Joint Optimization of AoI, SINR, Completeness, and Energy in UAV-Aided SDCNs: Coalition Formation Game and Cooperative Order

As one of the most important representatives for the edge intelligence, Unmanned Aerial Vehicle (UAV) can be used to provide the intelligent edge service, such as performing data collection, computation and transmission tasks in the air-to-ground networks. In the considered Sensed Data Collection Networks (SDCNs), the UAV is in charge of collecting and computing the sensed data from mobile ground nodes, and multiple performance metrics need to be jointly optimized, including the collected data’s Age of Information (AoI) and the Signal to Interference plus Noise Ratio (SINR) at the UAV from mobile sensor nodes, the data collection areas’ completeness, and the mobile sensor nodes’ energy consumption. Due to the absence of such a joint optimization framework, this paper formulates the mobile sensing nodes deployment problem in the UAV-aided SDCNs. Afterwards, the formulated problem is transformed into a utility maximization problem from the perspective of Coalition Formation Game (CFG), where the orders, actions, rule, and stability in the coalitions are analyzed and proved. Then, two algorithms are put forward to reach the NE (Nash Equilibrium) of the CFG by determining the mobile sensor nodes’ coalitions and positions. Finally, extensive simulations are conducted with different parameters settings to evaluate the correctness and effectiveness of the proposed algorithms. Results have shown that the mobile sensor nodes, which adopt the proposed cooperative order to formulate the coalitions, could reach lower AoI, larger SINR, higher data completeness, and less energy consumption than the typical Pareto order.