Work

Latency-Aware Placement of Microservices in the Cloud-to-Edge Continuum via Resource Scaling

Year: 2025

Type: conference-paper

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.

Source: IEEE International Conference on Smart Computing

DOI: 10.1109/smartcomp65954.2025.00103

Authors: Alberto Bertoncini, Alberto Ceselli, Christian Quadri

Institution: University of Milan

Language: English

Topic: IoT and Edge/Fog Computing

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funder: European Commission