A task scheduling method and device of an energy data platform, a terminal device, and a storage medium

What is AI technical title?
AI technical title is built by PatSnap AI team. It summarizes the technical point description of the patent document.
By predicting changes in business scenarios and constructing resource topology maps, task allocation and scheduling are optimized, solving the problem of high resource consumption in task scheduling in existing energy data platforms and improving task completion efficiency.

CN122311902APending Publication Date: 2026-06-30GUANGDONG POWER GRID CO LTD INFORMATION CENT +1

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Applications(China)
Current Assignee / Owner: GUANGDONG POWER GRID CO LTD INFORMATION CENT
Filing Date: 2026-04-01
Publication Date: 2026-06-30

AI Technical Summary

Technical Problem

Existing energy data platforms struggle to dynamically adjust task scheduling based on changes in business scenarios and system load, resulting in high resource consumption and low task completion efficiency.

Method used

By acquiring task data, node status, and transmission channel load status, we can predict the changing trends of business scenarios, assess the business value of tasks at future moments, construct a resource topology map, and allocate and schedule tasks with the goals of maximizing the total business value score, minimizing resource consumption, and minimizing task latency, thereby generating a task scheduling instruction table.

Benefits of technology

It fully considers the value of task processing, resource consumption, and latency in different business scenarios, dynamically adjusts resource allocation, improves task completion efficiency, and overcomes the problem of high resource consumption.

✦ Generated by Eureka AI based on patent content.

Smart Images

Figure CN122311902A_ABST

Patent Text Reader

Abstract

This invention discloses a task scheduling method, apparatus, terminal device, and storage medium for an energy data platform, belonging to the field of computer technology. The method predicts business scenario change trends based on task data and evaluates the business value of each task to be executed at several future moments based on these trends, determining a business value score for each task at each future moment. Further, a resource topology map is constructed, and tasks are allocated based on the business value scores and the resource topology map, with the objectives of maximizing the total business value score, minimizing resource consumption, and minimizing task latency. This generates a task scheduling instruction table for each future moment and sends the task scheduling instructions to each data processing node. Therefore, this invention overcomes the problems of high resource consumption and low task completion efficiency in current task scheduling methods.

Need to check novelty before this filing date? Find Prior Art