Evolutionary Algorithm Based Task Scheduling in IoT Enabled Cloud Environment

Internet of Things (IoT) is transforming the technical setting conventional systems and finds applicability in smart cities, healthcare, industry, etc. In addition, application areas relating to IoT enabled models are resource-limited necessitate crisp responses, low latencies, high bandwidth, which beyond their abilities. Cloud computing (CC) treated as a resource-rich solution above mentioned challenges. But intrinsic latency CC makes it nonviable. The longer degrades outcome based systems. an emergent dispersed, inexpensive pattern with massive assembly heterogeneous autonomous effective use task scheduling minimizes energy utilization cloud infrastructure rises income service providers by minimization processing time user job. With this motivation, paper presents intelligent Chaotic Artificial Immune Optimization Algorithm for Task Scheduling (CAIOA-RS) environment. proposed CAIOA-RS algorithm solves issue resource allocation It also satisfies makespan carrying out optimum process distinct strategies incoming tasks. design technique incorporates concept chaotic maps into AIOA enhance its performance. A series experiments were carried on CloudSim platform. simulation results demonstrate that indicates model outperforms original version, well other heuristics metaheuristics.