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D-26, Munich

D-26, Munich. An Approach to Dynamic Optical Transparent Network Simulations [D26] Simone De Patre, Stefano Santoni. RFWA Background. RWA is referred to as the algorithm to determine a route and corresponding wavelength on each fiber along the route for the lightpath.

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D-26, Munich

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  1. D-26, Munich • An Approach to Dynamic Optical Transparent Network Simulations [D26] Simone De Patre, Stefano Santoni NOBEL Plenary Munich 2005

  2. RFWA Background • RWA is referred to as the algorithm to determine a route and corresponding wavelength on each fiber along the route for the lightpath. • the objective of a RWA problem in dynamic network is to optimize the network performance, in terms of network blocking probability or network utilization. • the RWA problem remains at a theoretical level without considering optical layer impairments. • Physical layer impairment is a critical constraint for designing optical switched networks. • The accumulated impairments without regeneration will result in a high bit error rate (BER), which in turn increases the network blocking probability. • Physical Impairments = Implications for Routing NOBEL Plenary Munich 2005

  3. RFWA: A Layered Graph Approach • For a given physical network topology PG(N,L) an auxiliary graph LG(W) is created • W is the maximum number of wavelength channel supported by a transmission system (i.e. 40/80 channels) • N is the set of nodes, L is the set of bidirectional fiber link • LG(W) is such that each layer graph is initialized to be the same of PG • Routing decision are made on this auxiliary graph solving Shortest Path Algorithm (i.e. Dijkstra) • Worst case complexity: where F is the maximum number of fiber/system for link NOBEL Plenary Munich 2005

  4. (LG) Layered Graph transparent layers No vertical arcs representing wavelength conversions and regenerations NOBEL Plenary Munich 2005

  5. Network Design: RFWA • Routing criteria • SPR - Shortest path: any representative additional metrics possible • Number of hops (mH) • Physical path length (mL) • Path Cost (mC) • LLR - Least loaded routing: based on average link utilization along a path • SCR – Shortest Cycle (for DPP demands) • Fiber / wavelength assignment criteria • FF - First fit: the first free in a preordered list (based on channel physical characteristic) • MU / LU - Most / Least used: based on current wavelength utilization (network state) • RAND – Random choice • QBF – Q-marginBest First (minimum margin first) • Prioritized multiple RWFA criteria • More of the above criteria are combined in a priority list • When comparing two paths in the LG(W), ties according to criterion i are broken using criterion i + 1 • Each arc aw,f of the LG(W) is assigned an array of weights NOBEL Plenary Munich 2005

  6. (R) problem: minimum cost (mC) • Network Cost is evaluated according to a simplified cost structure (Matthias Gunkel) [D26] • Normalized cost based on averaged cost derived from vendors prices • Transponder (Long Haul, Extended Long Haul, Ultra Long Haul) • Terminal (Fixed amount and variable amount function of Mux/Demux granularity) • Link (fiber length, Km) • R-OADM / R-OXC (node degree N, traffic relation R) • Minimum Cost Routing will select the path pmC(s,d)such that where is the set of mC SPRs NOBEL Plenary Munich 2005

  7. Survivability • Survivability technique: dedicated path-protection • Each connection-request is satisfied by a lightpath pair (working + protection) • RFWA must be performed in such a way that working and protection lightpaths are edge-disjoint (also node-disjoint) • Bhandari algorithm (based on modified Dijkstra Algorithm) to determine the minimum cycle between end-nodes (SCR) NOBEL Plenary Munich 2005

  8. Physical Impairments • Considered Impairments • ASE noise (OSNR) • PMD • Impairments to be introduced in future releases • Filtering effects • XTK (Crosstalk) • FWM (Four Wave Mixing) • SPM (Self Phase Modulation) • XPM (Cross Phase Modulation) non linear effects NOBEL Plenary Munich 2005

  9. Optical Feasibility Algorithm • After computing a route between a connection source and destination, we check a simple Q constraint: • a path can be accepted only if its estimated Q-factor is above a threshold , and if the Q-factors of all LPs previously established in the network remain above the threshold • Assumption: we introduce a Q-factor margin to take into account the inter channel effects • no iterative checking each time the previous established connections • Assumption is acceptable because the considered impairments affect wavelengths individually • Q-factor threshold is the minimum target performance at the receiver • A path is feasible if the minimum acceptable performance is guaranteed NOBEL Plenary Munich 2005

  10. Optical Feasibility Algorithm - details NOBEL Plenary Munich 2005

  11. OSNR modelling • Q has been selected in NOBEL as the metric quantity for baseline performance [D13] • Q is related to OSNR (R) using the Marcuse-Desurvire formula NOBEL Plenary Munich 2005

  12. PMD modelling • In the semi-analytical model developed in D19 the Q-factor penalty due to PMD depends on the lightpath baseline Q (ASE) • The number of realisation for D19 was high (40,000), but needs to be at least 100,000 • New simulations to cover with 100,000 samples the range of mean DGD values from 5 psec to 30 psec in 2.5 psec steps • Expected results: table reporting, for each baseline Q value (form 11 dB to 20 dB) and for each mean DGD values, the Q-factor penalty corresponding to a certain outage probability (10-5) • The table represents the repository for the assessment of Q-factor penalty in the optical viability algorithm NOBEL Plenary Munich 2005

  13. PMD modelling • The table reports the Qpenalty corresponding to a certain outage probability (10-5) NOBEL Plenary Munich 2005

  14. Filtering Effects Modelling • The purpose is to analyze the impact of some ROADM/OXC filter constructive technology on filtering effects (Q-penalty) of a cascade of ROADM/OXC. The analysis is carried out considering the impact of some design parameters on the filter shape (amplitude and phase) and also considering the effect of channel laser frequency stability. Filter characteristics will reflect some basic ROADM technologies (i.e. AWG-based, rings, grating). • Results will be integrated into the next version of the Feasibility Algorithm NOBEL Plenary Munich 2005

  15. Expected Simulation Results • Planning (mC, minimum cost approach) • Network Performances using RFWA with some physical impairment constraints • Blocking probability Pb clearly Pb = Pb(w) + Pb(Q), where Pb(w), is the blocking due to lack of available network resources Pb(Q), is the blocking due to physical transmission impairments • Distribution of lightpath lengths (unprotected and protected scenarios) • Comparison with traditional RFWA NOBEL Plenary Munich 2005

  16. Network Case-Study • DT network link distances are representative of a real national scale core network. • Connection requests arrive following a Poisson distribution with exponential holding times. • Connection requests are STM-64. • 40 system/fiber wavelengths • Equally spaced amplifiers along each link • Wavelength continuity constraint NOBEL Plenary Munich 2005

  17. Preliminary Results • Requests of static traffic matrix are previously sorted according to the rule: • priority is given to connection requests between node-pairs which are very far and have still many connections to be set up • Traffic 2005 matrix: 226 demands • RFWA: mH-LLR-WFF-FFF • 100% unprotected static traffic • No verification of connection feasibility • No Minimum Cost [D-26] but busy-Idle optimization (maximize system loads) • Graph inspection: • Average distance between two nodes (hop): 2.699 • Average distance between two nodes (km): 418.098 • Fiber links: 49 • Average LP length (# hop): 2.447 • Average LP length (km): 460.131 • Fiber links: 32 • Average LP length (# hop) 2.805 • Average LP length (km): 542.845 • Average utilization: 0.495 Traditional RFWA NOBEL Plenary Munich 2005

  18. Transparent vs Translucent NOBEL Plenary Munich 2005

  19. Translucent Network • To improve performances (reducing Pb) we can reduce: • Pb(w): using efficient WA (for example FF) • Pb(Q): introducing the regeneration functionality at some nodes instead of at all nodes. • How many regenerators shared in each node? • We suppose that a signal travels as long as possible before regenerating (its quality degrades below a threshold) • Regenerations could reduce Pb(w) when wavelength contention occurs (acting as wavelength converters) • In such a way we need less regeneration resources. NOBEL Plenary Munich 2005

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