Workflow Scheduling in Cloud Computing Environment using Chaotic Whale Optimization

Abstract

Cloud computing environments enable applications on virtualized resources that can be provisioned dynamically. A cloud workflow system is a platform service which permits to enable the various applications based on cloud infrastructure. Workflow systems have become an easy and efficient task for the development of scientific applications. Efficient workflow scheduling algorithms are employed to improve the resource utilization by enhancing the cloud computing performance and to meet the users’ requirements. Many scheduling algorithms have been proposed but many of them are not optimal to incorporate benefits of Cloud Computing. In this paper a new framework are introduced as Chaotic Whale Optimizer Algorithm (CWOA) which mimics the social behavior of humpback whales and aims to maximize the amount of work completed while meeting QoS constraints such as deadline and budget. This proposed method outperforms well when compared with other techniques and measured in terms of makespan, deadline and it is applicable for real time applications.