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

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, e.g., using scalable video codecs or segmented adaptive HTTP streaming that switches between non-scalable 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 paper 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.

Mobile video streaming using location-based network prediction and transparent handover

“…However, to the best of our knowledge, no other system integrates everything into one solution and presents a running prototype with real-world experiments, i.e., they do not experience all the possible real-world complications [10,17]. Our solution predicts the availability of several networks and their bandwidths at the different locations along the path, and then it plans and adapts video quality to available bandwidth for a mobile device.…”

“…In [17], we introduced a GPS-based bandwidth lookup service. For the solution presented in this paper, we extended the lookup service with support for storing information about different alternative networks (shown in figure 2).…”

“…Knowing network availability and bandwidth oscillations that have been measured by other clients before, the streaming system can calculate the estimated number of bytes that it can download during the remaining time of the trip. This technique is explained in detail in [17]. Using this approach, it is possible to predict the amount of data that can be downloaded in the future to smooth the video quality over the whole session.…”

“…Our streaming system provides two video quality schedulers (described in detail in [17]) a reactive and a predictive algorithm. The reactive algorithm is basically intended for sessions where predictions are unavailable, and the quality levels that are chosen are decided by current bandwidth and buffer fullness.…”

“…The solution is based on our bandwidth prediction service [17] for commuters, which uses a lookup service to predict 3G (HSDPA) bandwidth availability based on the geographical location of a device. We extend this by combining it with a technique for transparent network roaming and connection handover, without requiring operating system (OS) modifications or introducing new network protocols.…”