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Multi-Layer versus Single-Layer MGOXC for WBS Xiaojun Cao In collaboration with Vishal Anand and Chunming Qiao 1 Outline Concept of Waveband Switching (WBS) Multi-Layer MG-OXC and Single-Layer MG-OXC architecture Offline WBS algorithms Reconfigurable MG-OXC for Online case Online WBS algorithms Conclusions 2 The Optical Cross-connect (OXC) – Size, management complexity, cost … optical switch fabric Called Ordinary-OXC here DeMux/Mux: split/combine the wavelengths in a fiber Switch: connects the wavelengths to one another using ports requiring one port for each wavelength As the number of wavelength or fiber increase, it also brings up add traffic drop traffic 3 Waveband Switching (WBS) Up to 60%~80% of the total traffic in the backbone is bypass (i.e. transit) traffic Waveband: a group of several wavelengths All the wavelengths in a band will be switched as a single entity (port) Major merits of WBS - reduce port count - reduce complexity - simplify network management - better scalability Need new cross-connects architecture: MultiGranularity optical cross-connect (MG-OXC) 4 MG-OXC Architecture A new switching hierarchy with multiple granularities – Fiber, band, wavelength Three layer, three switching fabric Advantage: 1 2 .. 1 2 .. FXC n n BTF Mux .. .. .. .. BXC .. .. FTB Demux FXC Layer BXC Layer – flexible BTW Demux Fadd B d r o p .. .. .. .. W add WXC .. ..WTB Mux W d r o p B add WXC Layer Fdrop Three-Layer MG-OXC 5 Single-Layer MG-OXC One common switching fabric, includes three logical divisions Only designated fibers/bands can be demuxed/muxed Advantage: – Simple – better signal quality 1 2 .. ... FXC .. 1 2 ... BXC n ... F a d d Ba d d Wa d d WXC n ... Wdrop B d r o p Fd r o p 6 Three-Layer versus Single-Layer 1 2 .. 1 2 .. FXC FXC n Layer n BTF Mux BTW Demux F add B d r o p .. .. .. .. .. BXC .. .. .. W add .. WXC .. Wdrop 1 2 .. .. FXC .. .. FTB Demux BXC Layer Mux B add WXC Layer 2 .. BXC n .. ..WTB 1 F a d d Ba d d Wa d d WXC n .. Wdrop B d r o p Fd r o p Fdrop In WBS networks with Single-Layer MG-OXC, an appropriate WBS algorithm needs to make sure that dropped lightpath will be assigned wavelengths belong to a designated fiber/band. In the following, Consider Fixed band size as well as fixed set of wavelengths per band 7 Offline WBS Given static traffic, network topology, the number of wavelength etc, how to satisfy the demands while minizing the size of MG-OXCs. Optimal ILP model, BPHT appeared in InfoCom’03 and OptiComm’02 – Too time-consuming Near-Optimal ILP model (Off-ILP) – Limit the number of possible routing – To reduce the computation complexity 8 Off-ILP model Primary Notation: – In,On,An,Dn: set of incoming/outgoing fibers – B,W, Lb: number of band/wavelength, set of λ in band b. – P, T[p], K, Rk,p: traffic matrix and K-shortest path set Variables: – V, S, W, B, F: lightpaths going through which switching fabric – FTB/BTF, BTW/WTB: describe which demux/mux to use Objective: minimize the total MG-OXC ports in the network min imize[∑WXCn + ∑ BXCn + ∑ FXCn ] n n n 9 Constraints Traffic flow constraints – Satisfy all the traffic demands Waveband switching – Appropriately switch the lightpaths through the switch fabrics at a node Mux/Demux – Appropriately Mux/Demux the lightpaths at a node Detailed formulations refer to Papers 10 Performance Metrics Total port number ratio T: Total ( FXCn + BXCn + WXCn ) u sin g MG − OXC Total (OXCn ) u sin g ordinary − OXC Max port number ratio M: Max ( FXCn + BXCn + WXCn )u sin g MG − OXC Max (OXCn ) u sin g ordinary − OXC Used wavelength-hop ratio WH: λ − hop used by WBS a lg orithm λ − hop used by optimal RWA without WBS 11 Numerical Results 14-node Network with random traffic, K=3 1.2 1.2 Three-Layer,BPHT Three-Layer,Off-ILP Single-Layer,BPHT Single-Layer,Off-ILP 1.1 1.0 1.0 0.9 0.8 Ratio: M Ratio: T 0.9 Three-Layer,BPHT Three-Layer,Off-ILP Single-Layer,BPHT Single-Layer,Off-ILP 1.1 0.7 0.6 0.8 0.7 0.6 0.5 0.4 0.5 0.3 0.4 0 5 10 15 Number of wavlength per band 20 0 5 10 Number of wavlength per band 12 Summary for Offline case Near-optimal ILP model perform better Single-Layer MG-OXC requires up to 20% fewer ports than Multi-Layer MG-OXC With appropriate wavelength granuularity (W=4), MG-OXC can achieve more than 50% ports reduction when compared to ordinary OXCs – The maximum size of a node over all the nodes also has similar reduction Tradeoff between wavelength-hops and port count 13 Online WBS Given MG-OXC and network topology, how to process lightpath request without knowledge of any future requests. – Incremental, non-rearrangeable Unlike offline case, which can have as many port as needed to guarantee all demands In online case, MG-OXCs may have a predetermined limited port count – How to minimize request blocking probability – How to efficiently use the network resources (e.g. minimize active ports) 14 Reconfigurable MG-OXC X: the number of incoming fibers α(≤1): the ratio of fibers can be demuxed to bands Wa d d .. – Any α·X fibers can be demuxed to bands Y: the number of BXC ports from FTB demux β (≤1): the ratio of bands can be demuxed to λs – Any β ·Y bands can be demuxed to λs Wd r o p WXC ... ... .. BXC .. ... WXC Layer WTB Y BTF .. BXC Layer ... FTB FXC .. .. .. BTW βY .. ... FXC Layer αX X .. Total number of ports: MG − OXCn = (1 + α ) ⋅ X + (1 + β ) ⋅ Y + β ⋅ Y ⋅ W + Wadd / drop 15 T for Reconfigurable MG-OXC T3: ratio of the port count in a Three-Layer MG-OXC to the port count in an ordinary-OXC (1 + β ) ⋅ α MG − OXC n ≈ β ⋅α + T3 = OXC W n Similarly, T1: the ratio for Single-Layer MG-OXC (1 − β ) ⋅ α T1 ≈ β ⋅ α + W For single-fiber systems, it’s necessary to set α=1, otherwise the blocking is too high Wa d d n βY .. .. .. αX . . 1 WXC .. .. 2 Wd r o p .. .. .. .. .. BXC FXC n .. .. 2 .. 1 16 Online ILP model (On-ILP) Additional constraints for Three-Layer MG-OXC – δ:node degree n ,b WTB ∑ o ≤δ ⋅β ∀n o ,b n ,b BTW ∑ i ≤δ ⋅β ∀n i ,b Additional constraints for Single-Layer MG-OXC – The choice of the designated bands is critical: the traffic carried by a designated band at one node may bypass at another node. – EWTB/EBTW: the setting of designated bands: randomly select β ·Y bands as designated bands. WTBon ,b ≤ EWTBon ,b ∀n, o, b BTWi n ,b ≤ EBTWi n ,b ∀n, i, b Since α=1, no constraint on the number of FTB/BTF ports 17 Online heuristics Random-Fit – Combine the K-shortest path routing with random wavelength assignment First-Fit – Use K-shortest path routing and assign the wavelength sequentially Maximum Overlap Ratio (MOR) – Model a WBS network as a band-graph having B layers – Find K-shortest path in each layer corresponding to band b – Intuitively, to minimize the blocking coming with limitation of ports and wavelength resource • Route along the path that has max links in common with existing lightpaths • Avoid the wastage of wavelength resources – Set the weight of each (k,b) pair as Q kb = ∑ where L is the overlap H length, H is the number of hops, choose the maximum weight to route the new demand L 18 MOR example 1 R1 0 1 0 8 2 9 3 10 11 7 0 R3 4 5 6 8 2 9 λ0 3 10 b0 11 4 5 6 1 S2 S3 8 9 10 λ2 11 4 5 6 1 2 3 7 b1 S7 R2 (a) New demand: 0→7 Compute weight 3 1 b0 b2 Q k2 = Q k1 = 4 4 0 8 4 Q kb31 3 = 5 New lightpath: 0→4→5→6→7 (λ5) 9 10 5 existing lightpaths λ4 b2 11 7 6 λ5 new demand (b) 19 Results of Three-Layer MG-OXC For medium load, MOR is better than First-Fit, On-ILP, much better than Random-Fit. When β≈0.45 (i.e. T3≈0.60), MOR achieves the lowest blocking probability – One may build 45% (but not more) BTW ports – 40% savings on port count 0.3 0.4 0.5 0.6 β 0.7 0.8 0.9 1.0 0.14 0.12 Blocking Probability – MOR takes waveband grouping into consideration – On-ILP minimize additional ports, random λs assignment to the initial traffic set hurts its performance 0.10 Random-Fit On-ILP First-Fit MOR 0.08 0.06 0.04 0.02 0.00 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 Ratio: T3 (Three-Layer MG-OXC - Med load) 20 1.3 Results of Three-Layer MG-OXC cont. β For high load, First-Fit is the best when T3>0.75 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.20 0.18 0.16 Blocking Probability – Assign λs sequentially – Prefer to use shortest path 0.3 Random-Fit On-ILP MOR First-Fit 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Ratio: T3 (Three-Layer MG-OXC - High load) 1.5 1.4 Wavelength Hops MOR consumes more wavelength recourses, experience more blocking due to the lack of wavelength resources 1.3 1.2 Random-Fit On-ILP MOR First-Fit 1.1 1.0 0.3 0.4 0.5 0.6 0.7 0.8 β (Three-Layer MG-OXC) 0.9 1.0 1.1 21 Results of Single-Layer MG-OXC – At low loads, noneligible blocking – At high loads, blocking probability close to 1 0.3 0.4 0.5 0.6 β 0.7 0.8 0.9 1.0 0.6 0.5 Blocking Probability The designated bands are allocated randomly at different nodes, greatly reduces the chance of wavebanding and hence increase the blocking Random-Fit On-ILP First-Fit MOR 0.4 0.3 0.2 0.1 0.0 0.4 0.5 0.6 0.7 0.8 0.9 Ratio: T1 (Single-Layer MG-OXC - Low load) 22 1.0 Three-Layer versus Single-Layer Under medium load, the blocking probability using Three-Layer MG-OXC is much lower – Three-Layer MG-OXC is more suitable for online traffic β 0.4 0.5 0.6 0.7 0.9 0.3 1.0 0.4 0.5 0.6 β 0.7 0.8 0.9 1.0 0.14 0.7 Random-Fit On-ILP MOR First-Fit 0.6 Blocking Probability 0.8 0.5 0.12 Blocking Probability 0.8 0.3 0.4 0.3 0.2 0.10 Random-Fit On-ILP First-Fit MOR 0.08 0.06 0.04 0.02 0.1 0.00 0.0 0.4 0.5 0.6 0.7 0.8 0.9 Ratio: T1 (Single-Layer MG-OXC - Med load) 1.0 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 Ratio: T3 (Three-Layer MG-OXC - Med load) 23 Conclusion Proposed feasible ILP model for offline case and efficient heuristics for online case Compared Three-Layer MG-OXC and Single-Layer MG-OXC for both online case and offline case – For the offline case, Single-Layer MG-OXC is better in terms of reducing port count when building network from scratch – For the online case, Three-Layer MG-OXC is more flexible and results in lower blocking probability – The ratio (β) and waveband granularity have a great effect on the performance of WBS networks 24