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Multi-layer Traffic Engineering for IP-over-Optical networks

Multi-layer Traffic Engineering for IP-over-Optical networks

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Multi-layer Traffic Engineering for IP-over-Optical networks

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  1. Multi-layer Traffic Engineering for IP-over-Optical networks IMEC

  2. Introduction (1) Reconfiguration based on IP traffic/QoS measurements Information exchange (cost metric) • Topology • Optical metric IP-over-Optical Networks B IP router IP link A D E C IP network ASON/ION B optical switch optical fiber (WDM) lightpath A D E C Dept. of Information Technology - Ghent University

  3. Introduction (2) 70 60 50 40 Cost 30 20 10 0 0 20 40 60 80 100 Load(%) • General overview of MTE scheme used assign costs 3 4 route 2 5 full mesh signaling 1 · route traffic IP traffic or · set up necessarylightpaths 1’ failure ASON Dept. of Information Technology - Ghent University

  4. Introduction (3) moderate loads LC LMR LC:MC MC • MTE IP link load depending cost function 20 70 # links 60 cost 15 50 LLT 40 10 Cost # links 30 HLT 20 5 10 0 0 0 20 40 60 80 100 Load (%) Dept. of Information Technology - Ghent University

  5. Optical metrics (1) IP traffic flow grooming taking intoaccountthe opticallayer 9 l 6 l 2 1 3 2 2 1 1 1 1 1 Dept. of Information Technology - Ghent University

  6. Optical metrics – example (2) Static metric No metric • Many long lightpaths • No correspondence tophysical topology • Follows physical topology better • Shorter lightpaths • Topology seems more ‘open’ • Effect of cost metric in MTE strategy on logical topology Dept. of Information Technology - Ghent University

  7. Optical metrics in MTE (3) • Multi-layer Traffic Engineering strategy comes with an IP-layer cost function to handle: • IP/MPLS routing • Logical topology reconfiguration • Introduction of optical metric allows to take optical resources into account in setting up the logical topology • Optical metric used: C + S.#hops • calculated for each IP router pair (metric is used in IP/MPLS MTE) • #hops = optical hops for a lightpath between two IP routers. • Setting C and S allows to set the degree of optical resource optimization. • E.g. higher S = higher optical resource optimization  higher IP grooming Dept. of Information Technology - Ghent University

  8. Optical metrics in MTE (4) 70 60 50 40 Cost 30 20 10 0 0 20 40 60 80 100 Load (%) • Optical metrics in the MTE IP cost function • Multiply existing IP costfunction with optical metric • IP cost : grooming, topology • Optical : optimize optical layer • Note: optical cost as seen from • the IP layer, so each node pair • has an optical cost IP Optical ??? Dept. of Information Technology - Ghent University

  9. Optical metrics – costs (5) Optical metrics 12 C = 1 (flat) 2 C = 1, S = 0 (flat) C = 0.75 C = 0.75, S = 0.25 10 C = 0 C = 0, S = 1 C = –1, S = 2 C = –1 8 Same cost for single hop lightpath 1 optical cost optical cost 6 Cost penalty per lightpath 4 No fixed cost 0 0 0,5 1 1,5 2 Cost ‘bonus’ per lightpath 0 -1 optical hops 1 2 3 4 5 6 optical hops Cost = C + S.n Dept. of Information Technology - Ghent University

  10. Optical metrics – performance (6) maximum used wavelenghts on one fiber 18 flat (no metric) 16 C = 0.75 14 12 1 10 # lambda 8 6 2 • Better choice of lightpaths • Better (more) grooming 4 2 0 0% 10% 20% 30% 40% 50% Max IP load (<-> node pair) Maximum resource usage on single fiber C = 0 C = –1 Dept. of Information Technology - Ghent University

  11. Optical metrics – performance (7) slope 1 vs. no optical metric (relative) Relative optical savings (C = 0 vs. no metric) 60% total #Lambda max #Lambda 50% 40% 30% relative savings 20% 10% 0% 10% 15% 20% 25% 30% 35% 40% 45% 50% Max IP load (<-> node pair) Dept. of Information Technology - Ghent University

  12. Optical metrics – conclusion (8) optical metricsweet spot operatoradjustable Optical layer vs. IP layer Optical load vs. IP load 120 60 58 # Lambda 100 average IP load 56 80 54 load (%) #Lambda 60 52 50 40 48 20 46 0 44 1 0.75 0 –1 C (fixed penalty per lightpath) Dept. of Information Technology - Ghent University

  13. Optical metrics – conclusion (9) • Multi-layer Traffic Engineering strategy based on cost-function depending on IP link load. • Introduction of optical metric into the cost function to optimize the optical layer. • Even minimal information exchange (# hops) between optical and IP layer yields large improvement in optical layer utilization. • Simple optical cost metric with adjustable slope / fixed cost per lightpath allows a compromise between IP performance and optical layer cost. Dept. of Information Technology - Ghent University

  14. Prediction Based Routing (1) • Restraints such as wavelength continuity necessitate a proper routing strategy in the optical layer. • Not routing lightpaths, but typically also wavelength (and fiber) assignment: RWA. • Prediction Based Routing can select routes, wavelengths, fibers based on prediction (cf. branch prediction). • Find ways to combine the MTE strategy (mostly IP/MPLS layer) with the PBR strategy (optical layer). Dept. of Information Technology - Ghent University

  15. Prediction Based Routing (2) dest PBR decides on route, fiber, wavelength: • keeps history for each route-wavelength-fiber • selects from route x wavelength x fiber space using prediction fiber? route? wavelength? source Dept. of Information Technology - Ghent University

  16. Prediction Based Routing (3) • History for each Route/Fiber/Wavelength triplet (a ‘path’): • History becomes an index into a prediction table (separate table for each path). • Value in table[history-index] determines whether this path can be selected during lightpath set up • Important: construction of prediction table values is done completely at the source node, based on lambda utilization and blocking events: no information needs to be flooded to other nodes, lightpath setup uses only this local information! shift and update periodically … 0 1 0 past recent State means e.g. ‘path is utilized’ Dept. of Information Technology - Ghent University

  17. Prediction Based Routing (4) • The PBR strategy was developed by the Universitat Politècnica de Catalunya. In a joint effort with IMEC, the PBR was implemented using the MTE software tool. • Goals: • For MTE generated traffic loads, compare the performance of PBR against e.g. a first-fit strategy in the optical layer. note: MTE used fixed optical route/first free wavelength in the optical layer up till now. • Incorporate optical metrics that depend on optical load – we intend to extract an optical metric for each node pair from the PBR data structures. note: a lot of flooding in the optical layer lead to high overheads in optical load metric calculation. Dept. of Information Technology - Ghent University