Convergence and offloading: the smart Radio Base Station
The convergence of cloud computing and telecoms is a hot topic in technology these days, but underlying this paradigm shift is a trend in both IT and telecoms to move toward distributed processing.
While the telecommunications provider’s data center seems to be the first place to look for a convergence, the actual revolution lies across the chain – all the way to the Radio Base Station (RBS).
Samsung defines three areas where the Telecom and distributed computing convergence will give companies a competitive edge:
- Richness of services
- Speed of Delivery
- Performance and ROI
As pervasive connectivity becomes the goal in telecommunications, the opportunity to improve service velocity at the network edge becomes a need as well. Gateways and RBSs enable operators to place more IT assets in those locations. By shifting content management, application logic processing and even server infrastructure toward regional and local network components, the overall network capacity and scalability increases, thus providing faster service to the user.
Nokia Solutions and Networks sees distributing processing capacity as eliminating a potential bottleneck and creating what it calls distributed intelligence:
Approximating data centers at the very edge of the mobile network is a unique solution to this challenge. Rather than just expanding capacity within a centrally located data center, a transformed mobile base station can provide both the needed computational capacity and meet the communications industry’s needs for robust networking.
However, Kevin Fitchard repots in Gigaom that at the World Mobile Congress in Barcelona (24-27 February) a consortium of Alcatel-Lucent, Intel and China Mobile will be unveiling a trial that does the opposite – it replaces the RBS instead with a much simpler radio that sends the signal to a data center for processing.
We will need to measure how well either system works, and a rough guide is now available. A new metric that the user can understand is being touted in the form of ‘app coverage’. A cell-edge that provides acceptable voice and email service but not video, could be considered as having poor video app coverage at the edges. Ericsson calls app coverage, “ the probability that the network will deliver sufficient performance to run a particular application at a quality level acceptable to the user.”
App coverage is easy to understand and easy to test, so expect to hear more about it in the future. Moreover, the ramifications of a focus on app coverage go beyond the ability to reach the network, and while an editorial in telecomlead.com calls 2014 “the year of mobile core integration with Wi-Fi”, good app coverage needs more. As more processing-intensive data communications becomes the norm, being able to handle that processing will become just as important as the ability to send and receive it. Because of this, app coverage or an equivalent measurement is going to become part of our lives.
The ability to take advantage of distributed intelligence and the growing awareness of app coverage will require more than just relying on telecoms providers to put more computational power further afield. Smartphone apps, enterprise communications optimizations and content provision will all need to integrate the additional capacity – and client expectations – into an already intricate chain starting at the smartphone and ending at the data center.
Converging Telecom & IT in the LTE RAN, Samsung, 2013
“The next big step for cellular networks isn’t 5G. It’s the cloud”, Gigaom, 2014
App Coverage, Ericsson, 2013
“Wi-Fi offload technology and user experience 2014 trends by Aptilo Networks”, Telecomlead, 2013