Cloud Computing Based Task Scheduling Management Using Task Grouping for Balancing

Task scheduling in cloud computing is a challenging and essential part to a landscape of technology for a variety of complex undertaking tasks on various resources in a proficient and scalable path. Generally, task scheduling focuses on the completion time from high priority to the low priority, that has led to load imbalance of the process. The aim of this research is to dynamically optimize the aforesaid issue of task scheduling at the both sides for the system-level and user-level. This constitutes give an advantages fairness algorithm based on weighted-fair queuing model, which is significantly more effectively than the existing, that focuses on simple single priority queuing. It intends to combine both time and cost priority task scheduling in a way that is beneficial for the user and dynamically optimized resource allocation for the service provider. The CloudSim toolkit was utilized to demonstrate the simulation of task size and queue weight for the task scheduling algorithm.