Gradient Beetle Honey Badger Optimization based container migration and optimal key selection using Firefly Honey Badger Algorithm in cloud computing

Cloud migration involves virtual machines and containers, and the technology has many advantages, such as fault tolerance, manageability, load balancing, and energy efficiency. One of the biggest challenges in migration is securing the data that is migrated with the virtual machine or container. An effective approach for data security during container migration has been implemented using Gradient Beetle Honey Badger Optimization and Firefly Honey Badger Algorithm (GBHBA+FHBA) .At first, cloud model is simulated with PM, VM and containers. Here, tasks are assigned to VM in a round robin manner. The load prediction of VM and PM is done utilizing deep recurrent neural network (DRNN). Before container migration, data preservation is carried out using optimal key. The optimal key is selected employing Firefly Honey Badger Algorithm (FHBA), where FHBA is designed by combining Firefly algorithm (FA) and Honey Badger Algorithm (HBA). The container migration is conducted using proposed GBHBA by considering predicted load, migration cost, resource utilization, energy consumption and trust whereas GBHBA is the incorporation of Gradient Descent (GD) with Namib Beetle Optimization (NBO) and HBA. Additionally, GBHBA+FHBA attained minimum load of 0.126, minimum migration cost of 11.3 and minimum energy consumption of 0.041 respectively.