A Heuristic-Based Task Scheduling Policy for QoS Improvement in Cloud

Abstract

Cloud computing is a big step in the parallel and distributed computing that offers pervasive access to the entire stack of computing resources located in the data center via the Internet in a virtualized manner. QoS is an important research direction in the cloud and is a collection of constraints that meets the service level agreement (SLA) between the users and service providers. These constraints are waiting time, completion time, response time, makespan, resource utilization, effective utilization of bandwidth, and load balancing. This work presents a distribution plan for transferring task loads to different virtual machines (VMs) with an efficient load balancing mechanism that is best suited in heterogeneous environments and improve the QoS parameter of users and cloud vendors simultaneously. In this paper, the expected uniform load of tasks that can be mapped to a particular VMs is calculated and after that, the optimal average completion time (OACT) of expected uniform tasks load to each VM is calculated.