Cloud Resource Allocation using Deep Learning Techniques –A Study

The current era of information processing, communication, and technological advances provides resources to clients on demand. The client and service provider determine how much need there is for the resources. The fitness function and resource management strategy determine the best way to allocate cloud resources. Cloud Computing (CC) is a popular technology these days with the use of centralised computing facilities. Clients can utilize these resources to finish calculations, and the CC center will provide the user with the program's processed results. CC is useful for both consumer and business users. Users can save computing expenditures by avoiding the need to buy numerous PCs by investing in a cloud server. In huge-scale distributed computing, allocation of resources is essential as networks of machines face challenging optimization issues. This study is to analyse and evaluate the cloud resource optimization techniques such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), (Long Short term memory (LSTM) and Reinforcement learning (RL) for the allocation of resources in cloud.