Efficient application image management in the compute continuum: a vertex cover approach based on the think-like-a-vertex paradigm

This paper presents a novel algorithm for the Vertex Cover problem, inspired by the Think-Like-A-Vertex (TLAV) paradigm. The Vertex Cover problem, a fundamental challenge in graph theory, finds significant relevance in the context of the compute continuum, where the optimal placement of application images across a diverse range of computational resources is a critical concern. Our proposed TLAV-based algorithm addresses this challenge by leveraging local information at each vertex to make intelligent decisions, thereby reducing the global complexity of the problem. While this approach could potentially lead to resource overprovisioning, we argue that in the context of the compute continuum, this trade-off can provide more flexibility and redundancy, enhancing the reliability of the system. Through extensive analysis and experimental results, we demonstrate the efficiency and scalability of our algorithm on large-scale graphs, making a significant contribution to the field of resource management in the compute continuum.