File Updates Under Random/Arbitrary Insertions And Deletions
Qiwen Wang, Viveck Cadambe, Sidharth Jaggi, Moshe Schwartz, Muriel, M\'edard

TL;DR
This paper investigates efficient communication methods for updating files after random or arbitrary insertions and deletions, providing theoretical bounds and practical algorithms that are near-optimal in rate.
Contribution
It introduces models for file editing with insertions/deletions, derives lower bounds on update rates, and develops algorithms that approach these bounds.
Findings
Derived information-theoretic lower bounds on update rates.
Developed dynamic programming and entropy coding algorithms.
Achieved near-optimal compression rates for file updates.
Abstract
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…
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Taxonomy
TopicsDNA and Biological Computing · Cellular Automata and Applications · Advanced Data Storage Technologies
