Energy-Efficient and Reliable Deployment of IoT Applications in a Fog Infrastructure Based on Enhanced Water Strider Algorithm

سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 55

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شناسه ملی سند علمی:

JR_JITM-15-4_010

تاریخ نمایه سازی: 17 دی 1402

چکیده مقاله:

Fog computing is considered a promising solution to minimize processing and networking demands of the Internet of things (IoT) devices. In this work, a model based on the energy consumption evaluation criteria is provided to address the deployment issue in fog computing. Numerous factors, including processing loads, communication protocols, the distance between each connection of fog nodes, and the amount of traffic that is exchanged, all have an impact on the re-search system's overall energy consumption. The power consumption for implementing each com-ponent on the fog node as well as the power consumption for information exchange between the fog nodes are taken into account when calculating each fog node's energy use. Each fog node's energy consumption is closely correlated to how its resources are used, and as a result, to the average normalized resource utilization of a fog node. When the dependent components are spread across two distinct fog nodes, the transfer energy is taken into account in the computations. The sum of the energy used for transmission and the energy used for computational resources is the entire amount of energy consumed by a fog node. The goal is to reduce the energy consumption of the fog network while deploying components using a novel metaheuristic method.  Therefore, this work presents an enhanced water strider algorithm (EWSA) to address the problem of deploying application components with minimum energy consumption. Simulation experiments with two scenarios have been conducted based on the proposed EWSA algorithm. The results show that the EWSA algorithm achieved better performance with ۰.۰۱۳۶۴ and ۰.۰۱۰۰۴ optimal energy consumption rates.

کلیدواژه ها:

Internet of Things ، Fog Computing ، energy-efficient ، applications deployment ، courtship learning-based water strider algorithm ، metaheuristic

نویسندگان

Alsaabri

Biomedical Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Hillah ۵۱۰۰۱, Babil, Iraq.

Al-Khafaji

Biomedical Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, Hillah ۵۱۰۰۱, Babil, Iraq.

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  • Abualigah, L., Yousri, D., Abd Elaziz, M., Ewees, A. A., ...
  • Ahmed, A. M., Rashid, T. A., & Saeed, S. A. ...
  • Al-Khafaji, H. M. R. (۲۰۲۲). Improving Quality Indicators of the ...
  • Al-Khafaji, H. M. R., Alomari, E. S., & Majdi, H. ...
  • Arshed, J. U., Ahmed, M., Muhammad, T., Afzal, M., Arif, ...
  • Chegini, H., Naha, R. K., Mahanti, A., & Thulasiraman, P. ...
  • Cuevas, E., Fausto, F., & González, A. (۲۰۲۰). The locust ...
  • Hasan, M. Z., & Al-Rizzo, H. (۲۰۱۹). Optimization of sensor ...
  • Hassan, S. R., Ahmad, I., Rehman, A. U., Hussen, S., ...
  • Hatamlou, A. (۲۰۱۳). Black hole: A new heuristic optimization approach ...
  • Kaveh, A., & Eslamlou, A. D. (۲۰۲۰, June). Water strider ...
  • Kaveh, A., Khanzadi, M., & Moghaddam, M. R. (۲۰۲۰, October). ...
  • Liu, B., Wang, L., Jin, Y. H., Tang, F., & ...
  • Ouyang, M., Xi, J., Bai, W., & Li, K. (۲۰۲۲). ...
  • Ramezani, M., Bahmanyar, D., & Razmjooy, N. (۲۰۲۰). A new ...
  • Razmjooy, N., Ashourian, M., & Foroozandeh, Z. (Eds.). (۲۰۲۱). Metaheuristics ...
  • Razmjooy, N., Estrela, V. V., & Loschi, H. J. (۲۰۱۹). ...
  • Razmjooy, N., Estrela, V. V., Padilha, R., & Monteiro, A. ...
  • Razmjooy, N., Khalilpour, M., & Ramezani, M. (۲۰۱۶). A new ...
  • Samani, Z. N., Saurabh, N., & Prodan, R. (۲۰۲۱, May). ...
  • Sathya Sofia, A., & GaneshKumar, P. (۲۰۱۸). Multi-objective task scheduling ...
  • Stojmenovic, I. (۲۰۱۴, November). Fog computing: A cloud to the ...
  • Xiao, Y., Sun, X., Guo, Y., Cui, H., Wang, Y., ...
  • Zheng, Z. X., & Li, J. Q. (۲۰۱۸). Optimal chiller ...
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