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A taxonomy of load balancing algorithms and approaches in fog computing: a survey

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Abstract

These days, cloud computing usage has been increasing with the rapid growth of Internet coverage all over the world to serve as a pay-per-use model using shared computing resources. Internet of Things (IoT) is a growing technology which is used in different applications and it needs cloud computing however the distance between cloud computing resources and the end system in IoT can cause a delay which is intolerable for delay-sensitive applications. Fog computing is a computing resource between cloud computing and end system to reduce the delay for the delay-sensitive applications in IoT. Therefore, load balancing functionality is a significant role to provide the required quality of service (QoS), quality of experience (QoE), and performance. Load balancing can be done based on response time, throughput, energy consumption, and utilization metrics. In this paper, the papers published in Elsevier, ACM, IEEE, Springer and Wiley between 2018 and 2022 have been examined to extract the load-balancing algorithms, system architecture, tools and applications, advantages and disadvantages. This review is useful for those working on load-balancing performance improvement.

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Authors and Affiliations

  1. Department of Computer & Electrical Engineering, Ale-Taha Institute of Higher Education, Tehran, Iran

    Sepideh Ebneyousef & Alireza Shirmarz

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  1. Sepideh Ebneyousef
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Contributions

The Idea is from Alireza Shirmarz and the Abstract and conclusion have been written by Alireza Shirmarz and the clustering of papers has been done by Alireza Shirmarz. Section 1,2,3,4 have been written by Sepideh Ebneyousef. All authors reviewed the manuscript.

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Correspondence to Alireza Shirmarz.

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Ebneyousef, S., Shirmarz, A. A taxonomy of load balancing algorithms and approaches in fog computing: a survey. Cluster Comput 26, 3187–3208 (2023). https://doi.org/10.1007/s10586-023-03982-3

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