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

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

Yen Pei Tay (Quest International University Perak, Malaysia), Vasaki Ponnusamy (Quest International University Perak, Malaysia) and Lam Hong Lee (Quest International University Perak, Malaysia)
Copyright: © 2016 |Pages: 15
DOI: 10.4018/978-1-4666-9840-6.ch036


The meteoric rise of smart devices in dominating worldwide consumer electronics market complemented with data-hungry mobile applications and widely accessible heterogeneous networks e.g. 3G, 4G LTE and Wi-Fi, have elevated Mobile Internet from a ‘nice-to-have' to a mandatory feature on every mobile computing device. This has spurred serious data traffic congestion on mobile networks as a consequence. The nature of mobile network traffic today is more like little Data Tsunami, unpredictable in terms of time and location while pounding the access networks with waves of data streams. This chapter explains how Big Data analytics can be applied to understand the Device-Network-Application (DNA) dimensions in annotating mobile connectivity routine and how Simplify, a seamless network discovery solution developed at Nextwave Technology, can be extended to leverage crowd intelligence in predicting and collaboratively shaping mobile data traffic towards achieving real-time network congestion control. The chapter also presents the Big Data architecture hosted on Google Cloud Platform powering the backbone behind Simplify in realizing its intelligent traffic steering solution.
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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.

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