Optimizing Microservices Placement in the Cloud-to-Edge Continuum: A Comparative Analysis of App and Service Based Approaches
Miguel Mota-Cruz, Jo\~ao H Santos, Jos\'e F Macedo, Karima Velasquez,, David Perez Abreu

TL;DR
This paper compares app-based and service-based microservices placement strategies in cloud-to-edge environments, demonstrating that service-based approaches generally outperform or match app-based methods in reducing latency and balancing load.
Contribution
It introduces a comparative analysis of placement approaches and algorithms for microservices in edge computing, highlighting the advantages of service-based strategies over app-based ones.
Findings
Service-based placement strategies reduce latency more effectively.
Service-based approaches improve load balancing.
Performance varies depending on placement algorithms.
Abstract
In the ever-evolving landscape of computing, the advent of edge and fog computing has revolutionized data processing by bringing it closer to end-users. While cloud computing offers numerous advantages, including mobility, flexibility and scalability, it introduces challenges such as latency. Fog and edge computing emerge as complementary solutions, bridging the gap and enhancing services' proximity to users. The pivotal challenge addressed in this paper revolves around optimizing the placement of application microservices to minimize latency in the cloud-to-edge continuum, where a proper node selection may influence the app's performance. Therefore, this task gains complexity due to the paradigm shift from monolithic to microservices-based architectures. Two distinct placement approaches, app-based and service-based, are compared through four different placement algorithms based on…
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