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A Decentralized Reactive Approach to Online Task Offloading in Mobile Edge Computing Environments

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Service-Oriented Computing (ICSOC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12571))

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Abstract

In mobile edge computing (MEC) environments, the task offloading towards nearby edge servers usually occurs when local resources are inadequate for computation-intensive applications. While the MEC servers benefit from the close proximity to the end-users to provide services at reduced latency and lower energy costs, they suffer from limitations in computational and radio resources, which calls for smart, timely, and efficient offloading methods and strategies. In this paper, we consider an arbitrary request arrival pattern and formulate the MEC-oriented task offloading problem as an online multi-dimensional integer linear programming. We propose a decentralized reactive approach by adopting a dynamic-learning mechanism to yield online offloading decisions upon request arrivals. Experiments based on real-world MEC environment datasets show that our method outperforms state-of-the-art ones in terms of offloading responsiveness and efficiency.

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Notes

  1. 1.

    https://spark.apache.org/docs/latest/job-scheduling.html.

  2. 2.

    https://ci.apache.org/projects/flink/flink-docs-stable/internals/job_scheduling.html.

  3. 3.

    https://github.com/swinedge/eua-dataset.

  4. 4.

    http://www.sguangwang.com/TelecomDataset.html.

References

  1. Agrawal, S., Wang, Z., Ye, Y.: A dynamic near-optimal algorithm for online linear programming. Oper. Res. 62(4), 876–890 (2014)

    Article  MathSciNet  Google Scholar 

  2. Alameddine, H.A., Sharafeddine, S., Sebbah, S., Ayoubi, S.: Dynamic task offloading and scheduling for low-latency IoT services in multi-access edge computing. IEEE J. Sele. Areas Commun. 37(3), 668–682 (2019)

    Article  Google Scholar 

  3. Chen, L., Zhou, S., Xu, J.: Computation peer offloading for energy-constrained mobile edge computing in small-cell networks. IEEE/ACM Trans. Netw. 26(4), 1619–1632 (2018)

    Article  Google Scholar 

  4. Chen, M., Hao, Y.: Task offloading for mobile edge computing in software defined ultra-dense network. IEEE J. Sel. Areas Commun. 36(3), 587–597 (2018)

    Article  Google Scholar 

  5. Dai, Y., Xu, D., Maharjan, S., Zhang, Y.: Joint computation offloading and user association in multi-task mobile edge computing. IEEE Trans. Veh. Technol. 67(12), 12313–12325 (2018)

    Article  Google Scholar 

  6. Deng, S., Wu, H., Yin, J.: Mobile service provisioning. Mobile Service Computing. ATSTC, vol. 58, pp. 279–329. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-5921-1_8

    Chapter  Google Scholar 

  7. Du, W., et al.: Service capacity enhanced task offloading and resource allocation in multi-server edge computing environment. In: 2019 IEEE International Conference on Web Services (ICWS), pp. 83–90 (2019)

    Google Scholar 

  8. Fang, Z., Lin, J.H., Srivastava, M.B.: Multi-tenant mobile offloading systems for real-time computer vision applications. In: Proceedings of the 20th International Conference on Distributed Computing and Networking, pp. 21–30 (2019)

    Google Scholar 

  9. Feldman, J., Henzinger, M., Korula, N., Mirrokni, V.S., Stein, C.: Online stochastic packing applied to display ad allocation. In: de Berg, M., Meyer, U. (eds.) ESA 2010, Part I. LNCS, vol. 6346, pp. 182–194. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15775-2_16

    Chapter  Google Scholar 

  10. He, Q., et al.: A game-theoretical approach for user allocation in edge computing environment. IEEE Trans. Parallel Distrib. Syst. 31(3), 515–529 (2019)

    Article  Google Scholar 

  11. Huang, L., Bi, S., Zhang, Y.J.: Deep reinforcement learning for online computation offloading in wireless powered mobile-edge computing networks. IEEE Trans. Mob. Comput. 19(11), 2581–2593 (2020)

    Google Scholar 

  12. Lai, P., et al.: Optimal edge user allocation in edge computing with variable sized vector bin packing. In: Pahl, C., Vukovic, M., Yin, J., Yu, Q. (eds.) ICSOC 2018. LNCS, vol. 11236, pp. 230–245. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03596-9_15

    Chapter  Google Scholar 

  13. Lai, P., et al.: Edge user allocation with dynamic quality of service. In: Yangui, S., Bouassida Rodriguez, I., Drira, K., Tari, Z. (eds.) ICSOC 2019. LNCS, vol. 11895, pp. 86–101. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33702-5_8

    Chapter  Google Scholar 

  14. Liu, C.F., Bennis, M., Debbah, M., Poor, H.V.: Dynamic task offloading and resource allocation for ultra-reliable low-latency edge computing. IEEE Trans. Commun. 67(6), 4132–4150 (2019)

    Article  Google Scholar 

  15. Peng, Q., et al.: Mobility-aware and migration-enabled online edge user allocation in mobile edge computing. In: 2019 IEEE International Conference on Web Services (ICWS), pp. 91–98. IEEE (2019)

    Google Scholar 

  16. Rafique, W., Qi, L., Yaqoob, I., Imran, M., u. Rasool, R., Dou, W.: Complementing IoT services through software defined networking and edge computing: a comprehensive survey. IEEE Commun. Surv. Tutor. 22(3), 1761–1804 (2020)

    Google Scholar 

  17. Sun, M., Xu, X., Tao, X., Zhang, P.: Large-scale user-assisted multi-task online offloading for latency reduction in D2D-enabled heterogeneous networks. IEEE Trans. Netw. Sci. Eng. (2020). https://doi.org/10.1109/TNSE.2020.2979511

  18. Wang, S., Guo, Y., Zhang, N., Yang, P., Zhou, A., Shen, X.S.: Delay-aware microservice coordination in mobile edge computing: a reinforcement learning approach. IEEE Trans. Mob. Computi. (2019). https://doi.org/10.1109/TMC.2019.2957804

  19. Wang, S., Zhao, Y., Huang, L., Xu, J., Hsu, C.H.: Qos prediction for service recommendations in mobile edge computing. J. Parallel Distrib. Comput. 127, 134–144 (2019)

    Article  Google Scholar 

  20. Wang, S., Zhao, Y., Xu, J., Yuan, J.: Edge server placement in mobile edge computing. J. Parallel Distrib. Comput. 127, 160–168 (2019)

    Article  Google Scholar 

  21. Xu, J., Chen, L., Zhou, P.: Joint service caching and task offloading for mobile edge computing in dense networks. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications, pp. 207–215. IEEE (2018)

    Google Scholar 

  22. Yang, B., Cao, X., Bassey, J., Li, X., Qian, L.: Computation offloading in multi-access edge computing: a multi-task learning approach. IEEE Trans. Mob. Comput. (2020). https://doi.org/10.1109/TMC.2020.2990630

  23. Yang, L., Zhang, H., Li, X., Ji, H., Leung, V.C.: A distributed computation offloading strategy in small-cell networks integrated with mobile edge computing. IEEE/ACM Trans. Netw. 26(6), 2762–2773 (2018)

    Article  Google Scholar 

  24. Zhao, H., Deng, S., Zhang, C., Du, W., He, Q., Yin, J.: A mobility-aware cross-edge computation offloading framework for partitionable applications. In: 2019 IEEE International Conference on Web Services (ICWS), pp. 193–200. IEEE (2019)

    Google Scholar 

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Acknowledgements

This work is supported in part by the Graduate Scientific Research and Innovation Foundation of Chongqing, China (Grant No. CYB20062 and CYS20066), and the Fundamental Research Funds for the Central Universities (China) under Project 2019CDXYJSJ0022. The author gratefully acknowledges the support of K.C.Wong Education Foundation, Hong Kong.

Author information

Authors and Affiliations

  1. Software Theory and Technology Chongqing Key Lab, Chongqing University, Chongqing, China

    Qinglan Peng, Yunni Xia, Chunrong Wu & Jia Lee

  2. Department of Computing, Macquarie University, Sydney, NSW, 2109, Australia

    Yan Wang

  3. Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

    Xin Luo

Authors
  1. Qinglan Peng
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  2. Yunni Xia
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  3. Yan Wang
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  4. Chunrong Wu
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  5. Xin Luo
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  6. Jia Lee
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Corresponding authors

Correspondence to Yunni Xia or Xin Luo .

Editor information

Editors and Affiliations

  1. Zayed University, Dubai, United Arab Emirates

    Eleanna Kafeza

  2. University of New South Wales, Sydney, NSW, Australia

    Boualem Benatallah

  3. IIT National Research Council C.N.R., Pisa, Italy

    Fabio Martinelli

  4. Zayed University, Dubai, United Arab Emirates

    Hakim Hacid

  5. University of Sydney, Darlington, NSW, Australia

    Athman Bouguettaya

  6. Ernst & Young AI Lab, San Jose, CA, USA

    Hamid Motahari

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Peng, Q., Xia, Y., Wang, Y., Wu, C., Luo, X., Lee, J. (2020). A Decentralized Reactive Approach to Online Task Offloading in Mobile Edge Computing Environments. In: Kafeza, E., Benatallah, B., Martinelli, F., Hacid, H., Bouguettaya, A., Motahari, H. (eds) Service-Oriented Computing. ICSOC 2020. Lecture Notes in Computer Science(), vol 12571. Springer, Cham. https://doi.org/10.1007/978-3-030-65310-1_18

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  • DOI: https://doi.org/10.1007/978-3-030-65310-1_18

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  • Print ISBN: 978-3-030-65309-5

  • Online ISBN: 978-3-030-65310-1

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