Thanks to LTE, consumers are experiencing a complete overhaul of the way mobile services are used. Traditional text messaging is being replaced with rich communication services like real-time video calling, especially as screen size increases with higher screen resolution and phone batteries are lasting longer. These improvements are great for the end-user, but they are causing service providers to support a variety of applications not traditionally seen on mobile phones. Everything from web surfing, streaming video, peer-to-peer networking, and machine-to-machine communications that consume large amounts of bandwidth for longer durations are moving from 'nice-to-haves' to 'must-haves.' Not to mention that moving forward, LTE will be available for notebooks, ultra-portables, cameras, camcorders, mobile broadband routers, and other devices that would benefit from access to wireless.
As such, mobile services providers will be tasked with creating billing structures that drive revenue for these enhanced services. Smartphones have already increased backhaul traffic and created nightmare scenarios for carriers. Now, they must regulate the traffic flows and monetize new services, as well as optimize network performance. Besides, it's no surprise that downloading a YouTube video uses 100x more bandwidth than voice, and the average iPhone uses 400MB of data per month. But does this mean that the Netflix HD movie streamer should be billed at a different rate than your average texter? Most service providers believe so, considering there are millions of concurrent mobile users on any one network at any given time. Solutions must not only recognize the applications and services each individual is using, but also decipher their different billing plans based on a variety of criteria.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.