Scheduling the Tasks and Balancing the Loads in Cloud Computing Using African Vultures-Aquila Optimization Model

Author:

Raghavender Reddy K. L.,Lathigara Amit,Aluvalu Rajanikanth,Viswanadhula Uma Maheswari

Publisher

Springer Nature Singapore

Reference22 articles.

1. Sefati S, Mousavinasab M, Zareh Farkhady R (2022) Load balancing in cloud computing environment using the Grey wolf optimization algorithm based on the reliability: performance evaluation. The J Supercomput 78(1): 18–42

2. Kothi Laxman RR, Lathigara A, Aluvalu R, Viswanadhula UM (2022) PGWO-AVS-RDA: an intelligent optimization and clustering based load balancing model in cloud. Concurrency Comput: Pract Exp 34(21):e7136

3. Reddy H, Lathigara A, Aluvalu R (2021) Literature survey on adaptive virtual machine scheduling strategy to optimize load balancing in cloud environment. In: 2021 international conference on decision aid sciences and application (DASA). IEEE, pp 1092–1098

4. Haris M, Zubair S (2022) Mantaray modified multi-objective Harris hawk optimization algorithm expedites optimal load balancing in cloud computing. J King Saud Univ-Comput Inf Sci 34(10):9696–9709

5. Manikandan N, Gobalakrishnan N, Pradeep K (2022) Bee optimization based random double adaptive whale optimization model for task scheduling in cloud computing environment. Comput Commun 187:35–44

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