing P...

引用

31st international conference on Computer Communications and Networks (ICCCN)

作者： Li, Jiacong Lv, Hang Lei, Bo Xie, Yunpeng China Telecom Corp Ltd Res Inst Beijing Peoples R China

ISBN: (数字)9781665497268

ISBN: (纸本)9781665497268

edge computing has been proposed to satisfy delay requirement for various applications. It brings another challenge that the collaboration problem among cloud computing, edge computing and network resources. Diversification of computing power nodes makes the optimization of resource utilization more complicated. To solve this problem, we first describe a general computing power network (CPN) framework and analyze different roles and their focuses on computing power resource. Then we propose a computing power resource modeling approach from the operator's perspective. In this paper, we quantify the computing resource, storage resource and transmission time of wireless and wired. At last, we present completion time of a calculation task to measure computing power for CPN.

关键词： CPN resource modeling edge-cloud computing

来源：评论

学校读者我要写书评

暂无评论

A Novel Heterogeneous computing Middleware for Mobile AI Services 6

A Novel Heterogeneous Computing Middleware for Mobile AI Ser...

引用

6th IEEE international conference on edge computing and Communications (IEEE edge)

作者： Shao, Zihao Su, Tonghua Xu, Manyang Liu, Qinglin Han, Ruipeng Wang, Zhongjie Harbin Inst Technol Fac Comp Harbin Peoples R China

ISBN: (数字)9781665481403

ISBN: (纸本)9781665481403

Mobile applications play an important role in edge computing. Recently, with the advancement of more powerful mobile devices, deep models have been widely deployed in mobile applications to provide more intelligent and convenient services to users. However, mobile devices still face critical challenges, such as restricted power, sensitive latency, limited memory. As emerging AI chips are integrated into mobile devices, mobile AI solutions are proposed to accelerate model execution and improve mobile service experience. Unfortunately, they only focus on the acceleration of single chip and ignore the heterogeneity among different chips. This paper proposes a mobile heterogeneous computing AI middleware, which provides developers of AI applications with the ability to accelerate model execution. This proposed middleware utilizes three heterogeneous chips, CPU, GPU, DSP for model scheduling at a layer-wise granularity. It is designed in five layers from top to bottom: User Interface Layer, Heterogeneous Scheduling Layer, Performance Collection Layer, Hardware Information Collection Layer, AI Framework Layer. We verified it in the environment of typical mobile device through a series of experiments. The results prove the high accuracy of data collection algorithm and the effectiveness of heterogeneous scheduling services. For AlexNet and Inception V3, our schedule plan achieves at least 36.39% improvement in inference time and at least 24.4% reduction in energy consumption.

关键词： Deep learning edge devices Mobile applications Heterogeneous scheduling Middleware service

来源：评论

学校读者我要写书评

暂无评论

Analyzing Data Privacy for edge Systems 8

Analyzing Data Privacy for Edge Systems

引用

8th IEEE international conference on Smart computing (SMARTCOMP)

作者： Kotevska, Olivera Johnson, Jordan Kusne, A. Gilad Oak Ridge Natl Lab POB 2009 Oak Ridge TN 37831 USA Natl Inst Stand & Technol Gaithersburg MD 20899 USA

ISBN: (纸本)9781665481526

Internet-of-Things (IoT)-based streaming applications are all around us. Currently, we are transitioning from IoT processing being performed on the cloud to the edge. While moving to the edge provides significant networking efficiency benefits, IoT edge computing creates significant data privacy concerns. We propose a methodology that can successfully privacy protect the continual data streams generated by sensors on the edge device. We implement local differential privacy on streaming data and incorporate Bayesian inference and Gaussian process to evaluate the privacy policy. We demonstrate our methodology on a real-world smart meter testbed and identify the optimal privacy protection settings.

关键词： privacy edge Bayesian algorithms streaming data IoT Gaussian process

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109页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：