Big Data in Telecommunications: Seamless Network Discovery and Traffic Steering with Crowd Intelligence

Background

In the effort to curb mobile network congestion, the challenges facing mobile operators are far more complex than just scaling up their network infrastructure. As fluctuating mobile data demand varies from area to area, on-demand network capacity allocation is almost a mandatory requirement. Despite the advancements in software-defined radio network technologies, which allow mobile operators to flexibly configure network capacity on the fly, such deployment requires costly upgrade to existing radio base stations. Instead, the immediate priority should focus on optimizing existing mobile network traffic by reducing the cost per megabyte while maintaining good user experience.

One immediate remedy to ease mobile congestion is to employ Wi-Fi offloading solution, diverting mobile data traffic towards Wi-Fi networks. Cisco (2014) has reported that approximately 45 percent of global mobile data traffic (1.2 Exabytes per month) was offloaded onto the fixed network through Wi-Fi and Femtocell in 2013. This figure is expected to reach 51 percent (17.3 Exabytes per month) by 2018. In this section, as a prelude to our work on Simplify, we will first focus our evaluation on contemporary Wi-Fi offloading solutions and other related work in relieving mobile network congestion.