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- Title
State-of-the-Art Load Balancing Algorithms for Mist-Fog-Cloud Assisted Paradigm: A Review and Future Directions.
- Authors
Tripathy, Subhranshu Sekhar; Mishra, Kaushik; Roy, Diptendu Sinha; Yadav, Kusum; Alferaidi, Ali; Viriyasitavat, Wattana; Sharmila, J.; Dhiman, Gaurav; Barik, Rabindra K.
- Abstract
The rapid growth of IoT devices leads to increasing requests. These tremendous requests cannot be processed by IoT devices due to the computational power of IoT devices and the disparate requirements of requests. Cloud computing seemed appealing to service these requests due to its remarkable characteristics. However, the physical gap between the Cloud datacenter and IoT devices causes a huge latency overhead. Furthermore, the centralized datacenter also experiences tremendous power consumption. Therefore, the Fog computing layer is introduced as a complementary layer to Cloud computing in between the IoT and the Cloud layer. Fog computing appears as cutting-edge technology to leverage the large computations in the Fog layer, thereby minimizing the latency gap and the power consumption of the datacenters. A Mist layer is placed in between the Fog and IoT layer to enable routing of the requests to Fog nodes and Cloud virtual machines. Many articles propose different load balancing strategies to distribute the loads uniformly in both Fog and Cloud layers. This contribution considers a wide spectrum of reviews as well as research articles into consideration ranging from 2010 to 2022. Besides, a layered architecture is proposed considering the IoT, Mist, Fog, and Cloud layers. Furthermore, research queries are analyzed and answered about the load balancing for these evolving paradigms, critical issues and challenges, and future directions. It is believed that this contribution would be a helping hand for the nascent researchers to get an insight into evolving paradigms, algorithms, issues, challenges, and future directions.
- Subjects
VIRTUAL machine systems; ALGORITHMS; CLOUD computing; INTERNET of things
- Publication
Archives of Computational Methods in Engineering, 2023, Vol 30, Issue 4, p2725
- ISSN
1134-3060
- Publication type
Article
- DOI
10.1007/s11831-023-09885-1