Grasping Popular Applications in Cellular Networks With Big Data Analytics Platforms

摘要

Internet access through cellular networks is rapidly growing, driven by the great success of the mobile apps paradigm and the overwhelming popularity of social-related multimedia services such as YouTube, Facebook, or even WhatsApp. Understanding the functioning, performance, and traffic generated by these applications is paramount for ISPs, especially for cellular operators, who must manage the huge surge of volume and number of users with the constraints and challenges of cellular networks. In this paper, we study important networking aspects of three popular applications in cellular networks: YouTube, Facebook, and WhatsApp. Our evaluations span the content delivery networks hosting these services, their traffic characteristics, and their performance. The analysis is performed on top of real cellular network traffic monitored at the nationwide cellular network of a major European ISP. Due to privacy issues and given the huge amount of data generated by these applications as well as the large number of monitored customers, the analysis has been done in an online fashion, using a customized big data analytics (BDA) platform called DBStream. We overview DBStream and discuss other potential solutions currently available for traffic monitoring and analysis of big networking data. To the best of our knowledge, this is the first paper providing a complete analysis of popular services in cellular networks, using BDA platforms.