This inventor holds 3 USPTO granted patents. Top assignee: International Business Machines Corporation. Active years: 2002-2004.
Company Filing History:
Years Active: 2002-2004
Title: Michael Mallo: Innovator in Data Collection Technologies
Introduction
Michael Mallo is a notable inventor based in Austin, TX (US). He has made significant contributions to the field of data collection technologies, holding a total of 3 patents. His work focuses on scalable and distributed systems that enhance data collection mechanisms.
Latest Patents
Mallo's latest patents include a "Data collector for use in a scalable, distributed, asynchronous data collection mechanism." This invention involves a collector that utilizes input and output queues for priority-based queuing and dispatch of data from endpoints and downstream collector nodes. The system employs Collection Table of Contents (CTOC) data structures to manage data received, ensuring efficient sorting and scheduling based on priority and activation time windows. Additionally, he has developed a "Scheduler for use in a scalable, distributed, asynchronous data collection mechanism," which allows for local scheduling of data transfers without global management. This bifurcation of scheduling logic simplifies the process and enhances the efficiency of data collection.
Career Highlights
Michael Mallo is currently employed at International Business Machines Corporation (IBM), where he continues to innovate in the field of data collection. His work has been instrumental in developing technologies that improve network bandwidth utilization and data transfer efficiency.
Collaborations
Mallo has collaborated with notable coworkers such as Raghavendra Balavalikar Krishnamurthy and Vinod Thankappan Nair, contributing to advancements in their shared field of expertise.
Conclusion
Michael Mallo's contributions to data collection technologies through his innovative patents and work at IBM highlight his role as a significant inventor in this domain. His advancements are paving the way for more efficient data management systems.