Optical-wireless hybrid virtual network embedding based on location recommendations
Xiaoxue Gong, Qihan Zhang, Lei Guo · 2016
Location data reflects user preferences and even interdependency among users. Owing to this interdependency, the advertiser can push the corresponding products to users through location recommendations, i.e., advertisement targeting. To maximize the profitability of advertisement targeting, a novel design framework of optical-wireless hybrid virtual network embedding is proposed by us. This framework determines the interdependency (similar recommended Point of Interest (POI) trajectories) among user groups so that we can embed virtual networks of user groups with a high interdependency into the same part of the substrate optical-wireless hybrid infrastructure. The simulation results show that our framework has the higher profitability of advertisement targeting compared to the benchmark and has an effective bound analysis.