Improved DHOA-Fuzzy Based Load Scheduling in IoT Cloud Environment

Internet of things (IoT) has been significantly raised owing to the development broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The IoT technologies resulted in a massive quantity due existence several people linking through distinct physical components, indicating status CC environment. In IoT, load scheduling is realistic technique center guarantee network suitability by falling computer hardware software catastrophe with right utilize resource. ideal balancer improves many factors Quality Service (QoS) like resource performance, scalability, response time, error tolerance, efficiency. scholar assumed as vital problem There are techniques accessible environments. With this motivation, paper presents an improved deer hunting optimization algorithm Type II fuzzy logic (IDHOA-T2F) model for goal IDHOA-T2F diminish energy utilization integrated circuit node enhance IDHOA derived integrating concepts Nelder Mead (NM) DHOA. proposed also synthesized T2L based on (FL) systems counterbalance distribution. finds useful improve efficiency system. For validating enhanced performance technique, series simulations take place highlight performance. experimental outcomes demonstrate capable outcome over recent techniques.