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Journal of Mathematics Research
Article . 2009 . Peer-reviewed
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Journal of Mathematics Research
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Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches

Authors: Liew, S.Y.; Wong, E.S.K.;

Accounting Information Systems Genetic Algorithms for All-Optical Shared Fiber-Delay-Line Packet Switches

Abstract

All-optical shared fiber-delay-line (FDL) packet switches have been studied intensively in the literature and with theliterature, many scheduling genetic algorithms have been proposed. However, these genetic algorithms suffer from notbeing able to provide a delay bound, or require complex timing methods to compute scheduling assignments. In thispaper, we propose two fast scheduling algorithms for all-optical shared-FDL packet switches. In the first algorithm,packet scheduling is formulated as a tree-searching problem. This is accomplished by breaking down the search tree intomultiple smaller subsets and assigning each subset to a parallel processor. By using this method, scheduling solutions canbe obtained in a shorter time. Although this approach is superior to other algorithms, its overall complexity and processingoverheads are still too high to warrant its day to day use. In the second algorithm, the search tree is carefully trimmeddown in order to reduce complexity and overheads. The conclusion will consider a 32 × 32 switch with 32 FDLs, andassume a processor clock rate of 200MHz for schedulers. With this new and second algorithm, a scheduling assignmentcan be calculated for a given packet in 30ns if 8 parallel processors are employed and we show by simulation that bothalgorithms can achieve a loss rate of ? 10?7 even at load 0.9, where the average delay is 11.5 timeslots.

Keywords

HF Commerce, 006

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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