Abstract
A fractional calculus fluid model can be used to better explain the bursty data service traffic, which is long-range dependence and has a fractal like the feature of network data flow. The heavy-tailed delay distributions, the hyperbolic decay of the packet delay auto-covariance function and fractional differential equations are shown to be formally related. Effective capacity is a useful model to describe wireless networks with QoS constraints. This paper builds a fluid model to describe the traffic of multi-hop wireless networks under QoS constraints. The proposed method could analyze the relationship between latency and a complicated traffic model, which is more similar to the real scenario.
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Huo, L., Jiang, D., Lv, Z., et al. (2019). An intelligent optimization-based traffic information acquirement approach to software-defined networking. Computational Intelligence, 36(1), 1–21.
Wang, F., Jiang, D., & Qi, S. (2019). An adaptive routing algorithm for integrated information networks. China Communications, 7(1), 196–207.
Zhang, K., Chen, L., An, Y., et al. (2019). A QoE test system for vehicular voice cloud services. Mobile Networks and Applications. https://doi.org/10.1007/s11036-019-01415-3
Chen, L., Jiang, D., Bao, R., Xiong, J., Liu, F., & Bei, L. (2017). MIMO Scheduling effectiveness analysis for bursty data service from view of QoE. Chinese Journal of Electronics, 26(5), 1079–1085.
Jiang, D., Wang, Y., Lv, Z., et al. (2020). Big data analysis-based network behavior insight of cellular networks for industry 4.0 applications. IEEE Transactions on Industrial Informatics, 16(2), 1310–1320.
Jiang, D., Huo, L., & Song, H. (2018). Rethinking behaviors and activities of base stations in mobile cellular networks based on big data analysis. IEEE Transactions on Network Science and Engineering, 1(1), 1–12.
Chen, L., Jiang, D., Song, H., Wang, P., Bao, R., Zhang, K., & Li, Y. (2018). A lightweight end-side user experience data collection system for quality evaluation of multimedia communications. IEEE Access, 6(1), 15408–15419.
Tan, J., Xiao, S., Han, S., Liang, Y., & Leung, V. C. M. (2019). QoS-aware user association and resource allocation in LAA-LTE/WiFi coexistence systems. IEEE Transactions on Wireless Communications, 18(4), 2415–2430.
Wang, Y., Tang, X., & Wang, T. (2019). A unified QoS and security provisioning framework for wiretap cognitive radio networks: a statistical queueing analysis approach. IEEE Transactions on Wireless Communications, 18(3), 1548–1565.
Hassan, M. Z., Hossain, M. J., Cheng, J., & Leung, V. C. M. (2020). Hybrid RF/FSO backhaul networks with statistical-QoS-aware buffer-aided relaying. IEEE Transactions on Wireless Communications, 19(3), 1464–1483.
Zhang, Z., Wang, R., Yu, F. R., Fu, F., & Yan, Q. (2019). QoS aware transcoding for live streaming in edge-clouds aided hetnets: an enhanced actor-critic approach. IEEE Transactions on Vehicular Technology, 68(11), 11295–11308.
Chen, L., & Zhang, L. (2020). Spectral efficiency analysis for wireless network system under QoS constraint: an effective capacity perspective. Mobile Networks and Applications. https://doi.org/10.1007/s11036-019-01414-4.
Wang, F., Jiang, D., Qi, S., et al. (2021). A dynamic resource scheduling scheme in edge computing satellite networks. Mobile Networks and Applications, 2021(26), 597–608.
Jiang, D., Huo, L., Lv, Z., et al. (2018). A joint multi-criteria utility-based network selection approach for vehicle-to-infrastructure networking. IEEE Transactions on Intelligent Transportation Systems, 19(10), 3305–3319.
Jiang, D., Zhang, P., Lv, Z., et al. (2016). Energy-efficient multi-constraint routing algorithm with load balancing for smart city applications. IEEE Internet of Things Journal, 3(6), 1437–1447.
Lee, Y., Kim, Y., & Park, S. (2019). A Machine Learning Approach that meets Axiomatic Properties in Probabilistic Analysis of LTE Spectral Efficiency. 2019 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 1451–1453). Korea (South): Jeju Island.
Ji, H., Sun, C., & Shieh, W. (2020). Spectral efficiency comparison between analog and digital RoF for mobile fronthaul transmission link. Journal of Lightwave Technology., 38(20), 5617–5623.
Hayati, M., Kalbkhani, H., & Shayesteh, M. G. (2019) Relay selection for spectral-efficient network-coded multi-source d2d communications. 2019 27th Iranian Conference on Electrical Engineering (ICEE), (pp 1377-1381). Yazd: Iran
You, L., Xiong, J., Zappone, A., Wang, W., & Gao, X. (2020). Spectral efficiency and energy efficiency tradeoff in massive MIMO downlink transmission with statistical CSIT. IEEE Transactions on Signal Processing, 68, 2645–2659.
Jiang, D., Li, W., & Lv, H. (2017). An energy-efficient cooperative multicast routing in multi-hop wireless networks for smart medical applications. Neurocomputing, 220, 160–169.
Wiatr, P., Chen, J., Monti, P., & Wosinska, L. (2015). Energy efficiency versus reliability performance in optical backbone networks [invited] IEEE/OSA. Journal of Optical Communications and Networking, 7(3), A482–A491.
Jiang, D., Wang, Y., Lv, Z., et al. (2021). An energy-efficient networking approach in cloud services for IIoT networks. IEEE Journal on Selected Areas in Communications, 38(5), 928–941.
Jiang, D., Wang, W., Shi, L., et al. (2018). A compressive sensing-based approach to end-to-end network traffic reconstruction. IEEE Transactions on Network Science and Engineering, 5(3), 1–12.
Jiang, D., Huo, L., & Li, Y. (2018). Fine-granularity inference and estimations to network traffic for SDN. PLoS ONE, 13(5), 1–23.
Wang, Y., Jiang, D., Huo, L., et al. (2021). A new traffic prediction algorithm to software defined networking. Mobile Networks and Applications, 2021(26), 716–725.
Barakabitze, A. A., et al. (2020). QoE management of multimedia streaming services in future networks: a tutorial and survey. IEEE Communications Surveys & Tutorials, 22(1), 526–565.
Orsolic, I., & Skorin-Kapov, L. (2020). A framework for in-network QoE monitoring of encrypted video streaming. IEEE Access, 8, 74691–74706.
Song, E., et al. (2020). Threshold-oblivious on-line web QoE assessment using neural network-based regression model. IET Communications, 14(12), 2018–2026.
Seufert, M., Wassermann, S., & Casas, P. (2019). Considering user behavior in the quality of experience cycle: towards proactive QoE-aware traffic management. IEEE Communications Letters, 23(7), 1145–1148.
Chen, L., & Zhang, L. (2020). Spectral efficiency analysis for wireless network system under QoS constraint: an effective capacity perspective. Mobile Networks and Applications, 26(2), 691–699.
Qi, S., Jiang, D., & Huo, L. (2021). A prediction approach to end-to-end traffic in space information networks. Mobile Networks and Applications, 2021(26), 726–735.
Huo, L., Jiang, D., Qi, S., et al. (2021). An AI-based adaptive cognitive modeling and measurement method of network traffic for EIS. Mobile Networks and Applications, 2021(26), 575–585.
Huo, L., Jiang, D., Zhu, X., et al. (2019). A SDN based fine grained measurement and modeling approach to vehicular communication network traffic. International Journal of Communication Systems, 2019(9), 1–19. https://doi.org/10.1002/dac.4092.
Zaborovsky, V., & Meylanov, R., (2001) Informational Network traffic model based on fractional calculus. International Conferences on Info-tech & Info-net
Guo, C., Liang, L., & Li, G. Y. (2019). Resource allocation for low-latency vehicular communications: an effective capacity perspective. IEEE Journal on Selected Areas in Communications, 37(4), 905–917.
Shehab, M., Alves, H., & Latva-aho, M. (2019). Effective capacity and power allocation for machine-type communication. IEEE Transactions on Vehicular Technology, 68(4), 4098–4102.
Cui, Q., Gu, Y., Ni, W., & Liu, R. P. (2017). Effective capacity of licensed-assisted access in unlicensed spectrum for 5g: from theory to application. IEEE Journal on Selected Areas in Communications, 35(8), 1754–1767.
Xiao, C., Zeng, J., Ni, W., Liu, R. P., Su, X., & Wang, J. (2019). Delay guarantee and effective capacity of downlink noma fading channels. IEEE Journal of Selected Topics in Signal Processing, 13(3), 508–523.
Björnson, E., Larsson, E. G., & Debbah, M. (2016). Massive MIMO for maximal spectral efficiency: how many users and pilots should be allocated? IEEE Transactions on Wireless Communications, 15(2), 1293–1308.
Acknowledgements
This work is partly supported by Jiangsu technology project of Housing and Urban-Rural Development (No.2018ZD265) and Jiangsu major natural science research project of College and University (No. 19KJA470002).
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Chen, L., Tian, C., Cui, P. et al. Bursty data service latency analysis under fractional calculus fluid model of Multi-hop Wireless Networks. Wireless Netw 27, 4403–4409 (2021). https://doi.org/10.1007/s11276-021-02666-3
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DOI: https://doi.org/10.1007/s11276-021-02666-3