نوع مقاله : مقاله پژوهشی
نویسندگان
1 کارشناسی ارشد، دانشگاه شهرکرد، شهرکرد، ایران
2 استادیار، دانشگاه شهرکرد، شهرکرد، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Modern smart vehicles are connected to complex communication networks and exchange a massive volume of data, leading to increased energy consumption in these networks. In this study, a novel method for optimizing energy consumption in smart vehicular networks is proposed. The proposed approach is based on two dynamic load balancing techniques: First, setting dynamic thresholds based on the average workload of virtual machines, second, predicting future workload using regression analysis. Simulation results demonstrate that using 10% and 20% higher than the average workload threshold reduces energy consumption and improves load balancing efficiency. Additionally, the workload prediction model shows only a 5% deviation between predicted and actual values, indicating high accuracy. This algorithm significantly reduces energy consumption and improves the success rate of virtual machine migrations. The proposed method can be further utilized for efficient resource management in smart vehicular networks, contributing to lower operational costs and environmental sustainability.
کلیدواژهها [English]
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