An optimal task scheduling method in IoT-Fog-Cloud network using multi-objective moth-flame algorithm

Küçük Resim Yok

Tarih

2023

Dergi Başlığı

Dergi ISSN

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Yayıncı

Springer

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Nowadays, cloud and fog computing have been leveraged to enhance Internet of Things (IoT) performance. The outstanding potential of cloud platforms accelerates the processing and storage of aggregated big data from IoT equipment. Emerging fog-based schemes can improve service quality to IoT applications and mitigate excessive delays and security challenges. Also, since energy consumption can directly cause CO2 emissions from fog and cloud nodes, an efficient task scheduling method reduces energy consumption. In this regard, the growing need for an efficient task scheduling mechanism considering the optimal management of IoT resources is increasingly felt. IoT's task scheduling based on fog-cloud computing plays a crucial role in responding to users' requests. Optimal task scheduling can improve system performance. Therefore, this study uses an IoT task request scheduling method on resources by the Multi-Objective Moth-Flame Optimization (MOMFO) algorithm. It enhances the quality of IoT services based on fog-cloud computing to reduce task requests' completion and system throughput times and energy consumption. If energy consumption is diminished, the percentage of CO2 emissions is also reduced. Then, the proposed scheduling method to solve the task scheduling problem is evaluated using the datasets. A comparison between the proposed scheme and Particle Swarm Optimization (PSO), Firefly Algorithm (FA), Salp Swarm Algorithms (SSA), Harris Hawks Optimizer (HHO), and Artificial Bee Colony (ABC) is performed to assess the performance. According to experiments, the proposed solution has reduced the completion time of IoT tasks and throughput time, thus cutting down the delay due to the processing of tasks, energy consumption, and CO2 emissions and increasing the system's performance rate.

Açıklama

Anahtar Kelimeler

Cloud Computing, Fog Computing, Internet Of Things, Multi-Objective Moth-Flame Optimization, Task Scheduling

Kaynak

Multimedia Tools and Applications

WoS Q Değeri

N/A

Scopus Q Değeri

Q1

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