
Office: E2-383, MS SOE3
jbyron «at» ucsc·edu
Website
James Byron
I am a Ph.D. candidate in the Storage Systems Research Center (SSRC) working on highly-reliable and scalable archival storage systems. I joined the SSRC in 2016.
As the demand for reliable and capacious archival storage increases, so does the need to design archival storage systems that can adapt over time to changing needs and market conditions. Existing storage technologies are competing for viability in archival storgae systmes based on their characteristics of cost, capacity, performance, reliability, availability, and potential for further developments in the future. Yet prospective storage technologies like archival glass and synthetic DNA may emerge to disrrupt the market for archival storage. I am developing models to evaluate both existing and prospective archival storage technologies on a range of features and in a variety of different archival storage systems to understand and predict their optimal use within archival storage systems both today and in the future.
My current project is to develop a simulation model to predict and measure the cost of using each storage technology while meeting various requirements for total archival system reliability.
Previous Research: I have previously researched the power consumption of archival storage systems, SIMD optimization for sorting algorithms, performance in virtual machines, and diversity in genetic algorithms.
Research Interests: Archival and Reliable Storage, Secure Storage, Big Data, Assistive Technology
Anticipated Graduation: 2021
Visit my profile on Google Scholar.
Publications
Date | Publication | |
---|---|---|
Oct 1, 2020 |
James Byron,
Darrell D. E. Long,
Ethan L. Miller,
Measuring the Cost of Reliability in Archival Systems,Proceeding of the Conference on Mass Storage Systems and Technologies (MSST '20), October 2020. [Storage Class Memories] [Archival Storage] |
|
Sep 26, 2018 |
James Byron,
Darrell D. E. Long,
Ethan L. Miller,
Using Simulation to Design Scalable and Cost-Efficient Archival Storage Systems,Proceedings of the 26th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2018), September 2018. [Archival Storage] |
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