Hybrid energy-efficient algorithm for efficient Internet of Things deployment

Razaque, Abdul; Jararweh, Yaser; Alotaibi, Bandar; Alotaibi, Munif; Almiani, Muder

doi:10.1016/j.suscom.2022.100715

Cited by 4 publications

(1 citation statement)

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“…Therefore, integrating services provided by IoT devices is necessary. Energy consumption is a critical concern, particularly because most IoT smart devices rely on batteries for power [ 46 , 47 ]. Combining IoT and composite services is essential to ensuring battery longevity and meeting user requirements while optimizing energy consumption.…”

Section: Introductionmentioning

confidence: 99%

A Quality-of-Service-Aware Service Composition Method in the Internet of Things Using a Multi-Objective Fuzzy-Based Hybrid Algorithm

Hamzei,

Khandagh,

Jafari Navimipour

2023

Sensors

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The Internet of Things (IoT) represents a cutting-edge technical domain, encompassing billions of intelligent objects capable of bridging the physical and virtual worlds across various locations. IoT services are responsible for delivering essential functionalities. In this dynamic and interconnected IoT landscape, providing high-quality services is paramount to enhancing user experiences and optimizing system efficiency. Service composition techniques come into play to address user requests in IoT applications, allowing various IoT services to collaborate seamlessly. Considering the resource limitations of IoT devices, they often leverage cloud infrastructures to overcome technological constraints, benefiting from unlimited resources and capabilities. Moreover, the emergence of fog computing has gained prominence, facilitating IoT application processing in edge networks closer to IoT sensors and effectively reducing delays inherent in cloud data centers. In this context, our study proposes a cloud-/fog-based service composition for IoT, introducing a novel fuzzy-based hybrid algorithm. This algorithm ingeniously combines Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC) optimization algorithms, taking into account energy consumption and Quality of Service (QoS) factors during the service selection process. By leveraging this fuzzy-based hybrid algorithm, our approach aims to revolutionize service composition in IoT environments by empowering intelligent decision-making capabilities and ensuring optimal user satisfaction. Our experimental results demonstrate the effectiveness of the proposed strategy in successfully fulfilling service composition requests by identifying suitable services. When compared to recently introduced methods, our hybrid approach yields significant benefits. On average, it reduces energy consumption by 17.11%, enhances availability and reliability by 8.27% and 4.52%, respectively, and improves the average cost by 21.56%.

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Section: Introductionmentioning

confidence: 99%