An Effective Cloud Resource Allocation Framework with User Authentication Based on BED-DSA and AR-BiLSTM

Cloud resource allocation is a process of analyzing the Virtual Machines (VMs) availability and allocating it for running tasks. However, the longer queues in the network increased the delay in allocating the resources. So, a significant cloud Resource Allocation (RA) framework is proposed using Conhattan K-Means (C-K Means) and Aranmoid-Ridge Bilateral Long Short-Term Memory (AR-BiLSTM). Initially, the cloud users are registered and log in with their required tasks. During registration, a Service Level Agreement (SLA) is created betwixt the cloud server and user. Based on the SLA and tasks, a digital signature is created. Then, the tasks are clustered by using C-K Means; afterward, the clustered tasks are prioritized. Next, the workloads of the VMs are predicted by preprocessing the data and then extracting features from it. Then, optimal features are selected and given to AR-BiLSTM. Then, the features of the prioritized tasks and VMs are extracted and analyzed to allocate the suitable VM to the particular tasks. Here, the created signature is verified to ensure the user authentication for allocating resources. The analysis results proved the superiority of the proposed framework in allocating cloud resources by utilizing the maximum resources of 0.95.