Strategies and Analyses for Efficient Resource Allocation in Smart Cities Using Edge and Cloud Computing

• Bruno L. R. e Silva UFSJ
• Viviane C. Santos UFSJ
• Alex V. Bastos UFSJ https://orcid.org/0000-0002-9497-5890
• Samuel M. A. Araújo UFSJ https://orcid.org/0000-0002-0872-7234

DOI: https://doi.org/10.5753/sbrc_estendido.2025.7652

Abstract

The resource allocation problem in Smart Cities, integrating Edge and Cloud Computing resources, is addressed in this article. Three models based on Integer Linear Programming are proposed, aiming to: construct feasible solutions, minimize costs, and reduce the makespan. An analysis is presented in which a percentage increase in costs is allowed in exchange for a lower makespan. Experiments using exact algorithms were conducted. When considering the evolution of the network from 2G to 6G, it is observed that the rejection rate tends to increase due to reduced coverage. In cost minimization, still within the context of 6G technologies, costs can be reduced by up to ≈ 4.38% compared to the model that only generates a feasible solution. When optimizing the makespan, the execution time increased from 0.03s to up to 2.35s, but with a reduction of ≈ 84.7% in the makespan.

Keywords: Smart Cities, Edge Computing, Cloud Computing, Integer Linear Programming

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