Online Scheduling Technique To Handle Data Velocity Changes in Stream Workflows

Many IoT applications and services such as smart parking traffic control contain a network of different analytical components, which are composed in the form workflow to make better decisions. These workflows also known stream workflows. The focus existing research works is on streaming operator graph, differs from application it involves heterogeneity, multiple data sources outputs. Considering complexity dynamism workflow, meeting real-time analysis requirements at deployment time not whole story velocity changes over time. This change most dynamic that occurs frequently during execution this application. In article, we propose new scheduling technique manages cloud resources handle while maintaining user-defined minimising cost. efficiency proposed evaluated, experimental results showed outperformed its competitors close lower bound.