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

1,627 篇 会议
13 篇 期刊文献
9 册 图书

馆藏范围

1,649 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

921 篇 工学
- 843 篇 计算机科学与技术...
- 329 篇 软件工程
- 218 篇 信息与通信工程
- 141 篇 电气工程
- 71 篇 控制科学与工程
- 31 篇 生物工程
- 25 篇 电子科学与技术（可...
- 22 篇 生物医学工程（可授...
- 22 篇 网络空间安全
- 15 篇 动力工程及工程热...
- 14 篇 安全科学与工程
- 13 篇 建筑学
- 12 篇 土木工程
- 10 篇 仪器科学与技术
- 10 篇 交通运输工程
- 9 篇 机械工程
- 9 篇 材料科学与工程（可...
- 8 篇 化学工程与技术
182 篇 理学
- 88 篇 数学
- 68 篇 物理学
- 33 篇 生物学
- 19 篇 系统科学
- 18 篇 统计学（可授理学、...
130 篇 管理学
- 90 篇 管理科学与工程(可...
- 58 篇 图书情报与档案管...
- 53 篇 工商管理
20 篇 法学
- 16 篇 社会学
17 篇 医学
- 16 篇 临床医学
- 14 篇 基础医学(可授医学...
16 篇 经济学
- 14 篇 应用经济学
2 篇 农学
1 篇 教育学
1 篇 文学
1 篇 军事学
1 篇 艺术学

主题

156 篇 distributed comp...
114 篇 cloud computing
78 篇 peer to peer com...
74 篇 application soft...
67 篇 protocols
67 篇 computer network...
64 篇 computational mo...
63 篇 mobile computing
56 篇 computer science
56 篇 computer archite...
49 篇 high performance...
47 篇 routing
46 篇 bandwidth
45 篇 internet
45 篇 middleware
43 篇 privacy
40 篇 costs
39 篇 resource managem...
38 篇 social networkin...
38 篇 edge computing

机构

14 篇 state key labora...
10 篇 gansu provincial...
9 篇 beijing universi...
7 篇 institute of com...
7 篇 cern geneva
6 篇 college of compu...
6 篇 shenzhen institu...
6 篇 tokyo denki univ...
5 篇 department of ph...
5 篇 dept. of astrono...
5 篇 dept. of physics...
5 篇 dept. of physics...
5 篇 iii. physikalisc...
5 篇 erlangen centre ...
5 篇 département de p...
5 篇 school of physic...
5 篇 dept. of physics...
5 篇 dept. of physics...
5 篇 department of ph...
5 篇 institut für phy...

作者

8 篇 takizawa makoto
6 篇 huang lican
6 篇 enokido tomoya
6 篇 makoto takizawa
5 篇 de ridder s.
5 篇 choi k.
5 篇 an r.
5 篇 haungs a.
5 篇 fürst p.
5 篇 cross r.
5 篇 bradascio f.
5 篇 fan k.l.
5 篇 bourbeau e.
5 篇 fritz a.
5 篇 bastian b.
5 篇 gündüz m.
5 篇 dvorak e.
5 篇 halve l.
5 篇 gonzalez j.g.
5 篇 de clercq c.

语言

1,629 篇 英文
15 篇 其他
8 篇 中文

检索条件"任意字段=Proceedings of the 22nd International Conference on Distributed Computing and Networking"

共 1649 条记录，以下是11-20 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：

Consensus in the Presence of Overlapping Faults and Total Omission 22nd

Consensus in the Presence of Overlapping Faults and Tota...

引用

22nd Theory of Cryptography conference, TCC 2024

作者： Loss, Julian Shi, Kecheng Stern, Gilad CISPA Helmholtz Center for Information Security Saarbrücken Germany Tel Aviv University Tel Aviv Israel Saarland University Saarbrücken Germany

ISBN: (纸本)9783031780103

Understanding the fault tolerance of Byzantine Agreement protocols is an important question in distributed computing. While the setting of Byzantine faults has been thoroughly explored in the literature, the (arguably more realistic) omission fault setting is far less studied. In this paper, we revisit the recent work of Loss and Stern who gave the first protocol in the mixed fault model tolerating t Byzantine faults, s send faults, and r receive faults, when 2t+r+s2, or a broadcast protocol for s+r=n and s>1 even without overlapping faults. © international Association for Cryptologic Research 2025.

关键词： distributed computer systems

来源：评论

学校读者我要写书评

暂无评论

POSEIDON: Efficient Function Placement at the Edge Using Deep Reinforcement Learning 22nd

POSEIDON: Efficient Function Placement at the Edge Using Dee...

引用

22nd international conference on Service Oriented computing

作者： Jain, Prakhar Singhal, Prakhar Pandey, Divyansh Quatrocchi, Giovanni Vaidhyanathan, Karthik Int Inst Informat Technol Software Engn Res Ctr Hyderabad India Politecn Milan Dipartimento Elettron Informaz & Bioingn Milan Italy

ISBN: (纸本)9789819608041;9789819608058

Edge computing allows for reduced latency and operational costs compared to centralized cloud systems. In this context, serverless functions are emerging as a lightweight and effective paradigm for managing computational tasks on edge infrastructures. However, the placement of such functions in constrained edge nodes remains an open challenge. On one hand, it is key to minimize network delays and optimize resource consumption;on the other hand, decisions must be made in a timely manner due to the highly dynamic nature of edge environments. In this paper, we propose POSEIDON, a solution based on Deep Reinforcement Learning for the efficient placement of functions at the edge. POSEIDON leverages Proximal Policy Optimization (PPO) to place functions across a distributed network of nodes under highly dynamic workloads. A comprehensive empirical evaluation demonstrates that POSEIDON significantly reduces execution time, network delay, and resource consumption compared to state-of-the-art methods.

关键词： Edge computing Serverless Function Placement Deep Reinforcement Learning

来源：评论

学校读者我要写书评

暂无评论

False Data Injection Attack Detection in Edge-Based Smart Metering Networks with Federated Learning 22

False Data Injection Attack Detection in Edge-Based Smart Me...

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Uddin, Md Raihan Rahman, Ratun Nguyen, Dinh C. The University of Alabama in Huntsville Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798331508050

Smart metering networks are increasingly susceptible to cyber threats, where false data injection (FDI) appears as a critical attack. Data-driven-based machine learning (ML) methods have shown immense benefits in detecting FDI attacks via data learning and prediction abilities. Literature works have mostly focused on centralized learning and deploying FDI attack detection models at the control center, which requires data collection from local utilities like meters and transformers. However, this data sharing may raise privacy concerns due to the potential disclosure of household information like energy usage patterns. This paper proposes a new privacy-preserved FDI attack detection by developing an efficient federated learning (FL) framework in the smart meter network with edge computing. distributed edge servers located at the network edge run an ML-based FDI attack detection model and share the trained model with the grid operator, aiming to build a strong FDI attack detection model without data sharing. Simulation results demonstrate the efficiency of our proposed FL method over the conventional method without collaboration. © 2025 IEEE.

关键词： Attack detection edge computing federated learning metering networks

来源：评论

学校读者我要写书评

暂无评论

distributed Denial of Service Attack Detection by Machine Learning Techniques 22

Distributed Denial of Service Attack Detection by Machine Le...

引用

22nd international Learning and Technology conference, L and T 2025

作者： Jewani, Varkha K. Ajmire, Prafulla E. Atique, Mohd. Sharma, Bhisham Dhaou, Imed Ben Awadhesh Chaurasia, Suhashini Sant Gadge Baba Amravati University Amravati India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140401 India Dar Al-Hekma University Hekma School of Engineering Computing and Design Department of Computer Science Jeddah Saudi Arabia RTM Nagpur University Department of Computer Science Nagpur India

ISBN: (纸本)9798331532215

The exponential expansion of computer networks and the internet makes it clear that there is a chance of being attacked and harmed. In the meantime, one of the most crucial defensive measures against the more complex and frequent network attacks is the intrusion detection and prevention systems (IDSs and IPSs). Due to insufficient datasets, anomaly-based research in intrusion detection systems is plagued by imprecise deployment, analysis, and evaluation. The researchers analyzed a variety of datasets, including DARPA98, KDD99, ISC2012, and ADFA13, to assess how well their suggested intrusion detection and intrusion prevention techniques performed. There are several issues: lack of adequate attack coverage, unrepresentative payloads, and anonymised packet information, insufficient traffic volume and diversity, or a deficiency in feature set and metadata. This study is focused on CICIDS-2017 which is the recently updated IDS dataset that meets real-world requirements and is accessible publicly. In addition to benign network flows and distributed denial of service (DDoS) attacks, it contains seven common attack network flows as well. To provide the optimal combination of features for the identification of the attack category, it also assesses the efficacy of several machine learning (ML) algorithms and network traffic feature sets. Even though various ML techniques like Linear Regression, Random Forests, and Decision Tree can be used, and performed very well, Hybrid Algorithm is designed to get better analysis on dataset. © 2025 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

A Preliminary Study on Performance Modeling at Scale for Geophysical Applications 33

A Preliminary Study on Performance Modeling at Scale for Geo...

引用

33rd Euromicro international conference on Parallel, distributed, and Network-Based Processing, PDP 2025

作者： Dupros, Fabrice Jubertie, Sylvain Aochi, Hideo Intel Corporation Paris France Brgm Orléans France

ISBN: (纸本)9798331524937

Modeling the performance of real-world applications at scale is essential for designing next-generation platforms and shaping the development of future algorithms. However, accurately capturing the complexity of application execution graphs and their interaction with large-scale hardware environments remains a significant challenge. In recent years, several frameworks have been developed to tackle this issue by providing tools to simulate and analyze complex workloads on distributed systems. This paper focuses on seismic wave propagation problems as a representative use case to explore the challenges of modeling at scale. We employ the SimGrid simulation toolkit, a versatile framework for simulating distributed systems, to analyze the performance of large-scale applications. Particular emphasis is placed on the role of critical networking characteristics, such as bandwidth and topology, in influencing overall scalability and performance. © 2025 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Federated Learning as a Service for Hierarchical Edge Networks with Heterogeneous Models 22nd

Federated Learning as a Service for Hierarchical Edge Networ...

引用

22nd international conference on Service Oriented computing

作者： Gao, Wentao Tavallaie, Omid Chen, Shuaijun Zomaya, Albert Univ Sydney Sch Comp Sci Sydney NSW Australia Univ Oxford Dept Engn Sci Oxford England

ISBN: (纸本)9789819608041;9789819608058

Federated learning (FL) is a distributed Machine Learning (ML) framework that is capable of training a new global model by aggregating clients' locally trained models without sharing users' original data. Federated learning as a service (FLaaS) offers a privacy-preserving approach for training machine learning models on devices with various computational resources. Most proposed FL-based methods train the same model in all client devices regardless of their computational resources. However, in practical Internet of Things (IoT) scenarios, IoT devices with limited computational resources may not be capable of training models that client devices with greater hardware performance hosted. Most of the existing FL frameworks that aim to solve the problem of aggregating heterogeneous models are designed for Independent and Identical distributed (IID) data, which may make it hard to reach the target algorithm performance when encountering non-IID scenarios. To address these problems in hierarchical networks, in this paper, we propose a heterogeneous aggregation framework for hierarchical edge systems called HAF-Edge. In our proposed framework, we introduce a communication-efficient model aggregation method designed for FL systems with two-level model aggregations running at the edge and cloud levels. This approach enhances the convergence rate of the global model by leveraging selective knowledge transfer during the aggregation of heterogeneous models. To the best of our knowledge, this work is pioneering in addressing the problem of aggregating heterogeneous models within hierarchical FL systems spanning IoT, edge, and cloud environments. We conducted extensive experiments to validate the performance of our proposed method. The evaluation results demonstrate that HAF-Edge significantly outperforms state-of-the-art methods.

关键词： Federated Learning as a Service (FLaaS) Model Heterogeneity Edge computing IoT Networks

来源：评论

学校读者我要写书评

暂无评论

Pricing Strategies in Cybersecurity Markets with Network Effects 22

Pricing Strategies in Cybersecurity Markets with Network Eff...

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Hou, Jing Wang, Xuyu Zeng, Amy Z. California State University San Marcos Department of Computer Science and Information Systems San Marcos 92096 CA United States School of Computing and Information Sciences Florida International University Miami 33199 FL United States Sawyer Business School Suffolk University Boston 02108 MA United States

ISBN: (纸本)9798331508050

The cybersecurity market is rapidly growing in the face of ubiquitous vulnerabilities, with vendors delivering solutions ranging from basic software-based approaches to high-end services for diverse business needs. The sustainability of a cybersecurity business relies on its ability to update its solutions to address ever-changing cyber threats continuously. It requires a substantial customer base for data collection and service enhancement, which, in turn, can attract more customers. Therefore, a novel business model that acknowledges this positive network effect and provides incentives for potential customers is crucial to ensure the success of the cybersecurity business. In this paper, we develop an analytical framework with optimization and a Stackelberg game approach to model the cybersecurity market scenario for a cybersecurity vendor offering both a basic software-based service and a premium service. We delve into the market evolution and characterize the conditions under which the dynamic market converges to a unique equilibrium. The optimal pricing strategy for the vendor is analyzed to leverage the network effects for profit maximization. © 2025 IEEE.

关键词： Cybersecurity market incentive inter-service relationship network externality pricing

来源：评论

学校读者我要写书评

暂无评论

Network Anomaly Detection in distributed Edge computing Infrastructure

Network Anomaly Detection in Distributed Edge Computing Infr...

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Marfo, William Rico, Enrique A. Tosh, Deepak K. Moore, Shirley V. University of Texas at El Paso Department of Computer Science El Paso United States

ISBN: (纸本)9798331508050

As networks continue to grow in complexity and scale, detecting anomalies has become increasingly challenging, particularly in diverse and geographically dispersed environments. Traditional approaches often struggle with managing the computational burden associated with analyzing large-scale network traffic to identify anomalies. This paper introduces a distributed edge computing framework that integrates federated learning with Apache Spark and Kubernetes to address these challenges. We hypothesize that our approach, which enables collaborative model training across distributed nodes, significantly enhances the detection accuracy of network anomalies across different network types. We show that by leveraging distributed computing and containerization technologies, our framework not only improves scalability and fault tolerance but also achieves superior detection performance compared to state-of-the-art methods. Extensive experiments on the UNSW-NB15 and ROAD datasets validate the effectiveness of our approach, demonstrating statistically significant improvements in detection accuracy and training efficiency over baseline models, as confirmed by MannWhitney U and Kolmogorov-Smirnov tests (p<0.05). © 2025 IEEE.

关键词： Anomaly Detection Deep Learning Edge computing Federated Learning Kubernetes Networks Security

来源：评论

学校读者我要写书评

暂无评论

Balancing computing and networking in Autonomous Edge Clouds 22

Balancing Computing and Networking in Autonomous Edge Clouds

引用

22nd IEEE Consumer Communications and networking conference, CCNC 2025

作者： Masuda, Shinnosuke Hasegawa, Tsuyoshi Shudo, Kazuyuki Cho, Kenjiro Kyoto University Japan Iij Japan

ISBN: (纸本)9798331508050

In the ever-changing environment of edge cloud systems, it is necessary to allocate diverse cloud resources in an efficient manner, at the same time, reducing energy consumption. A simple distributed resource allocation model is proposed in a previous study that utilizes a pseudo cost function of resource load, and it is shown that a convex function allows energy saving by pooling idle edge servers. In this paper, we extend this cost model beyond simple load, and present a method to balance computation and communication by merging multiple constraints into the cost function. We show trade-offs among soft constraints along with energy saving effects by simulation, using specific scenarios with computational and communication constraints. Our simulation results show that the combination of a convex function with a polynomial penalty function works well for balancing energy saving and other soft constraints. © 2025 IEEE.

关键词： autonomous resource management cloud morphing convex cost function edge computing

来源：评论

学校读者我要写书评

暂无评论

proceedings - 2018 IEEE 22nd international Enterprise distributed Object computing conference, EDOC 2018

Proceedings - 2018 IEEE 22nd International Enterprise Distri...

引用

22nd IEEE international Enterprise distributed Object computing conference, EDOC 2018

ISBN: (纸本)9781538641392

The proceedings contain 25 papers. The topics discussed include: enterprise architecture 4.0 – a vision, an approach and software tool support;formalizing application integration patterns;FEDSA: a data federation platform for law enforcement management;modeling data transformations in data-aware service choreographies;enterprise architecture planning in the context of industry 4.0 transformations;a probabilistic enterprise architecture model evolution;modeling and analyzing process architecture for context-driven adaptation: designing cognitively-enhanced business processes for enterprises;and a flexible event handling model for business process enactment.

关键词：

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165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：