Aeronauticalad hocnetworking (AANET) of the air vehicles is envisioned to support future enhanced applications, such as free flight and in-flight Internet, and AANET serves as the middle layer of the air–space–ground integrated network, bridging the space and the ground components. However, intermittent connectivity is the greatest challenge to an AANET. To deal with the intermittence, the air vehicle acts as a relay in an AANET using the buffer onboard to temporally cache the data when an interruption occurs, known as opportunistic transmission. For the highly dynamic topology of an AANET, we use a sampled dynamic graph to capture significant variations while ignoring trivial changes for avoiding extra complexity. And thus we formulate a coalitional game incorporating with the dynamic graph for the AANET to obtain the optimal transmission schedule in terms of the effective throughput with limited transmission delay. The corresponding coalitional dynamic graph game algorithm will then generate an approximately optimal AANET formation, which converges to Nash equilibrium within finite iterations. The simulations conducted with the real flight data show that 700 Mb of buffer size onboard and 1400 Mb of buffer in the Internet gateway station (IGS) are the optimal settings for the opportunistic transmission, and the coalitional dynamic graph game algorithm outperforms the geographic location-based greedy perimeter stateless routing algorithm in terms of the total received data amounts.

With the growing interest in providing internet access and cellular connectivity in the commercial aircraft, the compatibility between Air-to-Air (A2A) communications and current Air-to-Ground (A2G) macro-cellular communications is necessary to form an Aeronautical Ad hoc Network (AANet). Due to the typical features of airborne communications, such as high mobility, long transmission range and three-dimensional macro-cells, AANet is affected by intermittent links, which results in variant delayed data transmissions. To this end, we exploit a dynamic graph approach to model such an AANet with rapidly changing topology under a realistic airborne scenario. Targeting the problem of intermittent transmissions, by employing A2A, an AANet can bear three transmission modes: direct transmission, connected relay transmission and opportunistic transmission. To investigate the potential gain of A2A transmissions in terms of the end-to-end data flow transmission delay and the data traffic amount, we formulate an integer non-linear programming problem that minimizes the average end-to-end delay from Internet Gateways (IGWs) on shore to the aircraft receivers through multiple options of the transmission modes. Through solving this minimization problem based on the realistic dynamic graph model, the tradeoffs between the end-to-end transmission delay and other key network factors related to AANet formation and resource allocation can be obtained without much compromise on the transmission delay. The results show that the average end-to-end delay of the AANet is comparable to the direct transmission delay when having a tradeoff with the data traffic amount, buffer size and the spectrum sharing.