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基于众包感知的OTT业务体验影响因素分析
引用本文:徐小龙,李克,王海,宋晓勤,王征,吴雄. 基于众包感知的OTT业务体验影响因素分析[J]. 数据采集与处理, 2018, 33(3): 564-574
作者姓名:徐小龙  李克  王海  宋晓勤  王征  吴雄
作者单位:1. 北京联合大学智慧城市学院, 北京, 100101;2. 南京航空航天大学电子与信息工程学院, 南京, 210012;3. 中国电信股份有限公司上海分公司, 上海, 200122
基金项目:国家自然科学基金(61301103)资助项目;北京邮电大学泛网无线通信教育部重点实验室开放课题(KFKT-2016102)资助项目。
摘    要:随着移动互联网和OTT (Over-the-top)业务的高速发展,传统以网络为中心的运维方式难以为继,因此如何提高用户业务体验、变革传统网络质量的评价和优化方法迫在眉睫。本文围绕基于终端侧业务感知大数据进行网络和业务质量评价这一新型网络评价与运维作业模式,首先对影响端到端用户业务感知的因素进行了较全面的剖析;并利用从普通用户终端上采集的现网真实的海量业务感知数据,重点针对网页浏览这一代表性的OTT业务,从多个不同的维度深入研究影响业务感知的关键因素,以及关键业务感知指标间的关联关系,揭示了OTT业务感知的关键影响因素间的内在联系。研究结果对于进一步分析业务感知质差成因、合理构建用户体验质量(Quality of experience,QoE)映射模型等具有很好的参考价值。

关 键 词:众包感知  业务体验  网络测量  OTT业务
收稿时间:2017-11-28
修稿时间:2018-04-04

Crowdsourcing-based Analysis on Impact Factors of OTT Service Perception
Xu Xiaolong,Li Ke,Wang Hai,Song Xiaoqin,Wang Zheng,Wu Xiong. Crowdsourcing-based Analysis on Impact Factors of OTT Service Perception[J]. Journal of Data Acquisition & Processing, 2018, 33(3): 564-574
Authors:Xu Xiaolong  Li Ke  Wang Hai  Song Xiaoqin  Wang Zheng  Wu Xiong
Affiliation:1. College of Smart City, Beijing Union University, Beijing, 100101, China;2. College of Electronics and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210012, China;3. China Telecom Corp. Ltd. Shanghai Branch, Shanghai, 200122, China
Abstract:Service perception analysis is the crucial solution to understand user experience and network quality, and the maintenance and optimization of the mobile networks. With the fast development of mobile Internet and OTT(over-the-top) services, the traditional network-centric mode of network operation and maintenance is no longer an effective way. In this situation, how to effectively evaluate and optimize user''s service perception is getting more and more important. The key factors that impact on user''s end-to-end OTT service perception is analyzed based on the so-called crowd sourcing based user perception monitoring methodology. Furthermore, the inner relationship among the key factors and the interaction between key quality indicators are evaluated from several aspects, by utilizing big data set of user perception collected from large amount of smart phone users in the real network. The results of analysis are highly valuable references for the improvement of user perception and network quality, network deployment and optimizations, etc.
Keywords:crowdsourcing  service perception  network measurement  OTT service
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