Demo Data from EDBT 2026 / reviewers in the wild / expert
Michael Leczinsky
dblp:218/6233
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—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 networks
1 paper |
Routing and switching · 56% Network management and operations · 44% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Routing and switching
forwarding table |
0.3 | 1 | 2018 | VeriTable: Fast Equivalence Verification of Multiple Large Forwarding Tables · INFOCOM 2018 |
Network management and operations
network verification |
0.3 | 1 | 2018 | VeriTable: Fast Equivalence Verification of Multiple Large Forwarding Tables · INFOCOM 2018 |
Routing and switching › packet forwarding
IP forwarding |
0.1 | 1 | 2018 | VeriTable: Fast Equivalence Verification of Multiple Large Forwarding Tables · INFOCOM 2018 |
Methods — techniques the papers use, named apart from their topics
trie traversal · 0.3longest prefix matching · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | VeriTable: Fast Equivalence Verification of Multiple Large Forwarding TablesabstractDue to network practices such as traffic engineering and multi-homing, the number of routes-also known as IP prefixes-in the global forwarding tables has been increasing significantly in the last decade and continues growing in a super linear trend. One of the most promising solutions is to use smart Forwarding Information Base (FIB) aggregation algorithms to aggregate the prefixes and convert a large table into a small one. Doing so poses a research question, however, i.e., how can we quickly verify that the original table yields the same forwarding behaviors as the aggregated one? We answer this question in this paper, including addressing the challenges caused by the longest prefix matching (LPM) lookups. In particular, we propose the VeriTable algorithm that can employ a single tree/trie traversal to quickly check if multiple forwarding tables are forwarding equivalent, as well as if they could result in routing loops or black holes. The VeriTable algorithm significantly outperforms the state-of-the-art work for both IPv4 and IPv6 tables in every aspect, including the total running time, memory access times and memory consumption. Garegin Grigoryan, Yaoqing Liu, Michael Leczinsky, Jun Li 0001 |
INFOCOM | 3 |