View source for 18517587. RESOURCE SCHEDULING METHODS AND APPARATUSES, AND ELECTRONIC DEVICES simplified abstract (Alipay (Hangzhou) Information Technology Co., Ltd.)

=RESOURCE SCHEDULING METHODS AND APPARATUSES, AND ELECTRONIC DEVICES=


==Organization Name==

[[:Category:Alipay (Hangzhou) Information Technology Co., Ltd.|Alipay (Hangzhou) Information Technology Co., Ltd.]]


[[Category:Alipay (Hangzhou) Information Technology Co., Ltd.]]

==Inventor(s)==

[[:Category:Wei Wu of Hangzhou (CN)|Wei Wu of Hangzhou (CN)]][[Category:Wei Wu of Hangzhou (CN)]]

[[:Category:Denghui Li of Hangzhou (CN)|Denghui Li of Hangzhou (CN)]][[Category:Denghui Li of Hangzhou (CN)]]

[[:Category:Tongkai Yang of Hangzhou (CN)|Tongkai Yang of Hangzhou (CN)]][[Category:Tongkai Yang of Hangzhou (CN)]]

==RESOURCE SCHEDULING METHODS AND APPARATUSES, AND ELECTRONIC DEVICES - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18517587 titled 'RESOURCE SCHEDULING METHODS AND APPARATUSES, AND ELECTRONIC DEVICES

==Simplified Explanation==

The patent application abstract describes resource scheduling methods and apparatuses for electronic devices. The method involves determining estimated resource consumption data of a target container group in multiple time periods in response to a resource application request, obtaining resource amount data of cluster nodes in the same time periods, and scheduling the target container group to cluster nodes based on the estimated resource consumption data and resource amount data.

* Efficient resource allocation in different time periods
* Full utilization of allocated resources by the target container group during operation
* Reduction of waste of cluster resources

== Potential Applications ==
The technology described in this patent application could be applied in cloud computing environments, data centers, and distributed systems where efficient resource allocation and scheduling are crucial.

== Problems Solved ==
This technology addresses the challenge of optimizing resource allocation and utilization in dynamic environments, ensuring that resources are efficiently used without waste.

== Benefits ==
The benefits of this technology include improved performance, reduced resource wastage, and enhanced scalability in resource management.

== Potential Commercial Applications ==
"Optimized Resource Scheduling Methods for Cloud Computing Environments"

== Possible Prior Art ==
One possible prior art in resource scheduling methods could be traditional load balancing algorithms used in distributed systems to optimize resource allocation.

=== Unanswered Questions ===

=== How does this technology compare to existing resource scheduling methods in terms of efficiency and scalability? ===
This article does not provide a direct comparison with existing resource scheduling methods, leaving the reader to wonder about the specific advantages of this technology over current solutions.

=== What are the potential limitations or constraints of implementing this resource scheduling method in real-world applications? ===
The article does not address any potential challenges or constraints that may arise when implementing this resource scheduling method, leaving room for further exploration of its practical implications.


==Original Abstract Submitted==

This specification discloses resource scheduling methods and apparatuses, electronic devices. The resource scheduling method includes following: estimated resource consumption data of a target container group in a plurality of time periods is determined in response to a resource application request of the target container group, resource amount data of each of a plurality of cluster nodes in the plurality of time periods is obtained, and the target container group is scheduled to at least one of the plurality of cluster nodes based on the estimated resource consumption data and the resource amount data. It can be seen that in this specification, different resource amounts can be allocated to the target container group in different time periods, and the target container group can fully use resources allocated to the target container group in each time period during running, thereby reducing the waste of cluster resources.



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