نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی مهندسی برق، دانشگاه آزاد اسلامی، واحد کرمان، ایران
2 استادیار، گروه برق، واحد کرمان، دانشگاه آزاد اسلامی، کرمان، ایران
3 کرمان- بلوار جمهوری- کوچه جمهوری 9- انتهای کوچه- ساخنمان اریون برزن- طبقه 5- واحد 11
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Providing services for real-time, latency-sensitive IoT applications is a major challenge. . Fog environments can significantly reduce the latency of services because they move resources to the nearest edge of the network. On the other hand, fog nodes are not able to provide all the required resources at a large scale due to energy and processing power limitations. For this reason, the problem of optimizing service requests and energy consumption is raised as a major challenge. The nature of this problem is NP-hard, and therefore, exact optimization solutions are insufficient and impractical for large-scale problems. In this regard, a new approach based on the plant defense algorithm (Plant Defense Optimization Algorithm) is proposed as a novel solution to this challenge. This algorithm is inspired by the genetic defense behavior of plants. In the proposed algorithm, genes are first classified using the K-means clustering method. Then, the plant defense optimization algorithm operators are applied specifically to each solution. These operators are designed to avoid local optimality. In this method, the cost function is calculated as a combination of two factors: time delay and energy consumption. The plant defense optimization algorithm is tested in a simulated environment in which environmental dynamics and changes are carefully considered. Finally, the performance of the plant defense optimization algorithm is evaluated and compared with other methods. The experimental results show that the overall delay in the proposed approach is improved between 23.84% and 48.51% compared to other algorithms.
کلیدواژه‌ها [English]
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