Abstract
Satellites have been integrated into the terrestrial mobile network to meet the 5G requirements of providing connectivity regardless of time and location. The user terminal needs to switch between the satellite and base station, known as vertical handover, to achieve continuous and high-quality communication. The credit method avoids frequent network state measurement. However, it requires the status of all networks for credit calculation, which may lead to incomplete and delayed data acquisition. Therefore, a handover decision method based on time-space attribute reputation is proposed in this study. The proposed method takes the user’s location and time factors into account. Considering the changes of the network topology caused by satellite and user mobility, the target network is selected according to the overall reputation of candidates and the user’s current location. The early untrusted network information is eliminated in time to obtain an effective and accurate result. Moreover, since uplink vertical handover has an undesirably high propagation delay during protocol implementation, this study optimizes the existing execution process and proposes an early access strategy to reduce the handover delay. Both designs have been tested and are proved to be effective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhao, H., Chen, M., et al.: A novel pre-cache schema for high performance Android system. Futur. Gener. Comput. Syst. 56, 766–772 (2016)
Qiu, L., Gai, K., Qiu, M.: Optimal big data sharing approach for tele-health in cloud computing. In: IEEE SmartCloud, pp. 184–189 (2016)
Qiu, M., Khisamutdinov, E., et al.: RNA nanotechnology for computer design and in vivo computation. Philos. Trans. R. Soc. A 371, 20120310 (2013)
Guo, Y., Zhuge, Q., Hu, J., et al.: Optimal data allocation for scratch-pad memory on embedded multi-core systems. In: IEEE ICPP Conference, pp. 464–471 (2011)
Zhang, L., Qiu, M., Tseng, W., Sha, E.: Variable partitioning and scheduling for MPSoC with virtually shared scratch pad memory. J. Sig. Process. Syst. 58(2), 247–265 (2010). https://doi.org/10.1007/s11265-009-0362-3
Qiu, M., Liu, J., et al.: A novel energy-aware fault tolerance mechanism for wireless sensor networks. In: IEEE/ACM Conference on Green Computing and Communications (2011)
Qiu, M., Cao, D., Su, H., Gai, K.: Data transfer minimization for financial derivative pricing using Monte Carlo simulation with GPU in 5G. Int’l J. Comm. Sys. 29(16), 2364–2374 (2016)
Lu, Z., Wang, N., Wu, J., Qiu, M.: IoTDeM: An IoT Big Data-oriented MapReduce performance prediction extended model in multiple edge clouds. J. Parallel Distrib. Comput. 118, 316–327 (2018)
Qiu, H., Qiu, M., Lu, Z.: Selective encryption on ECG data in body sensor network based on supervised machine learning. Inf. Fusion 55, 59–67 (2020)
Qiu, M., Chen, Z., Liu, M.: Low-power low-latency data allocation for hybrid scratch-pad memory. IEEE Embed. Syst. Lett. 6(4), 69–72 (2014)
Gao, Y., Iqbal, S., et al.: Performance and power analysis of high-density multi-GPGPU architectures: a preliminary case study. In: IEEE 17th HPCC (2015)
Qiu, M., Xue, C., Shao, Z., Sha, E.: Energy minimization with soft real-time and DVS for uniprocessor and multiprocessor embedded systems. In: IEEE DATE Conference, pp. 1–6 (2007)
Gai, K., Qiu, M., Elnagdy, S.: A novel secure big data cyber incident analytics framework for cloud-based cybersecurity insurance. In: IEEE BigDataSecurity (2016)
Thakur, K., Qiu, M., Gai, K., Ali, M.: An investigation on cyber security threats and security models. In: IEEE CSCloud (2015)
Gai, K., Qiu, M., Sun, X., Zhao, H.: Security and privacy issues: a survey on FinTech. In: Qiu, M. (ed.) SmartCom 2016. LNCS, vol. 10135, pp. 236–247. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-52015-5_24
Giambene, G., Kota, S., Pillai, P.: Satellite-5G integration: a network perspective. IEEE Network 32(5), 25–31 (2018)
Zhang, Z., Wu, J., et al.: Jamming ACK attack to wireless networks and a mitigation approach. In: IEEE GLOBECOM Conference, pp. 1–5 (2008)
Qiu, H., Qiu, M., Memmi, G., Ming, Z., Liu, M.: A dynamic scalable blockchain based communication architecture for IoT. In: SmartBlock, pp. 159–166 (2018)
Lu, R., Jin, X., Zhang, S., Qiu, M., Wu, X.: A study on big knowledge and its engineering issues. IEEE Trans. Knowl. Data Eng. 31(9), 1630–1644 (2018)
Liu, M., Zhang, S., et al.: H infinite state estimation for discrete-time chaotic systems based on a unified model. IEEE Trans. Syst. Man, Cybern. (B) (2012)
Desogus, C., Anedda, M., Murroni, M., et al.: A traffic type-based differentiated reputation algorithm for radio resource allocation during multi-service content delivery in 5G heterogeneous scenarios. IEEE Access 7, 27720–27735 (2019)
3GPP. Study on New Radio (NR) to support non-terrestrial networks[S]. 2019
Ahuja, K., Singh, B., Khanna, R.: Network selection algorithm based on link quality parameters for heterogeneous wireless networks. Optik 125(14), 3657–3662 (2014)
Rahman, M.A., Salih, Q.M., Asyhari, A.T., et al.: Traveling distance estimation to mitigate unnecessary handoff in mobile wireless networks. Ann. Telecommun. 74(11), 717–726 (2019)
Lahby, M., Attioui, A., Sekkaki, A.: An improved policy for network selection decision based on enhanced-topsis and utility function. In: 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 2175–2180. IEEE (2017)
Zhu, Y., Li, J., Huang, Q., et al.: Game theoretic approach for network access control in heterogeneous networks. IEEE Trans. Veh. Technol. 67(10), 9856–9866 (2018)
Bi, T., Zou, L., Chen, S., et al.: RA3D: reputation-based adaptive 3D video delivery in heterogeneous wireless networks. In: 2019 International Conference on High Performance Computing and Simulation (HPCS), pp. 48–54. IEEE (2019)
Radouche, S., Leghris, C., Adib, A.: MADM methods based on utility function and reputation for access network selection in a multi-access mobile network environment. In: 2017 International Conference on Wireless Networks and Mobile Communications (WINCOM), pp. 1–6. IEEE (2017)
Goyal, R.K., Kaushal, S.: Network selection using AHP for fast moving vehicles in heterogeneous networks. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds.) Advanced Computing and Systems for Security. AISC, vol. 395, pp. 235–243. Springer, New Delhi (2016). https://doi.org/10.1007/978-81-322-2650-5_15
Goutam, S., Unnikrishnan, S., Karandikar, A.: Algorithm for handover decision based on TOPSIS. In: 2020 International Conference on UK-China Emerging Technologies (UCET), pp. 1–4. IEEE (2020)
Jiang, D., Huo, L., Lv, Z., et al.: A joint multi-criteria utility-based network selection approach for vehicle-to-infrastructure networking. IEEE Trans. Intell. Transp. Syst. 19(10), 3305–3319 (2018)
Yang, Z., Li, J., Huang, L., et al.: Developing dynamic intuitionistic normal fuzzy aggregation operators for multi-attribute decision-making with time sequence preference. Ex-pert Syst. Appl. 82, 344–356 (2017)
Li, K., Li, Y., Qiu, Z., et al.: Handover procedure design and performance optimization strategy in leo-hap system. In: 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), pp. 1–7. IEEE (2019)
Cakaj, S.: The parameters comparison of the “Starlink” LEO satellites constellation for different orbital shells. Front. Commun. Networks (2021)
Acknowledgement
This work was funded by the 54th Research Institute of China Electronics Technology Group Corporation in “The Manned Space Advanced Research Project under Grant [060501]” and “The Civil Aerospace Technology Advance Research Project under Grant [B0105].”
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, Y. et al. (2022). Vertical Handover of Satellite-Ground Fusion Network Based on Time and Location Under Early Access Strategy. In: Qiu, M., Gai, K., Qiu, H. (eds) Smart Computing and Communication. SmartCom 2021. Lecture Notes in Computer Science, vol 13202. Springer, Cham. https://doi.org/10.1007/978-3-030-97774-0_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-97774-0_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-97773-3
Online ISBN: 978-3-030-97774-0
eBook Packages: Computer ScienceComputer Science (R0)