Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Performance evaluation of an optically interconnected "scheduling" switch network for Pareto traffic

Not Accessible

Your library or personal account may give you access

Abstract

Feature Issue on Optical Interconnection Networks (OIN). A performance analysis of an optically interconnected packet-scheduling switch network is presented. The scheduling switch uses a branch of feed-forward delays for each input port, interconnected with elementary optical switches to resolve contention. The scheduling switch is guaranteed to be lossless under a certain smoothness property condition. We investigate the packet-loss performance of the switch when the smoothness property condition does not hold, as well as the packet delay impairments at the edge of a scheduling switch interconnected network when this property is enforced.

© 2004 Optical Society of America

PDF Article
More Like This
Burst segmentation for void-filling scheduling and its performance evaluation in optical burst switching

Wei Tan, Sheng Wang, and Lemin Li
Opt. Express 12(26) 6615-6623 (2004)

FPGA-based implementation of two-step schedulers for modular optical interconnection networks

Justine Cris Borromeo, Isabella Cerutti, Piero Castoldi, Rosula Reyes, and Nicola Andriolli
J. Opt. Commun. Netw. 13(5) 116-125 (2021)

Simulation and FPGA-Based Implementation of Iterative Parallel Schedulers for Optical Interconnection Networks

Isabella Cerutti, Jan Alain Corvera, Samuel Matthew Dumlao, Rosula Reyes, Piero Castoldi, and Nicola Andriolli
J. Opt. Commun. Netw. 9(4) C76-C87 (2017)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.