Paper Info
Title
Private Streaming With Convolutional Codes
Abstract
Recently, information-theoretic private information retrieval (PIR) from coded storage systems has gained a lot of attention, and a general star product PIR scheme was proposed. In this paper, the star product scheme is adopted, with appropriate modifications, to the case of private ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</italic> , video) streaming. It is assumed that the files to be streamed are stored on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> servers in a coded form, and the streaming is carried out via a convolutional code. The star product scheme is defined for this special case, and various properties are analyzed for two channel models related to straggling and Byzantine servers, both in the baseline case as well as with colluding servers. The achieved PIR rates for the given models are derived and, for the cases where the capacity is known, the first model is shown to be asymptotically optimal, when the number of stripes in a file is large. The second scheme introduced in this work is shown to be the equivalent of block convolutional codes in the PIR setting. For the Byzantine server model, it is shown to outperform the trivial scheme of downloading stripes of the desired file separately without memory.
Year
DOI
Venue
2020
10.1109/TIT.2019.2963872
IEEE Transactions on Information Theory
Keywords
DocType
Volume
Convolutional codes,multimedia streaming,privacy,private streaming
Journal
66
Issue
ISSN
Citations 
4
0018-9448
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Lukas Holzbaur166.35
Ragnar Freij-Hollanti2507.58
Antonia Wachter-Zeh312933.65
Camilla Hollanti430840.21