A Novel Push Pull Optimization Algorithm Fostered Deadline Aware Task Scheduling in Virtualized Cloud Computing

Keeping the quality-of-service criteria, such as dependability, elasticity, minimizing reaction time, maximizing throughput, keeping the task deadline, and also lowering the task rejection ratio, is the most difficult challenge for a service provider for cloud computing. Because of this issue, there is a need for a task scheduling method to be put forth from a service provider that maximizes response time, completes users' tasks by the deadline, complies with service level agreements (SLAs), meets user-defined quality-of-service (QoS) requirements, and increases the implementation of cloud computing resources. The ''Linked List based Push and Pull (LPP) migration of tasks among Virtual Machines in Cloud Environment-LPP Task Scheduling'' technology is a cutting-edge task scheduling method, proposed in this paper. The suggested LPP technique uses the Linked List idea to distribute incoming load across the designated virtual machines in a balanced manner. In the suggested technique, a virtual machine uses the push and pull concepts to execute activities on schedule, enhancing each task's response time while also meeting SLA requirements and making the best use of cloud resources. The assessment findings show the created strategy reduces the SLA violation rate compared to the current method, improves response time, and services the users' tasks by the deadline. The proposed technique is implemented using CloudSim.