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Service-Aware Cooperative Task Offloading and Scheduling in Multi-access Edge Computing Empowered IoT

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Algorithms and Architectures for Parallel Processing (ICA3PP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14488))

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Abstract

Multi-access edge computing(MEC) enables computation task offloading and data processing at close proximity to provide rich end-users services with ultra-low latency in Internet of things(IoT). However, the high heterogeneity of the edge node configuration and the diversity of services pose challenges in fully utilizing the computing capacity in MEC. In this paper, we consider the problem of service-aware cooperative task offloading and scheduling in a three-tier MEC empowered IoT where the service requests from IoT devices can be distributed among edge nodes or further offloaded to remote cloud. As this problem is proven to be NP-hard, we proposed a two-layer Cooperative workload Initialization and Distribution Algorithm (CIDA) to solve the problem with low time complexity by decomposing it into two subproblems: 1) the optimization problem of offloading profile under dynamic resource allocation determined by the workload type, and 2) optimization problem of computation resources allocation under given offloading profile. Extensive experiments demonstrate that CIDA achieves superior performance compared to other approaches and scales well as the system size increases.

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References

  1. Laghari, A.A., Wu, K., Laghari, R.A., Ali, M., Khan, A.A.: A review and state of art of internet of things (iot). Archives of Computational Methods in Engineering, pp. 1–19 (2021)

    Google Scholar 

  2. Tao, M., Li, X., Wei, W., Yuan, H.: Jointly optimization for activity recognition in secure iot-enabled elderly care applications. Appl. Soft Comput. 99, 106788 (2021)

    Article  Google Scholar 

  3. Zhu, R., Liu, L., Song, H., Ma, M.: Multi-access edge computing enabled internet of things: advances and novel applications (2020)

    Google Scholar 

  4. Mach, P., Becvar, Z.: Mobile edge computing: a survey on architecture and computation offloading. IEEE Commun. Surv. Tutorials 19(3), 1628–1656 (2017)

    Article  Google Scholar 

  5. 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 

  6. Ma, X., Zhou, A., Zhang, S., Wang, S.: Cooperative service caching and workload scheduling in mobile edge computing. In: IEEE INFOCOM 2020-IEEE Conference on Computer Communications, pp. 2076–2085. IEEE (2020)

    Google Scholar 

  7. Fan, Q., Ansari, N.: Application aware workload allocation for edge computing-based iot. IEEE Internet Things J. 5(3), 2146–2153 (2018)

    Article  Google Scholar 

  8. Tao, M., Xueqiang, L., Kaoru, O., Mianxiong, D.: Single-cell multi-user computation offloading in dynamic pricing-aided mobile edge computing. IEEE Trans. Comput. Social Syst. (2023). https://doi.org/10.1109/TCSS.2023.3308563

    Article  Google Scholar 

  9. Guo, F., Zhang, H., Ji, H., Li, X., Leung, V.C.: An efficient computation offloading management scheme in the densely deployed small cell networks with mobile edge computing. IEEE/ACM Trans. Network. 26(6), 2651–2664 (2018)

    Article  Google Scholar 

  10. Fan, Q., Ansari, N.: Towards workload balancing in fog computing empowered iot. IEEE Trans. Netw. Sci. Eng. 7(1), 253–262 (2018)

    Article  MathSciNet  Google Scholar 

  11. Zhu, X., Zhou, M.: Multiobjective optimized cloudlet deployment and task offloading for mobile-edge computing. IEEE Internet Things J. 8(20), 15582–15595 (2021)

    Article  Google Scholar 

  12. Cui, Y., Song, J., Ren, K., Li, M., Li, Z., Ren, Q., Zhang, Y.: Software defined cooperative offloading for mobile cloudlets. IEEE/ACM Trans. Netw. 25(3), 1746–1760 (2017)

    Article  Google Scholar 

  13. Tao, M., Li, X., Yuan, H., Wei, W.: Uav-aided trustworthy data collection in federated-wsn-enabled iot applications. Inf. Sci. 532, 155–169 (2020)

    Article  Google Scholar 

  14. Tong, L., Li, Y., Gao, W.: A hierarchical edge cloud architecture for mobile computing. In: IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, pp. 1–9. IEEE (2016)

    Google Scholar 

  15. Tao, M., Ota, K., Dong, M.: Dsarp: dependable scheduling with active replica placement for workflow applications in cloud computing. IEEE Trans. Cloud Comput. 8(4), 1069–1078 (2020)

    Article  Google Scholar 

  16. Tan, H., Han, Z., Li, X.Y., Lau, F.C.: Online job dispatching and scheduling in edge-clouds. In: IEEE INFOCOM 2017-IEEE Conference on Computer Communications, pp. 1–9. IEEE (2017)

    Google Scholar 

  17. Chen, M.H., Dong, M., Liang, B.: Resource sharing of a computing access point for multi-user mobile cloud offloading with delay constraints. IEEE Trans. Mob. Comput. 17(12), 2868–2881 (2018)

    Article  Google Scholar 

  18. Zhang, H., Xiao, Y., Bu, S., Niyato, D., Yu, F.R., Han, Z.: Computing resource allocation in three-tier iot fog networks: a joint optimization approach combining stackelberg game and matching. IEEE Internet Things J. 4(5), 1204–1215 (2017)

    Article  Google Scholar 

  19. El Haber, E., Nguyen, T.M., Assi, C.: Joint optimization of computational cost and devices energy for task offloading in multi-tier edge-clouds. IEEE Trans. Commun. 67(5), 3407–3421 (2019)

    Article  Google Scholar 

  20. Chen, Z., He, L.: Modelling task offloading mobile edge computing. In: 2022 The 8th International Conference on Computing and Data Engineering, pp. 15–21 (2022)

    Google Scholar 

  21. Lyu, X., Tian, H., Sengul, C., Zhang, P.: Multiuser joint task offloading and resource optimization in proximate clouds. IEEE Trans. Veh. Technol. 66(4), 3435–3447 (2016)

    Article  Google Scholar 

  22. 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  MathSciNet  Google Scholar 

  23. Tao, M., Ota, K., Dong, M., Yuan, H.: Stackelberg game-based pricing and offloading in mobile edge computing. IEEE Wireless Commun. Lett. 11(5), 883–887 (2022)

    Article  Google Scholar 

  24. Van Adrichem, N.L., Doerr, C., Kuipers, F.A.: Opennetmon: network monitoring in openflow software-defined networks. In: 2014 IEEE Network Operations and Management Symposium (NOMS), pp. 1–8. IEEE (2014)

    Google Scholar 

  25. Sun, X., Ansari, N.: Latency aware workload offloading in the cloudlet network. IEEE Commun. Lett. 21(7), 1481–1484 (2017)

    Article  Google Scholar 

  26. Jia, M., Cao, J., Liang, W.: Optimal cloudlet placement and user to cloudlet allocation in wireless metropolitan area networks. IEEE Trans. Cloud Comput. 5(4), 725–737 (2015)

    Article  Google Scholar 

  27. Gao, B., He, L., Jarvis, S.A.: Offload decision models and the price of anarchy in mobile cloud application ecosystems. IEEE Access 3, 3125–3137 (2015)

    Google Scholar 

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Acknowledgements

This work was supported in part by the Guangdong Key Construction Discipline Research Ability Enhancement Project (Grant No. 2021ZDJS086); in part by the Guangdong University Key Project (Grant No. 2019KZDXM012); in part by the Natural Science Foundation of Guangdong Province (Grant No. 2021A1515010656); in part by Guangdong Basic and Applied Basic Research Foundation (2022B1515120059); in part by the research team project of Dongguan University of Technology (Grant No. TDY-B2019009).

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Authors and Affiliations

  1. School of Computer Science and Technology, Dongguan University of Technology, Dongguan, China

    Zhiyan Chen, Ming Tao & Xueqiang Li

  2. Department of Computer Science, University of Warwick, Coventry, UK

    Ligang He

Authors
  1. Zhiyan Chen
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  2. Ming Tao
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  3. Xueqiang Li
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  4. Ligang He
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Corresponding author

Correspondence to Zhiyan Chen .

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Editors and Affiliations

  1. Royal Melbourne Institute of Technology, Melbourne, VIC, Australia

    Zahir Tari

  2. Tianjin University, Tianjin, China

    Keqiu Li

  3. University of Arizona, Tucson, AZ, USA

    Hongyi Wu

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Chen, Z., Tao, M., Li, X., He, L. (2024). Service-Aware Cooperative Task Offloading and Scheduling in Multi-access Edge Computing Empowered IoT. In: Tari, Z., Li, K., Wu, H. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2023. Lecture Notes in Computer Science, vol 14488. Springer, Singapore. https://doi.org/10.1007/978-981-97-0801-7_19

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  • DOI: https://doi.org/10.1007/978-981-97-0801-7_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0800-0

  • Online ISBN: 978-981-97-0801-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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