Optimal capacity and flow assignment for self-healing ATM networks based on line and end-to-end restoration

1998 ◽  
Vol 6 (2) ◽  
pp. 207-221 ◽  
Author(s):  
K. Murakami ◽  
H.S. Kim
Keyword(s):  
Atm Networks ◽  
Self Healing ◽  
Optimal Capacity ◽  
Flow Assignment ◽  
On Line ◽  
End To End

On the problem of capacity allocation and flow assignment in self-healing ATM networks

2007 ◽  
Vol 30 (16) ◽  
pp. 3169-3178 ◽  
Author(s):  
Isaac Woungang ◽  
Sudip Misra ◽  
Mohammad S. Obaidat
Keyword(s):  
Capacity Allocation ◽  
Atm Networks ◽  
Self Healing ◽  
Flow Assignment

scholarly journals Optimal Capacity And Flow Assignment For Self-Healing ATM Networks Based On Path Restoration: Nonlinear Models

2021 ◽  
Author(s):  
Faria Khandaker
Keyword(s):  
Mathematical Models ◽  
Augmented Lagrangian ◽  
Performance Metrics ◽  
Atm Networks ◽  
Self Healing ◽  
Special Aspect ◽  
Nonlinear Mathematical Models ◽  
Flow Assignment ◽  
Restoration Strategies ◽  
Installation Cost

This thesis addresses the design of self-healing Asynchronous Transfer Mode (ATM) networks which is a special aspect of a more general problem, referred to as capacity and flow assignment (CFA) problem in self-healing ATM networks. We have proposed two nonlinear mathematical models for global reconfiguration strategy and failure-oriented reconfiguration strategy in our thesis. Our restoration strategies aim to minimize the capacity installation cost and the routing cost when a single link failure occurs in the network. A special case of the augmented Lagrangian method so-called Separable Augmented Lagrangian Algorithm (SALA) is proposed for solving the proposed nonlinear mathematical models. Numerical results are presented comparing the two restoration strategies in terms of five performance metrics which are capacity installation cost, total required capacity, routing cost, total network cost and required CPU time for convergence of the algorithms. Our results show that the global reconfiguration strategy has always performed better than the failure-oriented reconfiguration strategy for all the network scenarios, topologies and bandwidth requirements.

scholarly journals Optimal Capacity And Flow Assignment For Self-Healing ATM Networks Based On Path Restoration: Nonlinear Models

2021 ◽  
Author(s):  
Faria Khandaker
Keyword(s):  
Mathematical Models ◽  
Augmented Lagrangian ◽  
Performance Metrics ◽  
Atm Networks ◽  
Self Healing ◽  
Special Aspect ◽  
Nonlinear Mathematical Models ◽  
Flow Assignment ◽  
Restoration Strategies ◽  
Installation Cost

This thesis addresses the design of self-healing Asynchronous Transfer Mode (ATM) networks which is a special aspect of a more general problem, referred to as capacity and flow assignment (CFA) problem in self-healing ATM networks. We have proposed two nonlinear mathematical models for global reconfiguration strategy and failure-oriented reconfiguration strategy in our thesis. Our restoration strategies aim to minimize the capacity installation cost and the routing cost when a single link failure occurs in the network. A special case of the augmented Lagrangian method so-called Separable Augmented Lagrangian Algorithm (SALA) is proposed for solving the proposed nonlinear mathematical models. Numerical results are presented comparing the two restoration strategies in terms of five performance metrics which are capacity installation cost, total required capacity, routing cost, total network cost and required CPU time for convergence of the algorithms. Our results show that the global reconfiguration strategy has always performed better than the failure-oriented reconfiguration strategy for all the network scenarios, topologies and bandwidth requirements.

scholarly journals A Nonlinear Model For The Optimal Capacity Placement In Self-Healing ATM Networks Based On Link Restoration Strategy

2021 ◽  
Author(s):  
ABM B. Alam
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Performance Metrics ◽  
Asynchronous Transfer Mode ◽  
Critical Issue ◽  
Self Healing ◽  
Network Failure ◽  
Optimal Capacity ◽  
Telecommunications Network ◽  
Important Challenge

Network Survivability is a critical issue in telecommunications network due to increasing dependence of the society on communication systems. Fast restoration from a network failure is an important challenge that deserves attention. This thesis addresses an optimal link capacity design problem for survivable asynchronous transfer mode (ATM) network based on the link restoration strategy. Given a projected traffic demands and the network topology, capacity and flow assignment are jointly optimized to yield the optimal capacity placement. The problem is formulated as large-scale nonlinear programming and is solved using a specific type of Lagrange method (so called Separable Augmented Lagrangian Algorithm or SALA for short). Several networks with diverse topological characteristics are used in the experiments to validate our proposed novel model, using capacity installation cost, routing cost, total network cost, used capacity and required CPU time, as performance metrics. Link restoration strategy is compared against global reconfiguration strategy using these performance metrics.

scholarly journals Palmprint Recognition in Uncontrolled and Unco-operative Environment

2021 ◽  
Vol 9 (8) ◽  
pp. 1711-1718
Author(s):  
Jayakrishnan S Kumar
Keyword(s):  
Deep Learning ◽  
Learning Rule ◽  
Industrial Applications ◽  
Palmprint Recognition ◽  
User Cooperation ◽  
Victim Identification ◽  
Palmprint Identification ◽  
On Line ◽  
End To End ◽  
Area Unit

Abstract: On-line palmprint recognition and latent palmprint identification unit two branches of palmprint studies. The previous uses middle-resolution footage collected by a camera in an exceedingly} very well-controlled or contact-based surroundings with user cooperation for industrial applications and so the latter uses high resolution latent palmprints collected in crime scenes for rhetorical investigation. However, these two branches do not cowl some palmprint footage that have the potential for rhetorical investigation. Attributable to the prevalence of smartphone and shopper camera, further proof is at intervals the variability of digital footage taken in uncontrolled and uncooperative surroundings. However, their palms area unit typically noticeable. To visualize palmprint identification on footage collected in uncontrolled and uncooperative surroundings, a novel palmprint info is established Associate in nursing AN end-to-end deep learning rule is projected. The new data named NTU Palmprints from the net (NTU-PI-v1) contains 7881 footage from 2035 palms collected from the net. The projected rule consists of Associate in Nursing alignment network and a feature extraction network and is end-to-end trainable. The projected rule is compared with the progressive on-line palmprint recognition ways that and evaluated on three public contactless palmprint infos, IITD, CASIA, and PolyU and a couple of new databases, NTU-PI-v1 and NTU contactless palmprint info. The experimental results showed that the projected rule outperforms the current palmprint recognition ways that. Keywords: Biometrics, criminal and victim identification, forensics, palmprint recognition

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