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Cluster Computing
Erschienen in: Cluster Computing 1/2024

20.04.2023

Task scheduling in the internet of things: challenges, solutions, and future trends

verfasst von: Tianqi Bu, Zanyu Huang, Kairui Zhang, Yang Wang, Haobin Song, Jietong Zhou, Zhangjun Ren, Sen Liu

Erschienen in: Cluster Computing | Ausgabe 1/2024

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Abstract

The Internet of Things (IoT) paradigm, by transforming physical devices into innovative items, affects every aspect of our daily lives. It has brought a slew of evolutionary and revolutionary services that were almost impossible to imagine until recently. The numerous services and applications offered by IoT cover numerous fields, such as personal healthcare, urban life, energy management, and manufacturing. A tremendous amount of data is produced to reach valuable information and meet users’ needs. In addition, since the number of services and applications is increasing rapidly, an efficient method to fulfill the growing demands in different application domains becomes challenging. To handle the mentioned problems, task scheduling mechanisms have a significant influence. Despite the importance of these methods in the IoT, an in-depth and systematic review of the current works in this area is clearly lacking. Therefore, we aim to overcome this gap by adopting an organized manner. In fact, this paper aims to specify the challenging problems in IoT task scheduling, highlight the effective works, and outline some hints for upcoming studies.
Vorheriger Artikel Quantum-PSO based unsupervised clustering of users in social networks using attributes
Nächster Artikel Attribute-based access control scheme for secure storage and sharing of EHRs using blockchain and IPFS

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Metadaten
Titel
Task scheduling in the internet of things: challenges, solutions, and future trends
verfasst von
Tianqi Bu
Zanyu Huang
Kairui Zhang
Yang Wang
Haobin Song
Jietong Zhou
Zhangjun Ren
Sen Liu
Publikationsdatum
20.04.2023
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 1/2024
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-023-03991-2

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