Intel gets Real: Intel Buys $120m Codec Patents From RealNetworks

"RealNetworks, Inc. (Nasdaq: RNWK) today announced that it has signed an agreement to sell a significant number of its patents and its next generation video codecs software to Intel Corporation for a purchase price of $120 millions. Under terms of the sale, RealNetworks retains certain rights to continue to use the patents in current and future products.

"Selling these patents to Intel unlocks some of the substantial and unrealized value of RealNetworks assets," said Thomas Nielsen, RealNetworks President and CEO. "It represents an extraordinary opportunity for us to generate additional capital to boost investments in new businesses and markets while still protecting our existing business.

"RealNetworks is pleased Intel has agreed to acquire our next generation video codec software and team," said Nielsen. "Intel has a strong reputation as a technology innovator, and we believe they are well positioned to build on the development work and investment we've made in this area."

"As the technology industry evolves towards an experience-centric model, users are demanding more media and graphics capabilities in their computing devices.  The acquisition of these foundational media patents, additional patents and video codec software expands Intel's diverse and extensive portfolio of intellectual property," said Renée James, Intel senior vice president and general manager of the Software and Services Group.  "We believe this agreement enhances our ability to continue to offer richer experiences and innovative solutions to end users across a wide spectrum of devices, including through Ultrabook devices, smartphones and digital media."

In addition to the sale of the patents and next-generation video codec software, RealNetworks and Intel signed a memorandum of understanding to collaborate on future support and development of the next-generation video codec software and related products.

"We look forward to working with Intel to support the development of the next-generation video codec software and to expanding our relationship into new products and markets," said Nielsen.

RealNetworks does not anticipate that the sale of the approximately 190 patents and 170 patent applications and next generation video codec software will have any material impact on its businesses. RealNetworks businesses include a wide variety of SaaS products and services provided to global carriers, RealPlayer, the Helix streaming media platform, GameHouse online and social games, SuperPass and other media products and services sold both directly to consumers and through partners."

Another strong message and movement in the video encoding space. Video intellectual property as we have seen here is becoming increasingly strategic

For or against Adaptive Bit Rate? part IV: Alternatives

As we have seen  here,  here, and  here, Adaptive Bit Rate (ABR) is a great technology for streaming video contents in lossy networks but it is handicapped by many challenges that are hindering its success and threatening its implementation in mobile networks.

Having spoken to many vendors in the space, here are two techniques that I have seen deployed to try and  emulate ABR benefits in mobile networks, while reducing dependencies on some of the obstacles mentioned.

DBRA (Dynamic Bit Rate Adaptation)

DBRA is a technique that relies on real-time transcoding or transrating to follow network variations. It is implemented in the core network, on a video optimization engine. When the video connection is initialized, a DBRA-capable network uses TCP feedback and metrics to understand whether the connection is improving or worsening. The platform cannot detect congestion in itself but deduces it from the state of the connection. jitter, packet loss ratio, TCP window, device buffer size and filling rate are all parameters that are fed into proprietary heuristic algorithms. These algorithms in turn instruct the encoder frame by frame, bit by bit to encode the video bit rate to the available delivery bit rate.

In the above diagram, you see a theoretically perfect implementation of DBRA, where the platform follows network variations and "sticks" to the up and downs of the transmission rate.

The difference between each implementation depends largely on how aggressive or lax the algorithm is in predicting network variations. Being overly aggressive leads to decreased user experience as the encoder decreases the encoding faster than the decrease in available bandwidth while a lax implementation results in equal or worse user experience if the platform does not reduce the encoding fast enough to deplete the buffer, resulting in buffering or interruption of the playback.

Theoretically, this is a superior implementation to adaptive streaming, as it does not rely on content providers to format, maintain streams and chunks that might not be fully optimized for all network conditions (wifi, 3G, EDGE, HSPA, LTE…) and devices. It also guarantees an "optimal" user experience, always providing the best encoding the network can deliver at any point in time.

On the flip side, the technique is CAPEX expensive as real time encoding is CPU intensive.

Vendors such as Mobixell, Ortiva and others are proponents of this implementation.

Network-controlled Adaptive Streaming:

Unlike in ABR, where the device selects the appropriate bandwidth based on network availability, some vendors perform online transcoding to simulate an adaptive streaming scenario. The server feeds to the client a series of feeds whose quality vary throughout the connection and fakes the network feedback readout  to ensure a deterministic quality and size. The correct bitrate is computed from TCP connection status. More clearly, the network operator can decide at what bit rates a streaming connection should take place, spoofing the device by feeding it a manifest that does not correspond to the available delivery bit rate but to the bit rate selected by the carrier. 

This technique uses ABR as a Trojan horse. It relies on ABR for the delivery and flow control, but the device looses the capacity to detect network capacity, putting the carrier in control of the bandwidth it wants dedicated to the streaming operation.

These alternative implementations give the carrier more control over the streaming delivery on their networks. Conversely, handsets and content providers relinquish he capacity to control their user experience. The question is whether they really had control in the first place, as mobile networks are so congested that the resulting user experience is in most cases below expectations. In any case, I believe that a more meaningful coordination and collaboration between content providers, carriers and handset manufacturers is necessary to put the control of the user experience where it belongs: in the consumer's hands.