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

Abstract

A well known challenge with mobile video streaming is fluctuating bandwidth. As the client devices move in and out of network coverage areas, the users may experience varying signal strengths, competition for the available resources and periods of network outage. These conditions have a significant effect on video quality.In this paper, we present a video streaming solution for roaming clients that is able to compensate for the effects of oscillating bandwidth through bandwidth prediction and video quality scheduling. We combine our existing adaptive segmented HTTP streaming system with 1) an application layer framework for creating transparent multi-link applications, and 2) a location-based QoS information system containing GPS coordinates and accompanying bandwidth measurements, populated through crowd-sourcing. Additionally, we use real-time traffic information to improve the prediction by, for example, estimating the length of a commute route. To evaluate our prototype, we performed realworld experiments using a popular tram route in Oslo, Norway. The client connected to multiple networks, and the results show that our solution increases the perceived video quality significantly. Also, we used simulations to evaluate the potential of aggregating bandwidth along the route.

Multipath aggregation of heterogeneous access networks

“…A solution to this problem is to set up a virtual network by encapsulating all traffic, similar to the method suggested in [132] and the configuration we employ in Section 5.2.1. An approach that is part of our future work is the MULTI [47] framework, our successor to NAMA. MULTI builds an overlay network between a proxy and multihomed clients and uses virtual interfaces and IP tunneling to enable multipath aggregation and vertical handover.…”

“…A more promising method could involve the receiver to restore order in the packet requence, similar to the approach followed by MPTCP [57]. An improved version of the NAMA prototype that has already picked up momentum is our generic and modular MULTI [47] framework, which targets easy deployment and multipath support for all transport protocols and applications.…”

Adaptive Media Streaming to Mobile Devices: Challenges, Enhancements, and Recommendations

“…To compare the algorithms on equal terms, one is tested in the real-world setting and the other is simulated using the exact same bandwidth trace. Experiments where the simulated and the real-world algorithms are switched are presented in [10,11] with similar results.…”

“…As a further enhancement, we combined the predictive adaptation algorithms with the multilink solution presented in Section 7 [11]. Multiple test runs were performed to make sure the system discovered areas with higher bandwidth networks.…”

Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users

“…Han et al [21] investigated the extent to which the available user mobile channel bandwidth is affected by constraints including location, time, speed, humidity and cellular network type (3G/4G). Their scheme, called MASERATI, outperformed Pure-DASH and LoDASH, where Pure-DASH only uses the download throughput and LoDASH uses location based bandwidth predictions as in [22], [18].…”