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Content and network-aware multicast over wireless networks

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

This paper proposes content and network-aware redundancy allocation algorithms for channel coding and network coding to optimally deliver data and video multicast services over error prone wireless mesh networks. Each network node allocates redundancies for channel coding and network coding taking in to account the content properties, channel bandwidth and channel status to improve the end-to-end performance of data and video multicast applications. For data multicast applications, redundancies are allocated at each network node in such a way that the total amount of redundant bits transmitted is minimised. As for video multicast applications, redundancies are allocated considering the priority of video packets such that the probability of delivering high priority video packets is increased. This not only ensures the continuous playback of a video but also increases the received video quality. Simulation results for bandwidth sensitive data multicast applications exhibit up to 10× reduction of the required amount of redundant bits compared to reference schemes to achieve a 100% packet delivery ratio. Similarly, for delay sensitive video multicast applications, simulation results exhibit up to 3.5dB PSNR gains in the received video quality.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

  • Published - 20/10/2014

Publication status

Published - 20/10/2014

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Electronic)

9781631900259

External Publication IDs

  • ORCID: /0000-0002-2219-6142/work/129582664
  • Scopus: 84912144659

Host publication title

Proceedings of the 2014 10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QSHINE 2014