TY - GEN
T1 - File updates under random/arbitrary insertions and deletions
AU - Wang, Qiwen
AU - Cadambe, Viveck
AU - Jaggi, Sidharth
AU - Schwartz, Moshe
AU - Médard, Muriel
N1 - Publisher Copyright: © 2015 IEEE.
PY - 2015/6/24
Y1 - 2015/6/24
N2 - A client/encoder edits a file, as modeled by an insertion-deletion (InDel) process. An old copy of the file is stored remotely at a data-centre/decoder, and is also available to the client. We consider the problem of throughput- and computationally-efficient communication from the client to the data-centre, to enable the server to update its copy to the newly edited file. We study two models for the source files/edit patterns: the random pre-edit sequence left-to-right random InDel (RPES-LtRRID) process, and the arbitrary pre-edit sequence arbitrary InDel (APES-AID) process. In both models, we consider the regime in which the number of insertions/deletions is a small (but constant) fraction of the original file. For both models we prove information-theoretic lower bounds on the best possible compression rates that enable file updates. Conversely, our compression algorithms use dynamic programming (DP) and entropy coding, and achieve rates that are approximately optimal.
AB - A client/encoder edits a file, as modeled by an insertion-deletion (InDel) process. An old copy of the file is stored remotely at a data-centre/decoder, and is also available to the client. We consider the problem of throughput- and computationally-efficient communication from the client to the data-centre, to enable the server to update its copy to the newly edited file. We study two models for the source files/edit patterns: the random pre-edit sequence left-to-right random InDel (RPES-LtRRID) process, and the arbitrary pre-edit sequence arbitrary InDel (APES-AID) process. In both models, we consider the regime in which the number of insertions/deletions is a small (but constant) fraction of the original file. For both models we prove information-theoretic lower bounds on the best possible compression rates that enable file updates. Conversely, our compression algorithms use dynamic programming (DP) and entropy coding, and achieve rates that are approximately optimal.
UR - http://www.scopus.com/inward/record.url?scp=84938942101&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/ITW.2015.7133118
DO - https://doi.org/10.1109/ITW.2015.7133118
M3 - Conference contribution
T3 - 2015 IEEE Information Theory Workshop, ITW 2015
BT - 2015 IEEE Information Theory Workshop, ITW 2015
T2 - 2015 IEEE Information Theory Workshop, ITW 2015
Y2 - 26 April 2015 through 1 May 2015
ER -