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Opportunistic Mobile Data Offloading Using Machine Learning Approach

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Abstract

Currently, cellular networks both 3G and 4G are heavily overloaded due to increasing usage of mobile applications. Offloading mobile data traffic through opportunistic communications is one of promising solution to solve this problem. This has huge advantage over other kinds of offloading techniques like no extra cost, significant reduction of mobile traffic, high efficiency. As a case of study, we are focusing our investigation in opportunistic communication for optimizing target set selection problem. A new algorithm is proposed for generating target set which uses machine learning paradigm. Since, machine learning is an emerging sector in computer science with lots of potential; we integrated it with offloading procedure to achieve better performance in real world scenario. The efficiency of proposed method is measured by comparing it with other methods like Greedy, Heuristic and Random. A case study is conducted incorporating this approach and performance evaluation is done. It can be ensured from this comparison that the proposed algorithm outperforms its counterparts.

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References

  1. Han, B., Hui, P., Kumar, V. A., Marathe, M. V., Shao, J., & Srinivasan, A. (2011). Mobile data offloading through opportunistic communications and social participation. IEEE Transactions on Mobile Computing,11(5), 821–834.

    Article  Google Scholar 

  2. Lee, K., Lee, J., Yi, Y., Rhee, I., & Chong, S. (2013). Mobile data offloading: How much can WiFi deliver? IEEE/ACM Transactions on Networking (ToN),21(2), 536–550.

    Article  Google Scholar 

  3. Cisco, I. (2017). Cisco visual networking index: Global mobile data traffic forecast update. 2016–2021 White paper. San Jose: Cisco.

    Google Scholar 

  4. Yu, H., Cheung, M. H., Iosifidis, G., Gao, L., Tassiulas, L., & Huang, J. (2017). Mobile data offloading for green wireless networks. IEEE Wireless Communications,24(4), 31–37.

    Article  Google Scholar 

  5. Chen, Q., Yu, G., Maaref, A., Li, G. Y., & Huang, A. (2016). Rethinking mobile data offloading for LTE in unlicensed spectrum. IEEE Transactions on Wireless Communications,15(7), 4987–5000.

    Google Scholar 

  6. Iosifidis, G., Gao, L., Huang, J., & Tassiulas, L. (2015). A double-auction mechanism for mobile data-offloading markets. IEEE/ACM Transactions on Networking,23(5), 1634–1647.

    Article  Google Scholar 

  7. Cheng, N., Lu, N., Zhang, N., Shen, X., & Mark, J. (2014). Vehicular WiFi offloading: Challenges and solutions. Vehicular Communications,1(1), 13–21.

    Article  Google Scholar 

  8. Zhuo, X., Gao, W., Cao, G., & Hua, S. (2014). An incentive framework for cellular traffic offloading. IEEE Transactions on Mobile Computing,13(3), 541–555.

    Article  Google Scholar 

  9. Cisco White Papers. (2012). Architecture for mobile data offload over Wi-Fi access networks. C11-701018-00 04/12.

  10. Bennis, M., Simsek, M., Czylwik, A., Saad, W., Valentin, S., & Debbah, M. (2013). When cellular meets WiFi in wireless small cell networks. Communications Magazine,51(6), 44–50.

    Article  Google Scholar 

  11. Srinivasan D, Dey J, Kumar SM, Mukherjee RN (2012). Data offload approaches for mobile operators. Wipro Council of Data Research. Wipro White-Papers.

  12. Apostolaras, A., Iosifidis, G., Chounos, K., Korakis, T., & Tassiulas, L. (2016). A mechanism for mobile data offloading to wireless mesh networks. IEEE Transactions on Wireless Communications,15(9), 5984–5997.

    Article  Google Scholar 

  13. Rimal, B. P., & Maier, M. (2017). Mobile data offloading in FiWi enhanced LTE-A heterogeneous networks. Journal of Optical Communications and Networking,9(7), 601–615.

    Article  Google Scholar 

  14. Peng, W., Li, F., Zou, X., & Wu, J. (2013). The virtue of patience: Offloading topical cellular content through opportunistic links. In IEEE MASS.

  15. Lu, Z., Sun, X., & Porta, T. L. (2016). Cooperative data offloading in opportunistic mobile networks. In INFOCOM.

  16. Zhu, X., Li, Y., Jin, D., & Lu, J. (2017). Contact-aware optimal resource allocation for mobile data offloading in opportunistic vehicular networks. IEEE Transactions on Vehicular Technology,66(8), 7384–7399.

    Article  Google Scholar 

  17. Deng, H., & Hou, I.-H. (2015). Online scheduling for delayed mobile offloading. In IEEE INFOCOM.

  18. Cheung, M. H., & Huang, J. (2015). DAWN: Delay-aware Wi-Fi offloading and network selection. IEEE JSAC,33(6), 1214–1223.

    Google Scholar 

  19. Li, Y., Qian, M., Jin, D., Hui, P., Wang, Z., & Chen, S. (2014). Multiple mobile data offloading through disruption tolerant networks. IEEE Transactions on Mobile Computing,13(7), 1579–1596.

    Article  Google Scholar 

  20. Vukadinovic, V., & Karlsson, G. (2010). Spectral efficiency of mobility assisted podcasting in cellular networks. In Proceedings of the second international workshop mobile opportunistic networking (MobiOpp’10) (pp. 51–57).

  21. Wang, X., Chen, M., Han, Z., Wu, D., & Kwon, T. (2014). Toss: Traffic offloading by social network service-based opportunistic sharing in mobile social networks. In IEEE INFOCOM.

  22. Gao, G., Xiao, M., Wu, J., Han, K., Huang, L., & Zhao, Z. (2017). Opportunistic mobile data offloading with deadline constraints. IEEE Transactions on Parallel and Distributed Systems,28(12), 3584–3599.

    Article  Google Scholar 

  23. Nichterlein, A., Niedermeier, R., Uhlmann, J., & Weller, M. (2010). On tractable cases of target set selection. In Proceedings of the 21st international symposium on algorithms and computation (ISAAC’10), LNCS (Vol. 6506, pp. 378–389).

  24. Zhang, C., Gu, B., Liu, Z., Yamori, K., & Tanaka, Y. (2016). A reinforcement learning approach for cost- and energy-aware mobile data offloading. In 2016 18th Asia-Pacific network operations and management symposium (APNOMS).

  25. Yu, K., Zhang, B., & Li, C. (2017). Mobile data offloading in heterogeneous networks for passengers on a subway train. In IEEE transactions on mobile computing.

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Authors and Affiliations

  1. College of Engineering and Technology, Bhubaneswar, Odisha, India

    Sanjit Kumar Dash, Siddhant Dash & Jibitesh Mishra

  2. Indira Gandhi Institute of Technology, Saranga, Odisha, India

    Sasmita Mishra

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  1. Sanjit Kumar Dash
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  2. Siddhant Dash
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  3. Jibitesh Mishra
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  4. Sasmita Mishra
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Correspondence to Sanjit Kumar Dash.

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Dash, S.K., Dash, S., Mishra, J. et al. Opportunistic Mobile Data Offloading Using Machine Learning Approach. Wireless Pers Commun 110, 125–139 (2020). https://doi.org/10.1007/s11277-019-06715-1

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