Community Detection-Empowered Hybrid Network Slicing for Aerial Communication Services

Network slicing is the most promising paradigm that enables the provision of services for aerial communication tasks, such as data traffic offloading, disaster relief, and data collection, with one shared physical network. However, current researchers primarily focus on the modeling of utilizing service function chaining (SFC) or task offloading, which have inherent limitations for areial communication tasks. While the former restricts the source-sink nodes to be fixed, the latter models network slicing as a whole. To further unleash the flexibility of network slicing, we introduce the hybrid network slicing (HNS) modeling in this paper. In our HNS, each aerial service is abstracted as multiple SFCs with dispersed source-sink nodes. These SFCs can be flexibly deployed in a unified or split manner based on the service workload and Quality of Service (QoS) requirements. Then, we formulate the HNS problem in a multi-tier network system as a mixed integer programming (MILP) problem and propose exact and community detection-based heuristic approaches to address the proposed problem. The simulation results demonstrate that the proposed heuristic approaches can effectively mitigate computational complexity than the exact method while providing near-optimal solutions for aerial communication tasks.