Resource Augmentation
Data Structures and Algorithms
2020-07-28 v1
Abstract
This chapter introduces resource augmentation, in which the performance of an algorithm is compared to the best-possible solution that is handicapped by less resources. We consider three case studies: online paging, with cache size as the resource; selfish routing, with capacity as the resource; and scheduling, with processor speed as the resource. Resource augmentation bounds also imply "loosely competitive" bounds, which show that an algorithm's performance is near-optimal for most resource levels.
Cite
@article{arxiv.2007.13234,
title = {Resource Augmentation},
author = {Tim Roughgarden},
journal= {arXiv preprint arXiv:2007.13234},
year = {2020}
}
Comments
Chapter 4 of the book Beyond the Worst-Case Analysis of Algorithms, edited by Tim Roughgarden and published by Cambridge University Press (2020)