TEMIS: Provisioning Justice in the Use of Computational Resources in Vehicular Clouds

• Joahannes B. D. da Costa UNICAMP
• Allan M. de Souza UNICAMP
• Denis Rosário UFPA
• Leandro Villas UNICAMP

DOI: https://doi.org/10.5753/sbrc.2024.1225

Abstract

Vehicular Edge Computing (VEC) provides cloud computing services closer to vehicular users by combining computational resources from vehicles and edge nodes to form Vehicular Clouds (VCs). In this scenario, a task scheduler must decide which tasks will be executed on the available VCs, considering contextual aspects such as vehicular mobility and the requirements of these tasks. This is crucial to minimize both processing time and monetary costs associated with resource utilization. However, this direct optimization can lead to resource imbalance, degrading the overall efficiency of the system in terms of performance and fairness in workload distribution. In this context, this work introduces TEMIS, a task scheduling mechanism that takes contextual aspects into account in its decision-making process and applies a probabilistic selection function on VCs to balance processing load and increase fairness in resource utilization. Compared to state-of-the-art solutions, TEMIS demonstrates a higher level of fairness in resource utilization and can schedule a greater number of tasks while minimizing monetary costs and system latency.

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