Research on Worker Allocation Optimization Based on Real-Time Data in Cloud Computing

The core of cloud computing task scheduling optimization for real-time data is to monitor the workload, task requirements, and resource utilization status of the real-time monitoring system, and then flexibly adjust the task allocation plan to improve resource utilization efficiency and accelerate response time. This article deeply analyzes the application of multi-objective optimization technology, optimization of data transmission and processing flow, changes in scheduling strategies based on real-time data, and the improvement of intelligent and adaptive task assignment capabilities, and constructs a comprehensive optimization architecture. By adopting these methods, the performance of cloud computing platforms can be significantly enhanced, task processing latency can be reduced, and scientific allocation of resources can be achieved.