Sunnyvale, CA, United States of America

Sherman Ma

This inventor holds 2 USPTO granted patents. Top assignee: Cisco Technology, Inc.. Active years: 2021-2022.


% Patents Active = 100.0

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2021-2022

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2 patents (USPTO):Explore Patents

Title: Innovations by Sherman Ma in Cloud Networking

Introduction

Sherman Ma is an accomplished inventor based in Sunnyvale, CA. He has made significant contributions to the field of cloud networking, holding 2 patents that showcase his expertise and innovative thinking. His work primarily focuses on scalable statistics and analytics mechanisms that enhance data collection and aggregation in application-centric networks.

Latest Patents

Sherman Ma's latest patents include systems, methods, and computer-readable storage mediums designed for scalable data collection and aggregation of statistics for logical objects within an application-centric network. An analytics agent running on a logical object of this network is elected as either a Designated Stats device (DSD) or a Member Stats device (MSD). If the analytics agent is defined as a DSD, it receives data reported from a downstream MSD communicated over the analytics plane and aggregates data from the MSD that belongs to the same access control list rule. Conversely, if the analytics agent is defined as an MSD, it selects a DSD and reports the statistics to that DSD over the analytics plane.

Career Highlights

Sherman Ma is currently employed at Cisco Technology, Inc., where he continues to develop innovative solutions in cloud networking. His work has been instrumental in advancing the capabilities of data analytics within network systems.

Collaborations

Sherman collaborates with Kalyan Ghosh, leveraging their combined expertise to drive innovation in their projects.

Conclusion

Sherman Ma's contributions to cloud networking through his patents and work at Cisco Technology, Inc. highlight his role as a key innovator in the field. His advancements in scalable statistics and analytics mechanisms are paving the way for more efficient data management in application-centric networks.

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