Big data analytics on mobile traffic through clustering analysis and machine learning

通过聚类分析和机器学习对移动流量进行大数据分析

• 批准号: 461314-2013
• 负责人: Lung, ChungHorng
• 金额: $ 1.82万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=542565
• 关键词: Big; data; analytics; mobile; traffic

Big data analytics has become increasingly important in practice and in theory. Mobile network infrastructure vendors, such as Ericsson, regularly collect and analyze a huge amount of traffic data from radio access and core networks globally. These data are used for different research and development (R&D), and business purposes, ranging from capacity and performance monitoring, product troubleshooting, realistic lab testing, new feature design, architectural evolution, etc.

大数据分析在实践和理论上变得越来越重要。爱立信等移动的网络基础设施供应商定期收集和分析来自全球无线电接入和核心网络的大量流量数据。这些数据用于不同的研发（R&D）和业务目的，包括容量和性能监控、产品故障排除、实际实验室测试、新功能设计、架构演进等。