Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Distributed restoration in optical networks using feed-forward neural networks
Date
2006-07-01
Author
Karpat, Demeter Gokisik
Bilgen, Semih
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
199
views
0
downloads
Cite This
A new method is proposed for determining protection paths in an optical network where users have different characteristics in terms of reliability needs and security restrictions. Survivability is achieved by distributed mesh protection. Over the preplanned primary and backup capacity, optimal routing and wavelength assignment is carried out. In case of a network failure, protection routes and optimum flow values on these protection routes are extracted from a previously trained feed-forward neural network which is distributed over the optical data communications network.
Subject Keywords
Computer Networks and Communications
,
Hardware and Architecture
,
Electrical and Electronic Engineering
,
Software
,
Atomic and Molecular Physics, and Optics
URI
https://hdl.handle.net/11511/51014
Journal
PHOTONIC NETWORK COMMUNICATIONS
DOI
https://doi.org/10.1007/s11107-006-0014-5
Collections
Graduate School of Natural and Applied Sciences, Article
Suggestions
OpenMETU
Core
Machine learning algorithms for accurate flow-based network traffic classification: Evaluation and comparison
Soysal, Murat; Schmidt, Şenan Ece (Elsevier BV, 2010-06-01)
The task of network management and monitoring relies on an accurate characterization of network traffic generated by different applications and network protocols. We employ three supervised machine learning (ML) algorithms, Bayesian Networks, Decision Trees and Multilayer Perceptrons for the flow-based classification of six different types of Internet traffic including peer-to-peer (P2P) and content delivery (Akamai) traffic. The dependency of the traffic classification performance on the amount and composi...
Path planning for mobile-anchor based wireless sensor network localization: Static and dynamic schemes
Erdemir, Ecenaz; Tuncer, Temel Engin (Elsevier BV, 2018-08-01)
In wireless sensor networks, node locations are required for many applications. Usually, anchors with known positions are employed for localization. Sensor positions can be estimated more efficiently by using mobile anchors (MAs). Finding the best MA trajectory is an important problem in this context. Various path planning algorithms are proposed to localize as many sensors as possible by following the shortest path with minimum number of anchors. In this paper, path planning algorithms for MA assisted loca...
Sparse Attack Construction and State Estimation in the Smart Grid: Centralized and Distributed Models
Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatoş Tunay; Kulkarni, Sanjeev R.; Poor, H. Vincent (Institute of Electrical and Electronics Engineers (IEEE), 2013-07-01)
New methods that exploit sparse structures arising in smart grid networks are proposed for the state estimation problem when data injection attacks are present. First, construction strategies for unobservable sparse data injection attacks on power grids are proposed for an attacker with access to all network information and nodes. Specifically, novel formulations for the optimization problem that provide a flexible design of the trade-off between performance and false alarm are proposed. In addition, the ce...
Space-bandwidth-efficient realizations of linear systems
KUTAY, MA; ERDEN, MF; OZAKTAS, HM; ARIKAN, O; GULERYUZ, O; Candan, Çağatay (The Optical Society, 1998-07-15)
One can obtain either exact realizations or useful approximations of linear systems or matrix-vector products that arise in many different applications by implementing them in the form of multistage or multichannel fractional Fourier-domain filters, resulting in space-bandwidth-efficient systems with acceptable decreases in accuracy. Varying the number and the configuration of filters enables one to trade off between accuracy and efficiency in a flexible manner. The proposed scheme constitutes a systematic ...
Transmit Precoding for Flat-Fading MIMO Multiuser Systems With Maximum Ratio Combining Receivers
Coskun, Adem; Candan, Çağatay (Institute of Electrical and Electronics Engineers (IEEE), 2011-02-01)
We examine the application of transmit precoding in multiuser multi-input-multi-output (MIMO) communication systems with maximum ratio combining (MRC) receivers. In many multiuser applications, the maximum-likelihood or minimum mean-square error (MMSE) receivers can be prohibitive to implement due to their high implementation complexity. We examine the performance of the system with simple MRC receivers and carefully selected precoders, which are designed to compensate the lack of high-complexity receivers,...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
D. G. Karpat and S. Bilgen, “Distributed restoration in optical networks using feed-forward neural networks,”
PHOTONIC NETWORK COMMUNICATIONS
, pp. 53–64, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51014.