Location-Recommendation-Aware Virtual Network Embedding in Energy-Efficient Optical-Wireless Hybrid Networks Supporting 5G Models

Abstract

Given the possibility of ubiquitous 5G wireless access, location data bridge the gap between the physical world and digital online social networking services and also reflect user preferences and even interdependence among users. Owing to this interdependence, the advertiser can push corresponding products to users according to location recommendations, i.e., advertisement targeting. To achieve this mobile cloud computing service, after moving the computing capacity away from end devices to data centres (DCs), the converged infrastructure integrating optical metro and ubiquitous wireless access technologies is proposed in accordance with the 5G model. To minimize energy consumption, we propose a novel design framework of location-recommendation-aware virtual network embedding. This design framework determines the interdependency among user groups so that we can embed the virtual networks owned by user groups with a high interdependence into the same DC of the substrate optical-wireless hybrid infrastructure. Thus, the adviser can locally push the corresponding products to user groups at a single DC instead of consuming a large amount of energy to build inter-DC paths. The simulation results show that our design framework has greater energy efficiency and more profitable advertisement targeting compared with the benchmark, and the result of our heuristic is very close to the upper bound.

Keywords

• 5G-based location recommendations
• energy efficiency
• optical-wireless integration
• virtual network embedding
• problem transformation
• bound analysis