Developing a Method for Measuring the Failover Times of First Hop Redundancy Within Video Networks

Research output: Chapter in Book/Report/Published conference proceedingChapter

Abstract

IP protocols have been used to distribute compressed media over private and public networks for a number of years. Recently the broadcast sector has started to adopt IP technologies to transport real time media within and between their facilities during production. However, the high bitrate of uncompressed media and its sensitivity to latency and timing variations requires careful design of the network in order to maintain quality of service. Connectionless protocols are commonly used, which means that packet loss is of particular concern and redundant paths must be provisioned with mechanisms to switch between them. This project develops and critically analyses a method for measuring the effectiveness of first hop redundancy protocols for broadcast video production networks. The aim extends previous work [1] to recommend particular configurations to optimise networks and to provide a method that broadcast engineers can use to verify performance. Cisco’s HSRP is recommended with static routes configured for redundant paths. It is recommended that the network is tested using a synthetic RTP stream with a low complexity packet sniffer and NICs with hardware timestamps. Further work is identified including ways to improve the accuracy of the results and to consider the impact of more complex networks.
Original languageEnglish
Title of host publicationRecent Advances in Computational Optimization
Subtitle of host publicationResults of the Workshop on Computational Optimization WCO 2017
EditorsStefka Fidanova
PublisherSpringer
Pages1-15
ISBN (Electronic)978-3-319-99648-6
Publication statusPublished - 20 May 2019

Publication series

NameStudies in Computational Intelligence
PublisherSpringer

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Bourne, P., Palmer, N., & Skrabala, J. (2019). Developing a Method for Measuring the Failover Times of First Hop Redundancy Within Video Networks. In S. Fidanova (Ed.), Recent Advances in Computational Optimization: Results of the Workshop on Computational Optimization WCO 2017 (pp. 1-15). (Studies in Computational Intelligence). Springer.