A Hybrid Strategy for Reduction in Time Consumption for Cloud Datacenter Using HMBC Algorithm

Cloud technology is a utility where different hardware and software resources are accessed on pay-per-user ground base. Most of these resources are available in virtualized form and virtual machine (VM) is one of the main elements of visualization. In virtualization, a physical server changes into the virtual machine (VM) and acts as a physical server. Due to the large number of users sometimes the task sent by the user to cloud causes the VM to be under loaded or overloaded. This system state happens due to poor task allocation process in VM and causes the system failure or user tasks delayed. For the improvement of task allocation, several load-balancing techniques are introduced in a cloud but stills the system failure occurs. Therefore we hybrid modified artificial bee colony for improvement in task allocation of VM and minimizing time consummation in cloud datacenter like makespan, total processing time, response time of algorithms, response time of datacenter and degree of imbalance. The consequences of the proposed task-scheduling algorithm are matched with existing heuristic-based scheduling procedures. The experimental consequences demonstrate that our approach is efficient when it is compared with the existing algorithms and reduce 1.7% in time consumption for cloud datacenter.