{"id":{"repo_id":"nus","oai_identifier":"oai:scholarbank.nus.edu.sg:10635/20409"},"canonical_url":"https://search.dev.ndltd.org/etd/nus/oai:scholarbank.nus.edu.sg:10635/20409","repository":{"repo_id":"nus","name":"National University of Singapore","base_url":"https://scholarbank.nus.edu.sg/oai/request"},"display":{"title":"Backup Radio Placement for Optical Fault Tolerance in Hybrid Wireless-Optical Broadband Access Networks","abstract":"Hybrid Wireless-Optical Broadband Access Network (WOBAN) is a new and promising architecture for next generation broadband access technology. This thesis introduces a new approach to tackle fault-tolerance provisioning in WOBAN. Back-up radios are deployed at selected existing nodes in the Wireless Mesh Network front end of WOBAN to create a dedicated wireless back-up channel to protect the network from fiber failures. Each ONU is wirelessly connected to another ONU in a multi-hop way, hence fully protected. We prove that to provide full protection while minimizing backup radio deployment cost is NP-complete. We develop an integer linear programming to obtain the optimal solution and two heuristics to reduce computation complexity. To evaluate our heuristic algorithms, we run simulation on real and random networks. The simulation results show that our approach gives a more feasible and cost-effective way to provide optical fault-tolerance compared to traditional PON and other existing solutions.","abstract_html":"Hybrid Wireless-Optical Broadband Access Network (WOBAN) is a new and promising architecture for next generation broadband access technology. This thesis introduces a new approach to tackle fault-tolerance provisioning in WOBAN. Back-up radios are deployed at selected existing nodes in the Wireless Mesh Network front end of WOBAN to create a dedicated wireless back-up channel to protect the network from fiber failures. Each ONU is wirelessly connected to another ONU in a multi-hop way, hence fully protected. We prove that to provide full protection while minimizing backup radio deployment cost is NP-complete. We develop an integer linear programming to obtain the optimal solution and two heuristics to reduce computation complexity. To evaluate our heuristic algorithms, we run simulation on real and random networks. 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