Video streaming using a location-based bandwidth-lookup service for bitrate planning

  • Authors:

  • Haakon Riiser;Tore Endestad;Paul Vigmostad;Carsten Griwodz;Pâl Halvorsen

  • Affiliations:

  • Netview Technology AS, Norway, Oslo, Norway;Netview Technology AS, Norway, Oslo, Norway;Netview Technology AS, Norway, Oslo, Norway;University of Oslo and Simula Research Laboratory, Norway, Oslo, Norway;University of Oslo and Simula Research Laboratory, Norway, Oslo, Norway

  • Venue:
  • ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
  • Year:
  • 2012

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Abstract

A lot of people around the world commute using public transportation and would like to spend this time viewing streamed video content such as news or sports updates. However, mobile wireless networks typically suffer from severe bandwidth fluctuations, and the networks are often completely unresponsive for several seconds, sometimes minutes. Today, there are several ways of adapting the video bitrate and thus the video quality to such fluctuations, for example, using scalable video codecs or segmented adaptive HTTP streaming that switches between nonscalable video streams encoded in different bitrates. Still, for a better long-term video playout experience that avoids disruptions and frequent quality changes while using existing video adaptation technology, it is desirable to perform bandwidth prediction and planned quality adaptation. This article describes a video streaming system for receivers equipped with a GPS. A receiver's download rate is constantly monitored, and periodically reported back to a central database along with associated GPS positional data. Thus, based on the current location, a streaming device can use a GPS-based bandwidth-lookup service in order to better predict the near-future bandwidth availability and create a schedule for the video playout that takes likely future availability into account. To create a prototype and perform initial tests, we conducted several field trials while commuting using public transportation. We show how our database has been used to predict bandwidth fluctuations and network outages, and how this information helps maintain uninterrupted playback with less compromise on video quality than possible without prediction.