Quantifying vSTB as a function of service velocity and subscriber reach
In the magical world of virtualization, we’re usually able to keep our eye on the ball as systems vanish and their functionality appears elsewhere in the network. So why is it that the concept of a virtual set-top box confounds the pay-TV industry like a David Copperfield illusion?
While there’s general agreement that a vSTB approach can conjure capex and opex savings, how it accomplishes that has kept pay-TV opinion divided. Is the native app in the connected TV also a vSTB? Can it be “vSTB” if the set-top box itself fails to disappear?
Like any good puzzle, there’s only one true solution, and for virtual STB the reality is rooted in this: a scientific, mathematical formula that defines vSTB not only as a cost reduction strategy for pay-TV providers, but also—and more importantly—as a function of service velocity and subscriber reach.
Let’s start with some basic assumptions: 1) Virtualization in computing is defined as the act of creating a “virtual” version of an actual platform, operating system, device or other resource; and 2) among the most essential resources in most pay-TV STBs are CPUs, GPUs, memory and browsers/rendering engines.
There are two problems that occur when virtualization strategies involve shifts of those resources from set-top boxes to other connected devices in the home. First, the continued presence of the actual resources at the customer premises—albeit in a different device—is contrary to the virtualization definition above. Second, history has shown that the 10-year development and deployment lifecycle for new pay-TV CPE is incompatible with the more rapid shifts in CPE horsepower, application frameworks and browser technology that are continually roiling the CE market.
How does all this apply to our formula? For modern IP set-top boxes or connected TVs, the slow pace of writing apps for the specific device (“# of Services”) and the slow growth of customer footprints (“Subscriber Reach”) pale in comparison to the hardware and browser resources required for every subscriber. And while devices such as Chromecast minimize the cost factor, issues of service availability and market footprint remain. At the same time, those devices rely on other processing resources located at the customer premises—a transparent shift in resources, not true virtualization.
Here’s the approach that has yielded the greatest number of new services and subscribers, while simultaneously reducing resource cost: Truly virtualizing the set-top box functionality by taking advantage of CPUs, GPUs, memory and browser technology in the cloud and delivering complex, high-end user experiences as interactive streams to any device—from low-cost dongles and “hockey puck” boxes to existing STBs and connected TVs.
Over the past year, industry leaders—including Charter Communications, Cablevision, Liberty Puerto Rico, Ziggo, UPC Hungary and Deutsche Telekom’s T-Labs—have begun virtualizing STB functionality in the cloud to deliver innovative new services ranging from guides to interactive ads to YouTube to entire market footprints of existing set-top boxes. In each case, true virtualization has enabled services to be created and scaled in a fraction of the time—and at a fraction of the cost—of device-based approaches.
While there is no question in our mind that this is true STB virtualization, we don’t expect the disagreement over what constitutes vSTB to disappear with a wave of the hand. What we do believe is that doing the math can help the industry move beyond capex and opex implications to understand how a cloud-based approach to vSTB can drive service velocity and scale.