The Library
Reordering buffers for general metric spaces
Tools
Englert, Matthias, Raecke, Harald and Westermann, Matthias. (2010) Reordering buffers for general metric spaces. Theory of Computing, Vol.6 (No.1). pp. 2746. ISSN 15572862

PDF
WRAP_Englert_Reordering_buffers.pdf  Published Version  Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader Available under License Creative Commons Attribution. Download (338Kb) 
Official URL: http://dx.doi.org/10.4086/toc.2010.v006a002
Abstract
In the reordering buffer problem, we are given an input sequence of requests for service each of which corresponds to a point in a metric space. The cost of serving the requests heavily depends on the processing order. When serving a request the cost is equal to the distance, in the metric space, between this request and the previously served request. A reordering buffer with storage capacity k can be used to reorder the input sequence in a restricted fashion so as to construct an output sequence with lower service cost. This simple and universal framework is useful for many applications in computer science and economics, e. g., disk scheduling, rendering in computer graphics, or painting shops in car plants.
In this paper, we design online algorithms for the reordering buffer problem where the goal is to minimize the total cost. Our main result is a strategy with a polylogarithmic competitive ratio for general metric spaces. Previous work on the reordering buffer problem only considered very restricted metric spaces. We obtain our result by first developing a deterministic algorithm for weighted trees whose competitive ratio depends on k and the hopdiameter of the tree. Then we show how to improve this competitive ratio to O(log2 k) for metric spaces that correspond to hierarchically wellseparated trees. Combining this result with the results on the probabilistic approximation of arbitrary metrics by tree metrics due to Fakcharoenphol, Rao, and Talwar, we obtain a randomized strategy for general metric spaces that achieves a competitive ratio of O(log2 k · log n) in expectation against an oblivious adversary. Here n denotes the number of distinct points in the metric space. Note that the length of the input sequence can be much larger than n.
Item Type:  Journal Article 

Subjects:  Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software 
Divisions:  Faculty of Science > Computer Science 
Library of Congress Subject Headings (LCSH):  Buffer storage (Computer science)  Mathematical models, Metric spaces 
Journal or Publication Title:  Theory of Computing 
Publisher:  University of Chicago, Department of Computer Science 
ISSN:  15572862 
Official Date:  2010 
Volume:  Vol.6 
Number:  No.1 
Page Range:  pp. 2746 
Identification Number:  10.4086/toc.2010.v006a002 
Status:  Peer Reviewed 
Publication Status:  Published 
Access rights to Published version:  Restricted or Subscription Access 
Funder:  Deutsche Forschungsgemeinschaft (DFG), Engineering and Physical Sciences Research Council (EPSRC), University of Warwick. Centre for Discrete Mathematics and Its Applications, Sixth Framework Programme (European Commission) (FP6) 
Grant number:  WE 2842/1 (DFG), EP/F043333/1 (EPSRC), 001907 (FP6) 
References:  [1] AMJAD ABOUD: Correlation clustering with penalties and approximating the recordering buffer 
URI:  http://wrap.warwick.ac.uk/id/eprint/42236 
Request changes or add full text files to a record
Actions (login required)
View Item 
Downloads
Downloads per month over past year