Flexible bandwidth assignment with application to optical networks

Flexible bandwidth assignment with application to optical networks We introduce two scheduling problems, the flexible bandwidth allocation problem ( $$\textsc {FBAP}$$ FBAP ) and the flexible storage allocation problem ( $$\textsc {FSAP}$$ FSAP ). In both problems, we have an available resource, and a set of requests, each consists of a minimum and a maximum resource requirement, for the duration of its execution, as well as a profit accrued per allocated unit of the resource. In $$\textsc {FBAP}$$ FBAP , the goal is to assign the available resource to a feasible subset of requests, such that the total profit is maximized, while in $$\textsc {FSAP}$$ FSAP we also require that each satisfied request is given a contiguous portion of the resource. Our problems generalize the classic bandwidth allocation problem (BAP) and storage allocation problem (SAP) and are therefore $$\text {NP-hard}$$ NP-hard . Our main results are a 3-approximation algorithm for $$\textsc {FBAP}$$ FBAP and a $$(3+\epsilon )$$ ( 3 + ϵ ) -approximation algorithm for $$\textsc {FSAP}$$ FSAP , for any fixed $$\epsilon >0 $$ ϵ > 0 . These algorithms make nonstandard use of the local ratio technique. Furthermore, we present a $$(2+\epsilon )$$ ( 2 + ϵ ) -approximation algorithm for $$\textsc {SAP}$$ SAP , for any fixed $$\epsilon >0 $$ ϵ > 0 , thus improving the best known ratio of $$\frac{2e-1}{e-1} + \epsilon $$ 2 e - 1 e - 1 + ϵ . Our study is motivated also by critical resource allocation problems arising in all-optical networks. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Scheduling Springer Journals

Flexible bandwidth assignment with application to optical networks

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media New York
Subject
Business and Management; Operations Research/Decision Theory; Calculus of Variations and Optimal Control; Optimization; Optimization; Artificial Intelligence (incl. Robotics); Supply Chain Management
ISSN
1094-6136
eISSN
1099-1425
D.O.I.
10.1007/s10951-017-0514-4
Publisher site
See Article on Publisher Site

Abstract

We introduce two scheduling problems, the flexible bandwidth allocation problem ( $$\textsc {FBAP}$$ FBAP ) and the flexible storage allocation problem ( $$\textsc {FSAP}$$ FSAP ). In both problems, we have an available resource, and a set of requests, each consists of a minimum and a maximum resource requirement, for the duration of its execution, as well as a profit accrued per allocated unit of the resource. In $$\textsc {FBAP}$$ FBAP , the goal is to assign the available resource to a feasible subset of requests, such that the total profit is maximized, while in $$\textsc {FSAP}$$ FSAP we also require that each satisfied request is given a contiguous portion of the resource. Our problems generalize the classic bandwidth allocation problem (BAP) and storage allocation problem (SAP) and are therefore $$\text {NP-hard}$$ NP-hard . Our main results are a 3-approximation algorithm for $$\textsc {FBAP}$$ FBAP and a $$(3+\epsilon )$$ ( 3 + ϵ ) -approximation algorithm for $$\textsc {FSAP}$$ FSAP , for any fixed $$\epsilon >0 $$ ϵ > 0 . These algorithms make nonstandard use of the local ratio technique. Furthermore, we present a $$(2+\epsilon )$$ ( 2 + ϵ ) -approximation algorithm for $$\textsc {SAP}$$ SAP , for any fixed $$\epsilon >0 $$ ϵ > 0 , thus improving the best known ratio of $$\frac{2e-1}{e-1} + \epsilon $$ 2 e - 1 e - 1 + ϵ . Our study is motivated also by critical resource allocation problems arising in all-optical networks.

Journal

Journal of SchedulingSpringer Journals

Published: Mar 4, 2017

References

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