Smart City Gnosys

Smart city article details

Title	Latency-Aware Placement Of Microservices In The Cloud-To-Edge Continuum Via Resource Scaling
ID_Doc	34796
Authors	Bertoncini A.; Ceselli A.; Quadri C.
Year	2025
Published	Proceedings - 2025 IEEE International Conference on Smart Computing, SMARTCOMP 2025
DOI	http://dx.doi.org/10.1109/SMARTCOMP65954.2025.00103
Abstract	Latency-sensitive applications, such as autonomous driving in smart cities and smart industries, require a networking and computing infrastructure to support their operations. Cloud-to-edge continuum represents a promising architecture to provide computational capability close to edge devices. However, deploying latency-sensitive applications in the continuum is challenging due to the heterogeneity and the geographical distribution of the computing nodes. In this paper, we address the deployment problem in a tele-operated autonomous driving scenario, formulating the orchestration task as a Virtual Network Function Placement Problem (VNFPP) with multi-tier performance levels, enabling vertical scaling of computational resources per microservice. Our MILP model, MORAL, minimizes node centrality-based deployment costs while satisfying resource and end-to-end latency constraints. We tested our approach through extensive simulations on realistic network topologies and synthetic applications, showing that the proposed model improves deployment feasibility, latency compliance, and resource efficiency compared to single performance tier versions and baseline strategies. © 2025 IEEE.
Author Keywords	Cloud-to-Edge Continuum; Mathematical Optimization; Service Orchestration

Similar Articles

Id	Similarity	Authors	Title	Published
21827	0.879	Rosmaninho R.; Raposo D.; Rito P.; Sargento S.	Edge-Cloud Continuum Orchestration Of Critical Services: A Smart-City Approach	IEEE Transactions on Services Computing, 18, 3 (2025)
47314	0.875	Pandey P.	Scalable And Resilient Microservices Deployment For Edge Computing With Kubernetes	International Conference on Advanced Computing Technologies, ICoACT 2025 (2025)
47495	0.867	Zhu J.; Chen H.; Wang H.	Sdt-Mcs: Topology-Aware Microservice Orchestration With Adaptive Learning In Cloud-Edge Environments	Concurrency and Computation: Practice and Experience, 37, 18-20 (2025)
48528	0.864	Rodrigues D.O.; de Souza A.M.; Braun T.; Maia G.; Loureiro A.A.F.; Villas L.A.	Service Provisioning In Edge-Cloud Continuum: Emerging Applications For Mobile Devices	Journal of Internet Services and Applications, 14, 1 (2023)
34793	0.864	Sfaxi H.; Lahyani I.; Yangui S.; Torjmen M.	Latency-Aware And Proactive Service Placement For Edge Computing	IEEE Transactions on Network and Service Management, 21, 4 (2024)
14480	0.863	Ranjbaran S.; Amadeo M.; Marche C.; Ruggeri G.; Sinha A.; Nitti M.	Cloud-Edge Resource Management And Migration: Leveraging Online Learning For Digital Twin Re-Placement	2024 IEEE 10th World Forum on Internet of Things, WF-IoT 2024 (2024)
28911	0.858	Mdemaya G.B.J.; Sindjoung M.L.F.; Ndadji M.M.Z.; Velempini M.	Hercule: High-Efficiency Resource Coordination Using Kubernetes And Machine Learning In Edge Computing For Improved Qos And Qoe	IEEE Access, 13 (2025)
22296	0.857	Khamari S.; Ahmed T.; Mosbah M.	Efficient Edge Server Placement Under Latency And Load Balancing Constraints For Vehicular Networks	Proceedings - IEEE Global Communications Conference, GLOBECOM (2022)
34798	0.851	Shahid U.; Ahmed G.; Siddiqui S.; Shuja J.; Balogun A.O.	Latency-Sensitive Function Placement Among Heterogeneous Nodes In Serverless Computing	Sensors, 24, 13 (2024)
8163	0.851	Qu Q.; Xu R.; Nikouei S.Y.; Chen Y.	An Experimental Study On Microservices Based Edge Computing Platforms	IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2020 (2020)