File Updates Under Random/Arbitrary Insertions and Deletions

The problem of one-way file synchronization, henceforth called “file updates”, is studied in this paper. Specifically, a client edits a file, where the edits are modeled by insertions and deletions (InDels). An old copy of the file is stored remotely at a data-centre, 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 data-centre to update its old copy to the newly edited file. Two models for the source files and edit patterns are studied: 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 and deletions is a small (but constant) fraction of the length of the original file. For both models, information-theoretic lower bounds on the best possible compression rates that enable file updates are derived (up to first order terms). Conversely, a simple compression algorithm using dynamic programming (DP) and entropy coding (EC), henceforth called DP-EC algorithm, achieves rates that are within constant additive gap (which diminishes as the alphabet size increases) to information-theoretic lower bounds for both models. For the RPES-LtRRID model, a dynamic-programming-run-length-compression (DP-RLC) algorithm is proposed, which achieves a compression rate matching the information-theoretic lower bound up to first order terms. Therefore, when the insertion and deletion probabilities are small (such that first order terms dominate), the achievable rate by DP-RLC is nearly optimal for the RPES-LtRRID model.