1. BUTE (BME) S1 D1 1 9 S2 D2 2 5 10 4 S3 D3 MIRO 8 3 6 7 11 • Search for critical links: •  introducing criticality classes • 2. Assign link weight: • cost assignment strategies: • contributions for each criticality class • more critical links higher contribution • linear, exponential, competitive paths • 3. Select shortest weighted path Simulation Destination • IF the max Nr. of criticality classes increases: • Nr. of blocked calls decreases • Average route length decreases 3rd criticality class 1st criticality class (MIRA class) C =  Source C =  2nd criticality class Conclusion • MIRO is a generalization of MIRA • The increase of calculation is not significant Class-based Minimum Interference Routing for Traffic Engineering for Optical Networks János Tapolcai, Péter Fodor, Gábor Rétvári, Markosz Maliosz, Tibor Cinkler {tapolcai, fodorp, retvari, maliosz, cinkler}@tmit.bme.hu Minimum Interference Routing & MIRA • Preventive path selection for TE • Existing algorithms give wrong solution Main idea: • sessions have critical links • sending traffic to a critical link interference • NP-hard problemMIRA • MIRA Steps: • Search for critical links: • 2. Assign link weight: • 3. Select shortest weighted path Blocking rate load of channels Multi-Layer TE Arnold Farkas, János Szigeti, Tibor Cinkler {farkas, szigeti, cinkler}@tmit.bme.hu Capacity of WL channels Capacity of WL channels Dynamic behaviour Blocking rate vs. Simulation time