Demo Data from SIGIR 2026 / reviewers in the wild / expert
Nathan Orr
dblp:93/267
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none
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 architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% | |
| Theoretical computer science
1 paper |
Automata and formal languages · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
code migration |
0.0 | 1 | 2002 | A Model for Mobile Code Using Interacting Automata · IEEE Trans. Mob. Comput. 2002 |
Distributed systems › distributed mobile computing
code mobility |
0.0 | 1 | 2002 | A Model for Mobile Code Using Interacting Automata · IEEE Trans. Mob. Comput. 2002 |
Distributed systems › distributed mobile computing
mobile agents |
0.0 | 1 | 2002 | A Model for Mobile Code Using Interacting Automata · IEEE Trans. Mob. Comput. 2002 |
Automata and formal languages
cellular automata |
0.0 | 1 | 2002 | A Model for Mobile Code Using Interacting Automata · IEEE Trans. Mob. Comput. 2002 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | A Model for Mobile Code Using Interacting AutomataabstractThe Internet supports migration of code from node to node. A number of paradigms exist for distributed computing and mobile code, including client/server, remote evaluation, code-on-demand, and mobile agents. We find them overly-restrictive views of reality. We propose a model that can express previous paradigms as special cases. We derive a model using cellular automata (CA) abstractions to study relations between local node behavior and global system behavior. Example mobile code systems are provided and existing paradigms are expressed in terms of the model. These examples include network attacks such as viruses, worms, and distributed denial of service (DDoS). A distributed system simulation tool based on the model is described. Simulation results provide insights gained from this work. Richard R. Brooks, Nathan Orr |
IEEE Trans. Mob. Comput. | 2 |