Minneapolis, MN, United States of America

Brian C Forney


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2010

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1 patent (USPTO):Explore Patents

Title: The Innovations of Brian C. Forney

Introduction

Brian C. Forney is an accomplished inventor based in Minneapolis, MN (US). He has made significant contributions to the field of distributed computing systems. His innovative approach focuses on the efficient management and allocation of computing resources.

Latest Patents

Forney holds a patent for "Autonomic control of a distributed computing system in accordance with a hierarchical model." This patent describes a distributed computing system that adheres to a multi-level, hierarchical organizational model. The system includes control nodes that automate the allocation and management of computing functions and resources. The hierarchical model consists of four distinct levels: fabric, domains, tiers, and nodes. These levels provide logical abstraction and containment of both physical components and application software. System administrators interact with the control nodes to define the hierarchical organization of the distributed computing system. The automation subsystem within the control node utilizes rule engines to provide autonomic control of application nodes based on predefined rules.

Career Highlights

Brian C. Forney is associated with Computer Associates Think, Inc., where he has contributed to various projects and innovations. His work has been instrumental in advancing the capabilities of distributed computing systems.

Collaborations

Some of Forney's notable coworkers include Jerry R. Jackson and Doreen E. Collins. Their collaborative efforts have further enhanced the development of innovative solutions in the field.

Conclusion

Brian C. Forney's contributions to distributed computing systems exemplify the impact of innovative thinking in technology. His patent reflects a deep understanding of hierarchical models and autonomic control, paving the way for more efficient computing solutions.

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