Warehouse Task Execution with Preloaded Task Data
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Solution Overview
Problem
Traditional warehouse management systems face inefficiencies in high-throughput scenarios due to the need for real-time retrieval of task information from cloud servers, which delays sorting operations in cargo collection and transfer processes.
Innovation Solution
A method and apparatus that allows terminal devices to store task information sets locally, enabling them to execute tasks efficiently by accessing preconfigured storage spaces for necessary information, reducing reliance on real-time cloud server queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If terminal devices retrieve task information from cloud server in real-time, then task information is always up-to-date, but execution efficiency decreases due to network delays
Solution Approach 1:
The cloud server proactively pushes task information to terminal devices before it is needed. The system determines which tasks meet the preconfigured condition (estimated execution time) and pushes their information in advance, so that when tasks need to be executed, the information is already available locally on the terminal device, eliminating network delay during execution.
Solution Approach 2:
The patent introduces a task information push mechanism as an intermediary between the cloud server and terminal devices. Instead of terminal devices directly querying the cloud server for task information, the cloud server pushes the information through this intermediary mechanism, allowing terminal devices to execute tasks without real-time network connections.
2Productivity
If terminal devices store task information locally, then execution efficiency improves by avoiding network delays, but device storage requirements increase
Solution Approach 1:
The system implements differentiated storage strategies based on task characteristics. Not all task information is stored locally - only tasks that meet the preconfigured condition (estimated execution time) are pushed and stored. This selective local storage approach ensures that storage space is used efficiently while maintaining high execution efficiency for critical tasks.
Data Source
AI summary
A method for warehouse task execution comprises receiving a task information set sent by a cloud server, wherein the task information includes task information of a plurality of target warehousing tasks of the target warehouse depend on, and the target warehousing task is a warehousing task with estimated execution time satisfying a preconfigured condition; storing the task information set in a preconfigured storage space of the terminal device; in response to receiving a task execution instruction indicating an execution of a first warehousing task and the preconfigured storage space comprising the task information that the first warehousing task depends on, obtaining, from the preconfigured storage space, the task information that the first warehousing task depends on; and executing the first warehousing task based on the task information that the first warehousing task depends on.