Cost Optimization in Cloud Environment based on Task Deadline

Abstract

The task of a service broker in a cloud computing environment is vital and challenging. Several sophisticated techniques have been proposed to improve the overall performance and minimize the cost. Most of the approaches optimize either performance or the cost; however, the users of cloud and fog need the best compromise for both. In this paper, we propose a hybrid technique that is Cost Optimization in the cloud/fog environment based on Task Deadline (COTD) that focuses on both parameters simultaneously and maintains the Quality of Service. The proposed algorithm is based on the task deadline and selects the most appropriate data center for task processing. We have implemented and tested COTD on a well-known simulation tool Cloud Analyst. Our comprehensive testbed experiments and simulations show that COTD outperforms comparable with Service Proximity Based Routing and Performance-Optimized Routing, and successfully minimizes an average of 35% cost while maintaining the same response time.