Abstract
Container-based microservice provisioning, with its elasticity in terms of the layered structure, enables the sharing of common layers among different edge computing tasks, both within and across edge servers (ES). However, due to the potential hardware breakdowns, each ES may prone to failures, affecting its lifetime (i.e., the time-length that an ES works continuously without interruptions), and in turn leading to the collapse of their hosted/provided microservices or the other ESs’ microservices requesting common layers from it. Obviously, if such an issue cannot be well addressed, the reliability of microservices in serving corresponding tasks may be severely reduced. In this paper, we study the microservice deployment optimization with layer sharing for maximizing the system-wide reliability while satisfying all tasks’ delay requirements. Considering dynamic task generations and the asynchronization of various decision variables with different triggers, we design an online optimization algorithm by leveraging an improved Lyapunov technique integrating randomized rounding and Lagrangian method, which iteratively solves the problem over different timescales. Theoretical analyses and simulations evaluate the performance of the proposed solution, and show its superiority over counterparts.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Tang, Z., Lou, J., Jia, W.: Layer dependency-aware learning scheduling algorithms for containers in mobile edge computing. IEEE Trans. Mobile Comput. (2022)
Shi, Y., Yang, Y., Yi, C., Chen, B., Cai, J.: Towards online reliability-enhanced microservice deployment with layer sharing in edge computing. IEEE Internet Things J. 1 (2024)
Gu, L., Chen, Z., Xu, H., Zeng, D., Li, B., Jin, H.: Layer-aware collaborative microservice deployment toward maximal edge throughput. In: Proceedings of IEEE INFOCOM, pp. 71–79. IEEE (2022)
Zheng, C., et al.: Wharf: sharing docker images in a distributed file system. In: Proceedings of ACM SOCC, pp. 174–185 (2018)
Liu, J., Zhou, A., et al.: Reliability-enhanced task offloading in mobile edge computing environments. IEEE Internet Things J. 9(13), 10:382–10:396 (2021)
Zhou, R., Wu, X., Tan, H., Zhang, R.: Two time-scale joint service caching and task offloading for UAV-assisted mobile edge computing. In: Proceedings of IEEE INFOCOM, pp. 1189–1198. IEEE (2022)
Shi, Y., Yi, C., Wang, R., Wu, Q., Chen, B., Cai, J.: Service migration or task rerouting: a two-timescale online resource optimization for MEC. IEEE Trans. Wirel. Commun. (2023)
Qiu, H., Noura, H., Qiu, M., Ming, Z., Memmi, G.: A user-centric data protection method for cloud storage based on invertible DWT. IEEE Trans. Cloud Comput. 9(4), 1293–1304 (2019)
Yuan, Y., Yi, C., Chen, B., Shi, Y., Cai, J.: A computation offloading game for jointly managing local pre-processing time-length and priority selection in edge computing. IEEE Trans. Veh. Technol. 71(9), 9868–9883 (2022)
Shi, Y., Yi, C., Chen, B., Yang, C., Zhu, K., Cai, J.: Joint online optimization of data sampling rate and preprocessing mode for edge-cloud collaboration enabled industrial IoT. IEEE Internet Things J. 9(17), 16:402–16:417 (2022)
Georgiadis, L., Neely, M.J., Tassiulas, L., et al.: Resource allocation and cross-layer control in wireless networks. Found. Trends Netw. 1(1), 1–144 (2006)
Yang, Y., et al.: Dynamic human digital twin deployment at the edge for task execution: a two-timescale accuracy-aware online optimization. arXiv preprint arXiv:2401.16710 (2024)
Srinivasan, A.: Approximation algorithms via randomized rounding: a survey. In: Proceedings of Advanced Topics in Mathematics (PWN), pp. 9–71 (1999)
Li, X., Zhang, X., Huang, T.: Asynchronous online service placement and task offloading for mobile edge computing. In: Proceedings of IEEE SECON, pp. 1–9 (2021)
Cao, K., Cui, Y., et al.: Edge intelligent joint optimization for lifetime and latency in large-scale cyber–physical systems. IEEE Internet Things J. 9(22), 22:267–22:279 (2021)
Acknowledgments
This work was supported by the State Key Laboratory of Massive Personalized Customization System and Technology under grant No. H&C-MPC-2023-04-01, National Natural Science Foundation of China (NSFC) under grant No. 62176122, Postgraduate Research & Practice Innovation Program of NUAA under grant No. xcxjh20231601, and by Postgraduate Research & Practice Innovation Program of Jiangsu Province under grants No. KYCX22_0372.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Shi, Y., Yang, Y., Yi, C., Wang, J. (2025). Reliability-Enhanced Microservice Deployment. In: Cai, Z., Takabi, D., Guo, S., Zou, Y. (eds) Wireless Artificial Intelligent Computing Systems and Applications. WASA 2024. Lecture Notes in Computer Science, vol 14998. Springer, Cham. https://doi.org/10.1007/978-3-031-71467-2_40
Download citation
DOI: https://doi.org/10.1007/978-3-031-71467-2_40
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-71466-5
Online ISBN: 978-3-031-71467-2
eBook Packages: Computer ScienceComputer Science (R0)