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Optoelectronic neural-network scheduler for packet switches.
R P Webb1, A J Waddie, K J Symington
1British Telecom Laboratories, Martlesham Heath, Ipswich IP5 3RE, UK.
Applied Optics
|March 14, 2008
Summary
A novel neural network packet scheduler offers superior performance. It utilizes a winner-take-all strategy and free-space optics for high-density interconnections, outperforming current technologies.
Area of Science:
- Computer Science
- Optical Engineering
- Artificial Intelligence
Background:
- Current packet schedulers face limitations in performance and scalability.
- High interconnection density presents a significant challenge in modern network design.
Purpose of the Study:
- To introduce a novel packet scheduler design.
- To demonstrate a significant performance improvement over state-of-the-art schedulers.
- To address challenges in high interconnection density.
Main Methods:
- Developed a packet scheduler employing a neural network with a winner-take-all strategy.
- Integrated a free-space optical interconnect using diffractive optics.
- Optimized decisions for crossbar and banyan switching fabrics.
Main Results:
- The novel scheduler demonstrated potential for significant performance outperformance.
- The free-space optical interconnect effectively solved high interconnection density problems.
- The experimental implementation proved fully operational.
Conclusions:
- The proposed neural network-based packet scheduler is a promising advancement.
- Free-space optical interconnects offer a viable solution for dense network architectures.
- This approach could redefine the capabilities of high-performance network schedulers.
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