Recent years have witnessed the rapid growth of mobile virtual network operators (MVNOs), which operate on top of existing cellular infrastructures of base carriers, while offering cheaper or more flexible data plans compared to those of the base carriers. In this paper, we present a two-year measurement study towards understanding various fundamental aspects of today’s MVNO ecosystem, including its architecture, customers, performance, economics, and the complex interplay with the base carrier. Our study focuses on a large commercial MVNO with one million customers, operating atop a nation-wide base carrier. Our measurements clarify several key concerns raised by MVNO customers, such as inaccurate billing and potential performance discrimination with the base carrier. We also leverage big data analytics, statistical modeling, and machine learning to address the MVNO’s key concerns with regard to data usage prediction, data plan reselling, customer churn mitigation, and billing delay reduction. Our proposed techniques can help achieve higher revenues and improved services for commercial MVNOs.

中文翻译：

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了解生态系统并解决商业MVNO的基本问题

近年来，目睹了移动虚拟网络运营商（MVNO）的快速增长，它们在基本运营商的现有蜂窝基础架构之上运行，同时提供了比基本运营商便宜，更灵活的数据计划。在本文中，我们进行了为期两年的测量研究，旨在了解当今MVNO生态系统的各个基本方面，包括其架构，客户，性能，经济性以及与基础运营商的复杂相互作用。我们的研究重点是在全国范围的基础运营商之上运营的拥有一百万客户的大型商用MVNO。我们的测量结果澄清了MVNO客户提出的几个关键问题，例如计费不准确以及对基本运营商的潜在性能歧视。我们还利用大数据分析，统计建模，以及机器学习解决MVNO在数据使用量预测，数据计划转售，客户流失缓解和计费延迟减少方面的关键问题。我们提出的技术可以帮助为商业MVNO获得更高的收入和更好的服务。