Space-Time Trade-off in Integer Linear Scaling Rounded to the Nearest Integer through Multiplicative and Additive Decomposition
Kyeong Soo Kim

TL;DR
This paper introduces two algorithms, MDID and ADDS, for integer linear scaling in clock skew compensation, analyzing their space-time trade-offs, overflow conditions, and equivalences to floating-point methods.
Contribution
The paper formulates a unified approach to integer linear scaling rounded to the nearest integer and proposes two novel algorithms with theoretical analysis and practical comparisons.
Findings
MDID achieves O(1) complexity when D is small but overflows otherwise.
ADDS handles all cases without overflow but with higher complexity.
ADDS with 32-bit integers is equivalent to 64-bit floating-point clock skew compensation.
Abstract
We formulate the problem of clock skew compensation as a special case of the integer linear scaling in the form of iD/A and propose two algorithms -- i.e., the multiplicative decomposition of integer division (MDID) and the additive decomposition of direct search (ADDS) -- for its nearest integer solution, which are not only immune to floating-point precision loss but also non-incremental unlike our prior approaches based on Bresenham's algorithm. Having theoretically established both decomposition algorithms based on a unified and rigorous formulation of the problem of the integer linear scaling rounded to the nearest integer, we discuss the space-time trade-off through the analysis of their computational complexities and non-overflow conditions. Through the numerical examples in a practical context of clock skew compensation under two different scenarios based on 32-bit and 64-bit…
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