An Adaboost Based Link Planning Scheme in Space-Air-Ground Integrated Networks
The Space-air-ground integrated network (SAGIN) has been a valuable architecture for communication support due to its characteristics of wide coverage and low transmission delay. Both low earth orbit (LEO) satellites and UAVs can serve as relay nodes to provide reliable communication services for ground devices. However, the design of data transmission links (DTL) in SAGIN is not easy, considering different accessing layers and resource usage of network segments. Moreover, network topology, available resources, and relative motion need to be analyzed comprehensively for the deployment of DTLs. To address these problems in a heterogeneous SAGIN network, the software defined networking (SDN) architecture is utilized to realize global knowledge acquisition. Then a traffic prediction method based on autoregressive moving average (ARMA) model is utilized to forecast the resource usage of SAGIN segments. After the analysis of link performance, the Adaboost algorithm is used to classify network nodes according to their data transmission capacity for DTL deployment. Simulation results show that the proposed Adaboost-based link planning scheme is feasible and effective.
KeywordsSpace-air-ground integrated network Software defined networking Traffic prediction Adaboost model Data transmission link
This work was supported in part by the National Natural Science Foundation of China (No. 61571104), the Sichuan Science and Technology Program (No. 2018JY0539), the Key projects of the Sichuan Provincial Education Department (No.18ZA0219), the Fundamental Research Funds for the Central Universities (No. ZYGX2017KYQD170), and the Innovation Funding (No. 2018510007000134). The authors wish to thank the reviewers for their helpful comments. Dr. Dingde Jiang is corresponding author of this paper (email: email@example.com).
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