Optimizing resource allocation in the edge: a minimum weighted vertex cover approach

The transition from Cloud Computing to a Cloud-Edge continuum introduces novel opportunities and challenges for data-intensive and interactive Next Generation applications. Strategies that were effective in the Cloud environment now necessitate reconsideration to adapt to the Edge's distributed, dynamic, and heterogeneous ecosystem. Proactively planning the placement of application images becomes crucial to minimize image transfer time, align with the dynamic nature of the system, and meet the strict demands of applications. In this regard, this paper proposes an empirical experimental analysis, by comparing the results of different placement strategies and various network topologies. In particular, we model the problem of proactive placement of application images as a Minimum Weighted Vertex Cover problem. Our results demonstrate that the Greedy approach seems to offer the optimal tradeoff with respect to the number of allocated images and execution time.