Demo Data from EDBT 2026 / reviewers in the wild / expert
Tong Liu 0012
dblp:36/5558-12
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-0284-486XORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
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 |
Internet of things and sensor networks · 44% Internet architecture and protocols · 44% Network performance modeling · 13% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet architecture and protocols › multicast
multicast scheduling |
0.5 | 1 | 2021 | Optimal Multicasting Strategies in Underwater Acoustic Networks · IEEE Trans. Mob. Comput. 2021 |
Internet of things and sensor networks › underwater sensor networks
underwater acoustic sensor networks |
0.5 | 1 | 2021 | Optimal Multicasting Strategies in Underwater Acoustic Networks · IEEE Trans. Mob. Comput. 2021 |
Network performance modeling
throughput analysis |
0.1 | 1 | 2021 | Optimal Multicasting Strategies in Underwater Acoustic Networks · IEEE Trans. Mob. Comput. 2021 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.5TDMA scheduling · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Optimal Multicasting Strategies in Underwater Acoustic NetworksabstractRecent advances in underwater networking exploit the large propagation delays in underwater channels to schedule transmissions which increase the performance of underwater acoustic sensor networks (UASNs). The underwater channel is broadcast in nature so it supports broadcast and multicast transmissions. In this paper, we discuss novel scheduling strategies, based on TDMA (Time Division Multiple Access), for UASNs where packets may be bound for multiple destinations. The main contributions are to establish an upper bound on the throughput of multicast networks, in which each packet has the same number of intended destinations, by exploiting large propagation delays, and explore network topologies that can achieve this bound. As an example, we study the throughput of unicast and multicast ring networks, including the properties of optimal, valid, perfect and fair transmission schedules. Further, several algorithms to find fair and optimal schedules for unicast and multicast ring networks are presented. Finally, we perform extensive simulations for uniform ring networks, as well as more general ring networks, in both noiseless and noisy underwater channels. Simulation results verify that the proposed algorithms can effectively determine the optimal schedules for ring networks, which achieve the maximum possible throughput and asymptotically approach the upper bound on the throughput of multicasting UASNs. Tong Liu 0012, Mehul Motani |
IEEE Trans. Mob. Comput. | 2 |