Resource provisioning model for executing realistic workload in heterogenous internet of things environment

Abstract

Resource provisioning considering scientific or realistic workload in a heterogeneous internet of things (IoT) environment presents significant challenges in terms of execution time and energy consumption. These challenges arise due to the dynamic nature of scientific or realistic-time workloads and the diverse characteristics of IoT devices. In this study, we propose a resource provisioning model that takes into account the dynamic and real-time nature of IoT workloads in a heterogeneous environment.
The model aims to allocate computational resources effectively, considering the real-time demands of IoT applications while optimizing execution time and energy consumption. Three scientific workloads have been used to evaluate the proposed model. The results have been compared with the existing models. The results show that the proposed model attains better performance in terms of reducing time and energy consumption for the execution of workload tasks.