Efficient Task Scheduling in Cloud Environment Based on Hyper Min Max Task Scheduling

The growing field of cloud computing deals with large tasks for processing resources. From the application point of view, the research on task scheduling mechanism of data transfer in large-scale cloud computing environment is relatively poor. Unbalanced scheduling leads to traffic overload, energy loss, and failure of hardware control. In addition, residential appliances do not consider delay reduction in power consumption. Hence, Internet of Things (IoT) dominates the current trends in the Internet. The large number of things (things) associated with the Internet creates a large amount of information that requires a lot of effort and work preparation to make it valuable. To resolve this problem, we propose a Hyper Min max task scheduling (HMMTS) based in cascade shrink priority (CSP) to allocate task to optimize the scheduling. With intent a Changeover Load Balancer (CLB) and The Preemptive Flow Manager (PFM) is responsible for the application of load balancing strategy based on the mixed load balancing algorithm improves the task allocation better to balance load to improve the response time. Experimental results have been demonstrated with respect to better load balancing, lower power rate, and time consumption rate in both phase and random uniform propagation. Simulated results performance of this process can reduce data processing time and achieve load neutralization.