Distributed approaches for impairment-aware routing and wavelength assignment algorithms in GMPLS networks

Pavani, Gustavo Sousa; Zuliani, Luiz Gustavo; Waldman, Hélio; Magalhães, Mauricio Ferreira

doi:10.1016/j.comnet.2008.02.010

Cited by 30 publications

(19 citation statements)

References 25 publications

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“…The noise modeling for n i is obtained according to the recursively model detailed in the Appendix [10]; the noise contribution of each amplifier (N ASE ) is given by…”

Section: B Optical Signal Noise Ratio Modelmentioning

confidence: 99%

“…The QoS is related to the OSNR, dispersion, and nonlinear effects those are represented by the quality-of-transmission (QoT) [5] [7]. Therefore, it is desirable to adjust network parameters such as optical transmitted power, amplifier gain, OADMs/OXCs power losses in an optimal way, based on online decentralized iterative algorithms, to accomplish such adjustment [7]- [9] [10]. The OSNR optimization could be integrated with RWA, considering the OSNR optimization procedure implemented after the routing step and the lightpath assignment have been established [10].…”

mentioning

confidence: 99%

“…Therefore, it is desirable to adjust network parameters such as optical transmitted power, amplifier gain, OADMs/OXCs power losses in an optimal way, based on online decentralized iterative algorithms, to accomplish such adjustment [7]- [9] [10]. The OSNR optimization could be integrated with RWA, considering the OSNR optimization procedure implemented after the routing step and the lightpath assignment have been established [10]. This approach is conveyed to the generalized multiprotocol label switching (GMPLS) signaling protocol in order to allocate the available power resources if and only if the connection meets OSNR constraints.…”

mentioning

confidence: 99%

“…The OSNR optimization algorithms are related to the optical channel estimation in the lighpath route or in the receiver node [7]- [10]. The estimation process is based on combinations and 3 interpolations of optical performance monitors (OPM) measurements, as well as in analytical models and numerical simulations [11]- [13].…”

mentioning

confidence: 99%

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Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Durand

Lopes

Spagolla

et al. 2016

J. Microw. Optoelectron. Electromagn. Appl.

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Abstract-In this work, we investigate the effects of estimation uncertainties in the optimization of the optical signal-to-noise ratio (OSNR) at the wavelength division multiplexing (WDM) optical networks. The OSNR optimization increases the network throughput and energy efficiency and it enables to minimize the number of retransmissions by higher layers. The OSNR optimization algorithms are related to the optical channel estimation performed by the combinations of optical performance monitors (OPM) measurements, analytical models and numerical simulations. Furthermore, the estimation uncertainties are introduced by several factors such as the availability of monitoring information, monitoring accuracy, imperfection of physical layer and dynamic of channel allocation. Our numerical results have demonstrated the relation between the uncertainties in the channel error estimation, normalized mean squared error (NMSE) and power penalty. The developed methodology can be utilized to determinate the maxim level of acceptable uncertainties in the channel error estimation according the power penalty permitted in the OSNR optimization.

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“…The noise modeling for n i is obtained according to the recursively model detailed in the Appendix [10]; the noise contribution of each amplifier (N ASE ) is given by…”

Section: B Optical Signal Noise Ratio Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Durand

Lopes

Spagolla

et al. 2016

J. Microw. Optoelectron. Electromagn. Appl.

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“…Based on information collected by each agent and the information left behind at every node by all agents, iteratively decentralised routing information is created. In Pavani et al 2008), a distributed IA-RWA scheme based on ant colony optimisation paradigm is presented. The next hop (outgoing optical channel) is determined based on a preference value (pheromone-level) derived from the information left behind by ants that previously passed.…”

Section: Ant Colony Optimisationmentioning

confidence: 99%

Signal Processing, Management and Monitoring in Transmission Networks

Vázquez

Montalvo

Ahmed

et al. 2011

Optical Transmission

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1higher, linear and non-linear fibre impairments become prominent factors affecting the signal quality. Thus, new techniques in both physical layer and network layer are necessary for mitigating impairments to accommodate high-speed traffic (Tomkos et al. 2002). On the other hand, the flexibility of modern networks with dynamic and distributed management, where lightpaths can be dynamically and automatically assigned end-to-end, increases the risk of changing path conditions that affect signal quality and consequently quality of service (QoS) over the lifetime of a connection as well as for subsequent connection set-up requests (on-demand routing and wavelength assignment -RWA). For traditional connection provisioning an ideal physical layer, ignoring transmission impairments (Chlamtac et al. 1992) could be assumed because the implicit per hop regeneration (optics-to-electronics-to-optics conversion -O/E/O) compensated signal impairments hop-by-hop in a rather static manner (section commissioning). For end-to-end all-optically switched connections using photonic cross-connect switches (PXC), the conditions change and common practice is not applicable. Anyhow, intelligent connection provisioning is an important traffic engineering problem, and minimising operational cost as well as efficiently utilising network resources is the main driver. In this context, it seems important to have flexible routing protocols that take into consideration the most relevant physical impairments, and are able to exchange messages with their values as part of the route information with others. This condition, if definitely used to calculate routing, will surely assure better success in data delivery over the network (Huang et al. 2005). Irrespective of the control architecture chosen by an operator of an optical network, the included control plane (in charge of setting up and tearing down optical circuits; also known as lightpaths) needs to have a proper set of tools to satisfyingly deal with physical impairments. The most essential tools are: optical signal monitoring, signal processing and impairment compensation techniques (each all-optically and/or electrically). With the help of these tools, it is possible to predict the QoT (quality of transmission) attainable for a lightpath at a given time (i.e. the latest network-wide monitoring instant), and the control plane can route requests across the network

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Introduction to Optical Packet Switched (OPS) Networks

Rahbar¹

2015

Quality of Service in Optical Packet Switched Networks

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Distributed approaches for impairment-aware routing and wavelength assignment algorithms in GMPLS networks

Cited by 30 publications

References 25 publications

Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Signal Processing, Management and Monitoring in Transmission Networks

Introduction to Optical Packet Switched (OPS) Networks

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