Hybrid Adam_POA: Hybrid Adam_Pufferfish Optimization Algorithm Based Load Balancing in Cloud Computing

Cloud Computing (CC) is the model of delivering services for users across internet. The CC is useful to address various issues like scheduling, security and Load balancing (LB). Amongst these problems, LB is the most demanding issue. LB is performed at VM or PM level. When the collection of tasks enter into VM, it uses VM resources and these resources become exhausted, that indicates that there are no resources available for handling the other task requests. Here, an efficient model named Adam_Pufferfish Optimization Algorithm (Adam_POA) is developed for LB in CC. Firstly, the tasks are assigned to the VM in the Data Center (DC) in round robin manner. Based upon VM parameters, VMs are classified as overloaded and underloaded VMs employing Deep Fuzzy Clustering (DFC). After that, divide the tasks in overloaded VM based upon priority. Following to this, the tasks are assigned in overloaded to underloaded VMs for balancing the load in the cloud using hybrid Adam_POA. It is recognized that Adam_POA obtained resource availability with 0.880, capacity with 0.915, load of 0.529 and 0.857 of reliability.