Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ran Duo
dblp:231/8623
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 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 networks
1 paper |
Vehicular, aerial and satellite networks · 56% Network management and operations · 36% Cellular and mobile networks · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network management and operations
network control |
0.4 | 1 | 2020 | Context-Aware Clustering for SDN Enabled Network · ICNP 2020 |
Vehicular, aerial and satellite networks › vehicular networks
vehicle clustering |
0.4 | 1 | 2020 | Context-Aware Clustering for SDN Enabled Network · ICNP 2020 |
Vehicular, aerial and satellite networks
vehicular networks |
0.4 | 1 | 2020 | Context-Aware Clustering for SDN Enabled Network · ICNP 2020 |
Cellular and mobile networks
5g |
0.1 | 1 | 2020 | Context-Aware Clustering for SDN Enabled Network · ICNP 2020 |
Network management and operations
quality of service management |
0.1 | 1 | 2020 | Context-Aware Clustering for SDN Enabled Network · ICNP 2020 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Context-Aware Clustering for SDN Enabled NetworkabstractNowadays, fifth-generation (5G) technology is promoted to support massive data transmissions and low-latency communications, which enables diverse vehicular applications. There have been some studies discussing the use of vehicle clustering to save scarce spectrum resources, and prevent network congestions in hybrid cellular/IEEE 802.11p vehicular environments. However, different types of applications could have different levels of quality-of-service (QoS) requirements, and thus this issue should be considered in the clustering of vehicles. We propose a novel vehicle clustering scheme that utilizes the global view and programmable advantage of software defined networking (SDN) technology to conduct an efficient clustering in vehicular environments. The proposed scheme first classifies the existing applications to three different types, the delay-sensitive type, traffic-intensive type, and computation-intensive type, according to the QoS requirements. Then the scheme forms three different clusters based on this classification to satisfy the QoS requirement for each type. We use computer simulations to show the advantage of the proposed scheme over the conventional approach. Ran Duo, Celimuge Wu, Tsutomu Yoshinaga, Yusheng Ji |
ICNP | 1 |