View source for Intel corporation (20240126615). PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS simplified abstract

=PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS=


==Organization Name==

[[:Category:intel corporation|intel corporation]]


[[Category:intel corporation]]

==Inventor(s)==

[[:Category:Sundar Nadathur of Cupertino CA (US)|Sundar Nadathur of Cupertino CA (US)]][[Category:Sundar Nadathur of Cupertino CA (US)]]

[[:Category:Akhilesh Thyagaturu of Tampa FL (US)|Akhilesh Thyagaturu of Tampa FL (US)]][[Category:Akhilesh Thyagaturu of Tampa FL (US)]]

[[:Category:Jonathan L. Kyle of Atlanta GA (US)|Jonathan L. Kyle of Atlanta GA (US)]][[Category:Jonathan L. Kyle of Atlanta GA (US)]]

[[:Category:Scott M. Baker of Eugene TX (US)|Scott M. Baker of Eugene TX (US)]][[Category:Scott M. Baker of Eugene TX (US)]]

[[:Category:Woojoong Kim of San Jose CA (US)|Woojoong Kim of San Jose CA (US)]][[Category:Woojoong Kim of San Jose CA (US)]]

==PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240126615 titled 'PREDICTIVE WORKLOAD ORCHESTRATION FOR DISTRIBUTED COMPUTING ENVIRONMENTS

==Simplified Explanation==

The patent application describes a method for orchestrating the execution of workloads on a distributed computing infrastructure based on predicted future operating conditions of compute devices.

* Environment data is received for compute devices in a distributed computing infrastructure.
* The environment data includes information about the operating environment and physical environment of the compute devices.
* Future operating conditions of the compute devices are predicted based on the environment data.
* Workloads are orchestrated for execution on the distributed computing infrastructure based on the predicted future operating conditions.

== Potential Applications ==
This technology could be applied in cloud computing environments, data centers, and other distributed computing systems to optimize workload execution based on predicted future operating conditions of compute devices.

== Problems Solved ==
1. Efficient workload orchestration in distributed computing environments.
2. Predicting future operating conditions of compute devices to proactively manage workloads.

== Benefits ==
1. Improved performance and resource utilization in distributed computing infrastructures.
2. Enhanced reliability and stability of workload execution.
3. Cost savings through optimized resource allocation.

== Potential Commercial Applications ==
Optimized workload orchestration technology could be valuable for cloud service providers, data center operators, and companies with large-scale distributed computing infrastructures.

== Possible Prior Art ==
There may be prior art related to workload orchestration and resource management in distributed computing environments, but specific examples are not provided in the patent application.

=== Unanswered Questions ===

== How does the technology handle unexpected changes in operating conditions of compute devices?
The patent application does not specify how the technology adapts to unforeseen variations in the operating conditions of compute devices.

== What types of workloads are most suitable for orchestration based on predicted future operating conditions?
The patent application does not discuss the specific characteristics or requirements of workloads that would benefit most from this predictive orchestration approach.


==Original Abstract Submitted==

embodiments for orchestrating execution of workloads on a distributed computing infrastructure are disclosed herein. in one example, environment data is received for compute devices in a distributed computing infrastructure. the environment data is indicative of an operating environment of the respective compute devices and a physical environment of the respective locations of the compute devices. future operating conditions of the compute devices are predicted based on the environment data, and workloads are orchestrated for execution on the distributed computing infrastructure based on the predicted future operating conditions.



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