The complexity of computation in bit streams
Raphael Clifford, Markus Jalsenius, Benjamin Sach

TL;DR
This paper introduces a new proof technique to establish meaningful lower bounds for online computation problems in the cell probe model, especially when input alphabet sizes are constant, with applications to pattern matching and convolution.
Contribution
The authors develop a novel lop-sided information transfer method that yields the first non-trivial cell probe lower bounds for online problems on bit streams with large cell sizes.
Findings
Proved an lower bound for pattern matching with address errors.
Established the same lower bound for online convolution under a new conjecture.
Provided the first meaningful bounds for online problems with constant alphabet size.
Abstract
We revisit the complexity of online computation in the cell probe model. We consider a class of problems where we are first given a fixed pattern or vector of symbols and then one symbol arrives at a time in a stream. After each symbol has arrived we must output some function of and the -length suffix of the arriving stream. Cell probe bounds of have previously been shown for both convolution and Hamming distance in this setting, where is the size of a symbol in bits and is the cell size in bits. However, when is a constant, as it is in many natural situations, these previous results no longer give us non-trivial bounds. We introduce a new lop-sided information transfer proof technique which enables us to prove meaningful lower bounds even for constant size input alphabets. We use our new framework to prove…
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Taxonomy
TopicsDNA and Biological Computing · Algorithms and Data Compression · Cellular Automata and Applications
