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A Prediction Approach to End-to-End Traffic in Space Information Networks

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Abstract

Software Defined Space Information Networks (SDSIN) is increasingly applied to life and production, the reason is that it can cope with various complex environments and tasks in the future communication environment. Owing to the performance advantages of the Software Defined Networking (SDN), some advanced technologies based on SDN are more and more applied to satellite network. In order to better provide users with high-quality services, network providers must predict and analyze End-to-End (E2E) traffic. Hence, this poses the natural question of how to accurately predict the future trend of E2E traffic to load balance, network optimization, and network security. Different from the previous 2-dimension terrestrial network, we study a 3-dimension SDSIN in this paper. Firstly, we analyze the difficulties and challenges of traffic engineering in SDSIN. Subsequently, an improved Hidden Markov Model (HMM) to E2E traffic prediction method is proposed. Finally, simulation results show that our improved HMM can be well applied for E2E traffic prediction in SDSIN.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (No. 61571104), Sichuan Science and Technology Program (No. 2018JY0539), Key projects of the Sichuan Provincial Education Department (No. 18ZA0219), Fundamental Research Funds for the Central Universities (No. ZYGX2017KYQD170), and 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: merry_99@sina.com).

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Authors and Affiliations

  1. School of Astronautics and Aeronautic, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Sheng Qi & Dingde Jiang

  2. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Liuwei Huo

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  1. Sheng Qi
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  2. Dingde Jiang
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  3. Liuwei Huo
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Correspondence to Dingde Jiang.

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Qi, S., Jiang, D. & Huo, L. A Prediction Approach to End-to-End Traffic in Space Information Networks. Mobile Netw Appl 26, 726–735 (2021). https://doi.org/10.1007/s11036-019-01424-2

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