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Miriam Sivan-Zimet

dblp:21/2767 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 61% Storage systems · 39%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › storage devices › storage media
probe storage		 0.012002
Workload based optimization of probe-based storage · SIGMETRICS 2002
Performance modeling and evaluation
simulation		 0.012002
Workload based optimization of probe-based storage · SIGMETRICS 2002
Performance modeling and evaluation › simulation › computer system simulation
storage system simulation		 0.012002
Workload based optimization of probe-based storage · SIGMETRICS 2002
Storage systems › storage hierarchy
secondary storage		 0.012002
Workload based optimization of probe-based storage · SIGMETRICS 2002

Methods — techniques the papers use, named apart from their topics

simulation modeling · 0.0sensitivity analysis · 0.0
YearPublicationVenuePosition
2004 Duplicate Data Elimination in a SAN File System
Demyn Plantenberg, Darrell D. E. Long, Miriam Sivan-Zimet
 MSST4
2002 Workload based optimization of probe-based storage
abstract
The performance gap between microprocessors and secondary storage is still a limitation in today's systems. Academia and industry are developing new technologies to overcome this gap, such as improved read-write head technology and higher storage densities. One promising new technology is probe-based storage[1]. Characteristics of probe-based storage include small size, high density, high parallelism, low power consumption, and rectilinear motion. We have created a probe-based storage simulation model, configurable to different design points, and identify its sensitivity to various parameters.
Miriam Sivan-Zimet, Tara M. Madhyastha
 SIGMETRICS1