Simulation of Task Scheduling Optimization Model for Internet of Things Based on Improved Genetic Algorithm

Orderly task scheduling in the Internet of Things environment is the key to the coordination of intelligent devices. Because there are many devices in the Internet of Things environment, there are many subtask scheduling processes in each device. There is a very complex correlation between various devices and task scheduling within devices. Some associations are contradictory in themselves, forming multi-core scheduling requirements. The combination of Internet of Things and industry is an important direction of industrial informatization and intelligent development. The Internet of Things system can collect real-time information about people and equipment in production and life. However, the number of sensors, terminal devices and user services in the Internet of Things is huge, and the data they generate and the tasks they submit are expected to be processed quickly and efficiently. Aiming at the problem of event detection in the Internet of Things environment and task scheduling and edge cooperation in the edge network environment, this paper studies the continuous target event boundary detection in the Internet of Things and complex task scheduling in the multi-edge server cooperation environment, and optimizes the detection accuracy and energy efficiency of the continuous target boundary area, the task scheduling delay in the edge network, and the long-term energy consumption delay of the system.