Fiskdale, MA, United States of America

Peter Yale Kushner


Average Co-Inventor Count = 3.4

ph-index = 3

Forward Citations = 38(Granted Patents)


Company Filing History:


Years Active: 2002-2021

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5 patents (USPTO):

Title: The Innovations of Peter Yale Kushner

Introduction

Peter Yale Kushner is a notable inventor based in Fiskdale, MA (US). He has made significant contributions to the field of data storage technology, holding a total of 5 patents. His work focuses on enhancing automated data tiering systems, which are crucial for improving database performance.

Latest Patents

Kushner's latest patents include "Positional indexing for a tiered data storage system" and "Tiered data storage system using mobility scoring." The first patent describes a system that improves automated data tiering technology by increasing the speed of data relocation between tiers. This is achieved by reducing the number of sort cycles needed for data relocation. Additionally, the system allows for uninterrupted access to read/write commands, enhancing user experience. The second patent introduces a method for weighing the importance of read, write, and pre-fetch operations in tier placement. This is accomplished through an off-load engine that calculates mobility scores for data relocation, optimizing the performance of the data storage system.

Career Highlights

Throughout his career, Kushner has worked with prominent companies such as EMC IP Holding Company LLC and EMC Corporation. His experience in these organizations has contributed to his expertise in data storage solutions and innovations.

Collaborations

Kushner has collaborated with notable professionals in his field, including Jonathan I Krasner and Chakib Ouarraoui. These collaborations have likely enriched his work and led to further advancements in data storage technology.

Conclusion

Peter Yale Kushner's contributions to data storage technology through his patents and career achievements highlight his role as an influential inventor. His innovative approaches continue to shape the future of automated data tiering systems.

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