View source for 18301852. GARBAGE COLLECTION IN CONSTRAINED LOCAL ENVIRONMENTS simplified abstract (Microsoft Technology Licensing, LLC)

=GARBAGE COLLECTION IN CONSTRAINED LOCAL ENVIRONMENTS=


==Organization Name==

[[:Category:Microsoft Technology Licensing, LLC|Microsoft Technology Licensing, LLC]]


[[Category:Microsoft Technology Licensing, LLC]]

==Inventor(s)==

[[:Category:Maoni Zhang Stephens of Kirkland WA (US)|Maoni Zhang Stephens of Kirkland WA (US)]][[Category:Maoni Zhang Stephens of Kirkland WA (US)]]

[[:Category:Brendan Davis Burns of Seattle WA (US)|Brendan Davis Burns of Seattle WA (US)]][[Category:Brendan Davis Burns of Seattle WA (US)]]

==GARBAGE COLLECTION IN CONSTRAINED LOCAL ENVIRONMENTS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18301852 titled 'GARBAGE COLLECTION IN CONSTRAINED LOCAL ENVIRONMENTS

==Simplified Explanation==
The patent application discusses a method to control garbage collection priority based on local and global memory pressures. This optimization aims to improve garbage collection efficiency, especially in memory overcommitment scenarios.

* Garbage collection priority is determined by both local memory pressure (within a container or isolation unit) and global memory pressure (across the entire machine).
* Each isolation unit and the machine itself have low and high memory pressure thresholds.
* The timing and performance of garbage collection are adjusted to low, normal, or high priority based on these pressures and thresholds.

==Key Features and Innovation==
* Control garbage collection priority based on local and global memory pressures.
* Optimize garbage collection efficiency in memory overcommitment scenarios.
* Set priority levels (low, normal, high) based on memory pressures and thresholds.

==Potential Applications==
This technology can be applied in:
* Cloud computing environments
* Virtualization platforms
* Containerized applications

==Problems Solved==
* Efficient garbage collection in memory-constrained environments
* Improved performance in memory overcommitment scenarios

==Benefits==
* Enhanced system performance
* Better resource utilization
* Reduced memory pressure impact

==Commercial Applications==
Title: Memory Pressure-Based Garbage Collection Optimization
This technology can be utilized in:
* Cloud service providers
* Virtual machine management software
* Container orchestration platforms

==Questions about Memory Pressure-Based Garbage Collection Optimization==
===How does this technology impact overall system performance?===
This technology improves system performance by optimizing garbage collection based on memory pressures, leading to better resource utilization and reduced memory pressure impact.

===What are the potential applications of this optimization method?===
This optimization method can be applied in cloud computing environments, virtualization platforms, and containerized applications to enhance garbage collection efficiency and system performance.


==Original Abstract Submitted==

Embodiments control garbage collection priority based on both a local memory pressure and a global memory pressure. The local pressure represents volatile memory usage in a container or other isolation unit residing on a machine, and the global pressure represents volatile memory usage in the machine overall. The machine is a device or a virtual machine containing one or more isolation units. Each isolation unit has a low threshold and a high threshold, and the machine has its own low threshold and its own high threshold. Garbage collection execution priority is set to low, normal, or high, depending on the memory pressures and the thresholds. By basing garbage collection timing and performance on both local pressure and global pressure, embodiments optimize garbage collection efficiency, especially in memory overcommitment scenarios.



[[Category:G06F12/02]]
[[Category:CPC_G06F12/0253]]