Demo Data from VLDB 2026 / reviewers in the wild / expert
Charles R. Standridge
dblp:66/2101
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1996
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1
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
1 paper |
Content delivery and video streaming · 91% Internet architecture and protocols · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Content delivery and video streaming › caching
cache hit ratio |
0.0 | 1 | 1996 | Removal Policies in Network Caches for World-Wide Web Documents · SIGCOMM 1996 |
Content delivery and video streaming › caching › cache management
cache replacement |
0.0 | 1 | 1996 | Removal Policies in Network Caches for World-Wide Web Documents · SIGCOMM 1996 |
Content delivery and video streaming › caching
web caching |
0.0 | 1 | 1996 | Removal Policies in Network Caches for World-Wide Web Documents · SIGCOMM 1996 |
Internet architecture and protocols › world wide web
web proxy |
0.0 | 1 | 1996 | Removal Policies in Network Caches for World-Wide Web Documents · SIGCOMM 1996 |
Methods — techniques the papers use, named apart from their topics
trace-driven simulation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1996 | Removal Policies in Network Caches for World-Wide Web DocumentsabstractWorld-Wide Web proxy servers that cache documents can potentially reduce three quantities: the number of requests that reach popular servers, the volume of network traffic resulting from document requests, and the latency that an end-user experiences in retrieving a document. This paper examines the first two using the measures of cache hit rate and weighted hit rate (or fraction of client-requested bytes returned by the proxy). A client request for an uncached document may cause the removal of one or more cached documents. Variable document sizes and types allow a rich variety of policies to select a document for removal, in contrast to policies for CPU caches or demand paging, that manage homogeneous objects. We present a taxonomy of removal policies. Through trace-driven simulation, we determine the maximum possible hit rate and weighted hit rate that a cache could ever achieve, and the removal policy that maximizes hit rate and weighted hit rate. The experiments use five traces of 37 to 185 days of client URL requests. Surprisingly, the criteria used by several proxy-server removal policies (LRU, Hyper-G, and a proposal by Pitkow and Recker) are among the worst performing criteria in our simulation; instead, replacing documents based on size maximizes hit rate in each of the studied workloads. Marc Abrams, Charles R. Standridge, Ghaleb Abdulla, Edward A. Fox, Stephen M. Williams |
SIGCOMM | 2 |