Network traffic classification with machine learning and edge computing
利用机器学习和边缘计算进行网络流量分类
基本信息
- 批准号:517685-2017
- 负责人:
- 金额:$ 5.15万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Collaborative Research and Development Grants
- 财政年份:2019
- 资助国家:加拿大
- 起止时间:2019-01-01 至 2020-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
With the emerging prevalence of data-hungry applications, such as augmented reality, wireless multimedia, cloud computing, and Internet of Things, the current generation of network infrastructure will face severe challenges in its struggle to satisfy the exploding service demands. In order to efficiently allocate the available networking resources among these diverse set of applications, traffic classification has become an essential technology for the optimal operation of a network. However, classical classification methods, such as those based on network protocol interface or packet content inspection, are no longer suitable to meet the accuracy, delay, and privacy requirements to support modern applications and services. The ever changing characteristics of new applications and increasing volume of traffic demand a flexible and automatic approach. In this project, we will apply dynamic machine learning techniques to identify and categorize the network traffic of an Internet service provider. A unique feature of this project is that we will leverage the availability of a vast amount anonymous user traffic data from TELUS, to investigate into a hybrid combination of both supervised and unsupervised learning. We will also take advantage of the emerging capabilities of computing at the network edge, where the network traffic is more localized with shared commonalities among local users, to improve the accuracy of traffic classification. Through mathematical analysis, computer simulation, and large-scale data experimentation, we will generate practical guidelines on how to design and operate network traffic classifiers, to optimally balance the tradeoff between accuracy, privacy, cost, and delay. The outcomes of the proposed research are expected to benefit both our industry partner and the Canadian information and communication industry at large, by promoting engineering theory, technical methods, and standardization policies that can lead to system improvement, cost reduction, sustainable growth, and long-term competitiveness.
随着增强现实、无线多媒体、云计算和物联网等大数据应用的兴起,当前一代网络基础设施在满足爆炸式增长的服务需求方面将面临严峻挑战。为了在这些不同的应用程序之间有效地分配可用的网络资源,流量分类已成为网络优化运行的一项重要技术。然而,经典的分类方法,例如基于网络协议接口或数据包内容检查的分类方法,不再适合满足支持现代应用和服务的准确性、延迟和隐私要求。新应用程序不断变化的特征和不断增加的流量需要灵活且自动的方法。在这个项目中,我们将应用动态机器学习技术来识别和分类互联网服务提供商的网络流量。该项目的一个独特之处在于,我们将利用 TELUS 提供的大量匿名用户流量数据来研究监督学习和无监督学习的混合组合。我们还将利用网络边缘新兴的计算能力(网络流量更加本地化,本地用户之间具有共享共性)来提高流量分类的准确性。通过数学分析、计算机模拟和大规模数据实验,我们将生成有关如何设计和操作网络流量分类器的实用指南,以最佳地平衡准确性、隐私、成本和延迟之间的权衡。拟议研究的成果预计将使我们的行业合作伙伴和整个加拿大信息和通信行业受益,通过推广工程理论、技术方法和标准化政策,从而改善系统、降低成本、可持续增长和长期发展。 - 长期竞争力。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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{{ truncateString('Liang, Ben', 18)}}的其他基金
Collaborative Communication and Computation for Hierarchical Learning at the Mobile Edge
移动边缘分层学习的协作通信和计算
- 批准号:
RGPIN-2020-05886 - 财政年份:2022
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Collaborative Communication and Computation for Hierarchical Learning at the Mobile Edge
移动边缘分层学习的协作通信和计算
- 批准号:
RGPIN-2020-05886 - 财政年份:2022
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Collaborative Communication and Computation for Hierarchical Learning at the Mobile Edge
移动边缘分层学习的协作通信和计算
- 批准号:
RGPIN-2020-05886 - 财政年份:2021
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Collaborative Communication and Computation for Hierarchical Learning at the Mobile Edge
移动边缘分层学习的协作通信和计算
- 批准号:
RGPIN-2020-05886 - 财政年份:2021
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Leading edge: an integrated communication and computation framework for mobile edge computing
前沿:移动边缘计算的集成通信和计算框架
- 批准号:
506678-2017 - 财政年份:2020
- 资助金额:
$ 5.15万 - 项目类别:
Strategic Projects - Group
Leading edge: an integrated communication and computation framework for mobile edge computing
前沿:移动边缘计算的集成通信和计算框架
- 批准号:
506678-2017 - 财政年份:2020
- 资助金额:
$ 5.15万 - 项目类别:
Strategic Projects - Group
Collaborative Communication and Computation for Hierarchical Learning at the Mobile Edge
移动边缘分层学习的协作通信和计算
- 批准号:
RGPIN-2020-05886 - 财政年份:2020
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Collaborative Communication and Computation for Hierarchical Learning at the Mobile Edge
移动边缘分层学习的协作通信和计算
- 批准号:
RGPIN-2020-05886 - 财政年份:2020
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Integrated Communication and Computation Resource Management for Mobile Cloud Computing
移动云计算的综合通信与计算资源管理
- 批准号:
RGPIN-2015-05506 - 财政年份:2019
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
Integrated Communication and Computation Resource Management for Mobile Cloud Computing
移动云计算的综合通信与计算资源管理
- 批准号:
RGPIN-2015-05506 - 财政年份:2019
- 资助金额:
$ 5.15万 - 项目类别:
Discovery Grants Program - Individual
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Network traffic classification with machine learning and edge computing
利用机器学习和边缘计算进行网络流量分类
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Collaborative Research and Development Grants
Network traffic classification with machine learning and edge computing
利用机器学习和边缘计算进行网络流量分类
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517685-2017 - 财政年份:2018
- 资助金额:
$ 5.15万 - 项目类别:
Collaborative Research and Development Grants