Application-centric routing for video streaming over multi-hop wireless networks

  • Authors:
  • Dalei Wu;Song Ci;Haiyan Luo;Haohong Wang;Aggelos K. Katsaggelos

  • Affiliations:
  • CEEN, University of Nebraska-Lincoln;CEEN, University of Nebraska-Lincoln;CEEN, University of Nebraska-Lincoln;Marvell Semiconductors;EECS, Northwestern University

  • Venue:
  • SECON'09 Proceedings of the 6th Annual IEEE communications society conference on Sensor, Mesh and Ad Hoc Communications and Networks
  • Year:
  • 2009

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Abstract

Routing for video transmissions over multi-hop wireless networks has gained increasing research interest in recent years. However, most existing works only focus on how to satisfy the network-oriented QoS, such as, throughput, delay, and packet loss rate rather than the user perceived quality. Although there are some research efforts which use application-centric video quality as the routing metric, the calculation of video quality is based on some predefined rate-distortion function or model without exploring the impact of video coding and decoding (including error concealment) on network path selection and the resulting received video quality. Moreover, unlike network-centric routing metrics, such as, hop count, average delay or average success probability of packet transmission, video distortion cannot be calculated either additively or multiplicatively in a hop-by-hop fashion due to the dependency among packets introduced by error concealment. As a result, most existing works use either exhaustive search or heuristic methods to find the optimal path, which leads to high computational complexity or suboptimal solutions to the routing problem of video transmission. In this paper, we propose an application-centric routing framework for real-time video transmission over multi-hop wireless networks, where expected video distortion is used as the routing metric. The major contributions of this work are: 1) the development of an efficient routing algorithm with the routing metric in terms of the expected video distortion being calculated on-the-fly, and 2) the development of a quality-driven cross-layer optimization framework to enhance the flexibility and robustness of routing by the joint optimization of routing path selection and video coding, thereby maximizing the user perceived video quality under a given video playback delay constraint. Both theoretical and experimental results demonstrate that the proposed quality-driven application-centric routing approach can achieve a superior performance over existing network-centric routing approaches.