Vehicular Edge Computing is a promising paradigm that provides cloud computing services closer to vehicular users. Vehicles and communication infrastructure can cooperatively provide vehicular services with low latency constraints through vehicular cloud formation and using these computational resources via task scheduling. An efficient task scheduler must decide which cloud will run the tasks, considering vehicular mobility and task requirements. This is important to minimize processing time and, consequently, monetary cost. However, the literature solutions do not consider these contextual aspects together, degrading the overall system efficiency. This work presents EFESTO, a task scheduling mechanism that considers contextual aspects in its decision process. The results show that, compared to state-of-the-art solutions, EFESTO can schedule more tasks while minimizing monetary cost and system latency.
Efficient Pareto Optimality-based Task Scheduling for Vehicular Edge Computing
01.09.2022
1944190 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Mobility and Deadline-Aware Task Scheduling Mechanism for Vehicular Edge Computing
IEEE | 2023
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