Zhi Ling Li, 554810 Helga Way NE, Woodstock, GA 30188

7723408, May 25, 2010

Feb 16, 2006

11/357582

Rosario A. Gerhardt - Marietta GA, US
Runqing Qu - Roswell GA, US
Zhi Li - Atlanta GA, US
Robert J. Samuels - Atlanta GA, US
Charles J. Capozzi - Alexandria VA, US

Georgia Tech Research Corporation - Atlanta GA

B22F 1/00

524 1, 524403, 524413, 524430, 524439, 524495, 523204, 252 6254, 252511, 252512, 252514, 501134, 501137, 501139

Composite materials are disclosed having low filler percolation thresholds for filler materials into the composite matrix material along with methods of controlling filler interconnectivity within the composite matrix material. Methods are, thus, disclosed that provide the ability to control the desired properties of the composites. The composites of the present disclosure are characterized by a “pseudo-crystalline” microstructure formed of matrix particles and filler particles where the matrix particles are faceted and substantially retain their individual particle boundaries and where the filler particles are interspersed between the matrix particles at the individual matrix particle boundaries such that the filler particles form a substantially interconnected network that substantially surrounds the individual faceted matrix particles. In an exemplary embodiment, the composites are formed by selecting matrix particles and filler particles wherein the ratio of the average size of the matrix particles to the average size of the filler particles is about 10 or more. The selected matrix particles exhibit a glass transition temperature.

2022030, Sep 22, 2022

Jun 6, 2022

17/805680

- Atlanta GA, US
Frederick Armanino - Milton GA, US
Cathleen Southwick - San Ramon CA, US
Robert Roycroft - Algonquin IL, US
Zhi Li - Palo Alto CA, US

H04L 41/00
H04L 12/46
G06F 9/455
H04L 43/16

A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

2021007, Mar 11, 2021

Nov 2, 2020

17/087580

- Atlanta GA, US
Frederick Armanino - Milton GA, US
Cathleen Southwick - San Ramon CA, US
Robert Roycroft - Algonquin IL, US
Zhi Li - Palo Alto CA, US

H04L 12/24
H04L 12/46
G06F 9/455
H04L 12/26

A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.

2020021, Jul 2, 2020

Dec 27, 2018

16/234248

- Atlanta GA, US
Frederick Armanino - Milton GA, US
Cathleen Southwick - San Ramon CA, US
Robert Roycroft - Algonquin IL, US
Zhi Li - Palo Alto CA, US

H04L 12/24
H04L 12/46
H04L 12/26
G06F 9/455

A method performed by a processor in a network function virtualization infrastructure includes determining an amount of resources consumed by a virtual network function subsequent to a scaling of the amount of resources in response to an occurrence of a predefined trigger event, determining an amount of time elapsed between the predefined trigger event and a completion of the scaling, determining a key performance indicator value for the virtual network function subsequent to completion of the scaling, evaluating an efficiency of the predefined trigger event that triggers the scaling, based on the amount of resources consumed by the virtual network function subsequent to the scaling, the amount of time elapsed between the detection of the predefined trigger event and completion of the scaling, and the key performance indicator for the virtual network function subsequent to completion of the scaling, and adjusting the predefined trigger event based on the evaluating.