Escalonamento de Tarefas Ciente de Contexto para Computação de Borda Veicular

• Joahannes B. D. da Costa UNICAMP
• Allan M. de Souza UNICAMP
• Rodolfo I. Meneguette USP
• Eduardo Cerqueira UFPA
• Denis Rosário UFPA
• Leandro A. Villas UNICAMP

DOI: https://doi.org/10.5753/sbrc.2022.221910

Abstract

Vehicular Edge Computing is a promising paradigm that provides cloud computing services closer to vehicular users. Vehicles and communication infrastructures can cooperatively attend vehicular services with low latency constraints through the vehicular clouds formation and use of these clouds' computational resources, where this last process is called task scheduling. An efficient task scheduler needs to decide which cloud will run the tasks, considering vehicular mobility and tasks' requirements. This is important to minimize processing time and the monetary cost of using computing power. However, the literature solutions do not consider these contextual aspects together, degrading the overall system efficiency. In this way, this work presents CARONTE, a task scheduler mechanism that considers contextual aspects in its decision process. The results have shown that CARONTE is able to schedule more tasks while minimizing monetary cost, computation delay, and queuing time when compared to state-of-the-art solutions.

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