Demo Data from EDBT 2026 / reviewers in the wild / expert
Daihui Mo
dblp:214/1934
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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 |
Wireless sensing and localization · 33% Physical-layer communications · 33% Vehicular, aerial and satellite networks · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Physical-layer communications › synchronization › phase synchronization
phase tracking |
0.4 | 1 | 2020 | Phase tracking approach for TDOA measurements in critical lunar spaceflights · Sci. China Inf. Sci. 2020 |
Vehicular, aerial and satellite networks
space communications |
0.4 | 1 | 2020 | Phase tracking approach for TDOA measurements in critical lunar spaceflights · Sci. China Inf. Sci. 2020 |
Wireless sensing and localization › ranging
time difference of arrival |
0.4 | 1 | 2020 | Phase tracking approach for TDOA measurements in critical lunar spaceflights · Sci. China Inf. Sci. 2020 |
Methods — techniques the papers use, named apart from their topics
phase tracking · 0.4TDOA · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Phase tracking approach for TDOA measurements in critical lunar spaceflights
Wanhong Hao, Daihui Mo |
Sci. China Inf. Sci. | 3 |
| 2017 | Load Balancing Oriented Computation Offloading in Mobile CloudletabstractThe limited computing ability of mobile device constrains its performance on complex mobile applications. Mobile cloud computing (MCC) has therefore emerged to migrate computation-intensive tasks to remote clouds or mobile cloudlets. Most strategies allocate tasks with minimal response time yet few consider the load of the nodes. In this paper, we focus on the load balancing problem for nodes when they conduct offloading. We first establish a five-tuple characterized task model to capture the response time of offloaded tasks. Then, we formulate the task allocation problem as an integer linear problem (ILP) under certain conditions. Furthermore, we propose a two-step appointment- driven strategy to solve this problem with minimal task response time. Specifically, a modified genetic algorithm (GA) is adopted to coordinate the load of the nodes. Simulations are conducted to prove the feasibility of our strategy and evaluate the performance of load coordination. Danhui Yao, Lin Gui 0001, Fen Hou, Daihui Mo, Hangguan Shan |
VTC Fall | 5 |