Providing an Improved Resource Management Approach for Healthcare Big Data Processing in Cloud Computing Environment

Due to the gathering of big data and advancement machine learning, healthcare industry has recently experienced fast change. Acceleration operations related analysis retrieval is essential facilitate surveillance. However, providing community a complex task that highly dependent on processing. Also, processing health metadata can be very expensive for organizations. To meet strict service quality requirements industry, large-scale in cloud confederation emerged as viable option. there are many challenges, including optimal resource management Based this, present study, fuzzy solution determining using forecasting technique presented During job processing, selection-based VM migration was used move virtual (VM) from high-load server low-load server. The proposed architecture divided into regional global levels. After evaluating local component, requests sent component. If component cannot requirements, request hierarchical structure method requires generation delivered before estimating available resources. compared with PSO ACO algorithms according different criteria. simulation results show effectiveness efficiency model alternative methods.