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Optimal Wavelength Scheduling in Optical Burst-Switched Networks Using Constant Time Burst Resequencing

Authors: Yuhua Chen; Jonathan S. Turner; Pu-Fan Mo;

Optimal Wavelength Scheduling in Optical Burst-Switched Networks Using Constant Time Burst Resequencing

Abstract

Optical burst switching (OBS) is an emerging technology that allows variable size data bursts to be transported directly over DWDM links. In order to make OBS a viable solution, the wavelength scheduling algorithms need to be able to utilize the available wavelengths efficiently, while being able to operate fast enough to keep up with the burst incoming rate. For example, for a system with 32 wavelengths per link, each operating at 10 Gb/s, we need to process one BHC every 25 ns, in order to support an average burst length of 1 KByte. When implemented in hardware, the running time of the well-known horizon scheduler is O(1) for practical numbers of wavelengths. Unfortunately, horizon scheduling cannot utilize the voids created by previously scheduled bursts, resulting in low bandwidth utilization. To date, Min-SV is the fastest scheduling algorithm that can schedule wavelengths efficiently. However, its complexity is O(log m) and it requires 10log m memory accesses to schedule a single burst. This means that it can take up to several microseconds for each burst request, which is still too slow to make it a practical solution for OBS deployment. In this paper, we propose an optimal wavelength scheduler using constant time burst resequencing (CTBR), which runs in O(1) time. The proposed CTBR scheduler is able to produce optimal wavelength schedules while having the same processing speed as the horizon scheduler. The algorithm is well-suited to high performance hardware implementation.

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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!
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