Verizon Wireless is deploying optimization technology in parts of its 3G mobile broadband network.  This network management technology is designed to transmit data more efficiently, ease capacity burdens on the network, primarily from video files, and improve the user experience with faster downloads and decreased Internet latency.

     Given the increasing web traffic for downloading video files, video optimization in particular benefits both the user as well as the network by facilitating sustainable online video browsing using only the required amount of data while enhancing the video experience and making room for other users to enjoy higher browsing speeds.  Although much effort is invested to avoid changing the file during optimization, and while any change to the file is likely to be indiscrnabile, the process may minimally impact the appearance of the file as displayed on a device. 

    The optimization techniques are applied to all content files coming from the Internet Port 80 that use the most common compression formats.  The form and extent of optimization depends on the compression format of the content file, but does not depend on the content of the file, the originating web site, or the user’s device.  No distinction in the application of these techniques is made based on the source website or originator of the content.  The system optimizes files based strictly on the type of file and the relevant file formats (recognizing that some file types are not modified).   Accordingly, all content, including Verizon Wireless branded content, of the same type will be subject to the same process.

     Why Optimization?  Delivering content files requested by an end user over the Internet always imposes some burden on the delivery network in terms of size of the file as well as the distance the file components must travel between the source and end user.  These factors also directly affect the user experience in downloading the file.

     The burden on the network can be mitigated and the speed and efficiency of delivery to the end user can be improved if the network deploys techniques to “optimize” or streamline content files.  For example, the size of the file can be compressed by removing pieces of information that are not usable by the end user’s mobile device, or that are not noticeable to the user.  Caching the file for subsequent requests can also reduce the time needed for delivery to end users.  Such network management techniques improve the user experience without noticeable impact on the content itself.

     How Optimization Works.  All HTTP (Port 80, i.e., World Wide Web) traffic is directed to the optimization process.   The direction of traffic to the optimization process is established when the user starts an HTTP data session before any requests for content from a specific web site have been made.  Accordingly, content files are not selected for optimization based on the nature of the web content itself or the source or provider of the web content file.  All web content files delivered over Port 80, regardless of source, are directed to the optimization process.  The system thus captures all Verizon Wireless branded web content delivered from its web servers, and treats such content in the same way as content of the same type requested from non-Verizon Wireless sites on the Internet.

      Content files made available on the World Wide Web come in a variety of types (web pages, text, image, video) and formats.  The process incorporates several optimization techniques that depend upon the specific type of content file.  Specifically, text files are compressed without any loss of information (“lossless”) and cached for subsequent end user requests.  Image files (PNG, JPEG, GIF formats, for example) are streamlined to remove colors or other data bits that would not be visible to the human eye, or to end users on a mobile device with limited display resolutions, thereby decreasing the size of the file, and also cached.  The output image file reflects “lossy” optimization because some data bits from the original file are lost in the optimization process.

     Video Optimization.  Video files represent a substantial and growing segment of web traffic, and also come in a variety of formats.  Optimization only captures recorded video files and does not affect live streaming video, e.g., a video conference call.  Several optimization techniques are applied to video files: transcoding, caching, and buffer tuning.  All are agnostic as to the source or content of the video.

     Transcoding.  When preparing a video file for posting on a web site, the video originator must select a codec (compression/decompression format) for the file.  All codecs are “lossy” to some degree in the compression process in that they reduce the quality of the original video.  But, some codecs are more efficient than others.  Optimization transcodes video files from their source codecs to a more efficient codec, H.264.  If the requesting device cannot decode an H.264 file, the file is delivered in the input codec.  Also, if the input file codec is H.264, there will be little or no effect on the file from the processes described below.

     The goal of this optimization process is to reduce the content file size while maintaining very similar video quality.  Re-quantization levels, that is, the size of the output file, are defined by the output video bit rate settings (based on a percentage from the original).  The loss of information from the input file may result in reduced color accuracy and sharpness of the output video.  These effects are offset with optimized de-blocking and smoothing algorithms to retain good perceptual visual quality (as measured by objective video quality tools discussed below).  In addition, videos are sent with variable bit rate (VBR), which provides more consistent quality at the same bit rate. 

     Optimization processes can range in how aggressively they pursue content file savings.  Verizon Wireless is using the Video Quality Measurement (VQM) tool to set the amount of reduction in a video file size.  VQM is a standardized method of objectively measuring video quality that closely predicts the subjective quality ratings that would be obtained from a panel of human viewers.  Although the tool is free, the technology is covered by four U.S. patents owned by NTIA/ITS.  The compression settings utilized equate to a .4-.6 score on the VQM scale, which is considered an “unnoticeable” change.

    Caching.  When a video file is detected from the Internet stream, the system decodes the first few frames (8 KB) of the video.  Based on those frames, the system attempts to locate the video file in its video cache, and, if the file is not in the cache, it copies the video file, catalogs, optimizes and places it into the video cache.  (The system needs to look at the first few frames for the cataloging process because the same video may come to the network from different sources and would have different URLs and headers; so, the header information is insufficient to identify multiple copies of the same video.)  The caching process is the same regardless of the source or content of the video.

    When a requested video is not in cache initially, the input video file is sent on to the requesting device.  When the system finds the video in its cache, then the flow from the Internet stops, and the video is replaced with file from the cache.  The video cache will retain the video, until the staleness filter flushes it from cache.  The video cache has a finite volume so it will regularly flush unused videos.

     Buffer Tuning.  The third video optimization technique is used in delivery to end users.  Whenever the video is requested, it is delivered on a "just in time" basis.  That is, rather than the entire file being downloaded when requested, the video is downloaded on an as needed basis.  A sufficient amount of video would be delivered to fill the user’s buffer to start viewing, and the remainder would be delivered as needed in time for the viewer to see it without interrupting the flow, calculating the video bit-rate and the actual bandwidth available.  This progressive download achieves significant network savings if the viewer chooses not to view the entire video, and it conserves data usage that would count toward the end users’ data allowance, and may result in savings if the end user is on a pay-for-usage plan.  As with caching, the buffer tuning process is the same regardless of the source or content of the video.

      These video optimization techniques generally reduce the time for a video to start and eliminate external network fluctuations that sometimes cause videos to stall. They also speed up the time for the video to pick up when jumping forward in the video.  The cache responds to the video request much faster than a remote location.  Because each video player needs to accumulate a certain amount of video seconds, the “buffer”, before the video actually starts playing, a smaller video will use the same amount of seconds to transmit less data as the original video, and, when delivered at the same speed, will result in faster buffer accumulation and therefore a faster start. The end result is a much smoother video that starts faster.