Demo Data from EDBT 2026 / reviewers in the wild / expert
Shinae Woo
dblp:129/3030
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3 · 2 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 networks
3 papers |
Software-defined and programmable networks · 57% Transport protocols and congestion control · 21% Network measurement and analytics · 14% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Operating systems · 100% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software-defined and programmable networks
network function virtualization |
0.3 | 1 | 2018 | Elastic Scaling of Stateful Network Functions · NSDI 2018 |
Software-defined and programmable networks › network function
stateful network functions |
0.3 | 1 | 2018 | Elastic Scaling of Stateful Network Functions · NSDI 2018 |
Cloud and datacenter computing
autoscaling |
0.3 | 1 | 2018 | Elastic Scaling of Stateful Network Functions · NSDI 2018 |
Transport protocols and congestion control › TCP
TCP implementation |
0.2 | 1 | 2014 | mTCP: a Highly Scalable User-level TCP Stack for Multicore Systems · NSDI 2014 |
Operating systems
network stack |
0.2 | 1 | 2014 | mTCP: a Highly Scalable User-level TCP Stack for Multicore Systems · NSDI 2014 |
Network measurement and analytics › mobile network measurement
cellular traffic characterization |
0.2 | 1 | 2013 | Comparison of caching strategies in modern cellular backhaul networks · MobiSys 2013 |
Content delivery and video streaming › caching › web caching
prefix caching |
0.0 | 1 | 2013 | Comparison of caching strategies in modern cellular backhaul networks · MobiSys 2013 |
Content delivery and video streaming › caching
web caching |
0.0 | 1 | 2013 | Comparison of caching strategies in modern cellular backhaul networks · MobiSys 2013 |
Methods — techniques the papers use, named apart from their topics
deep flow inspection · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Elastic Scaling of Stateful Network Functions
Shinae Woo, Justine Sherry, Sangjin Han, Sue B. Moon, Sylvia Ratnasamy, Scott Shenker |
NSDI | 1 |
| 2014 | mTCP: a Highly Scalable User-level TCP Stack for Multicore Systems
Eunyoung Jeong, Shinae Woo, Muhammad Asim Jamshed, Haewon Jeong, Sunghwan Ihm, Dongsu Han, KyoungSoo Park |
NSDI | 2 |
| 2013 | Comparison of caching strategies in modern cellular backhaul networksabstractRecent popularity of smartphones drives rapid growth in the demand for cellular network bandwidth. Unfortunately, due to the centralized architecture of cellular networks, increasing the physical backhaul bandwidth is challenging. While content caching in the cellular network could be beneficial, relatively few characteristics of the cellular traffic is known to come up with a highly-effetive caching strategy. In this work, we provide insight into flow and content-level characteristics of modern 3G traffic at a large cellular ISP in South Korea. We first develop a scalable deep flow inspection (DFI) system that can manage hundreds of thousands of concurrent TCP flows on a commodity multicore server. Our DFI system collects various HTTP/TCP-level statistics and produces logs for analyzing the effectiveness of conventional Web caching, prefix-based Web caching, and TCP-level redundancy elimination (RE) without a single packet drop at a 10~Gbps link. Our week-long measurements of over 370 TBs of the 3G traffic reveal that standard Web caching can reduce download bandwidth consumption up to 27.1% while simple TCP-level RE can save the bandwidth consumption up to 42.0% with a cache of 512~GB of RAM. We also find that applying TCP-level RE on the largest 9.4% flows eliminates 68.4% of the total redundancy. Most of the redundancy (52.1%~58.9%) comes from serving the same HTTP objects while the contribution by aliased URLs is up to 38.9%. Shinae Woo, Eunyoung Jeong, Shinjo Park, Jong Min Lee 0001, Sunghwan Ihm, KyoungSoo Park |
MobiSys | 1 |