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Daihui Mo

dblp:214/1934 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Physical-layer communications › synchronization › phase synchronization
phase tracking
0.412020
Phase tracking approach for TDOA measurements in critical lunar spaceflights · Sci. China Inf. Sci. 2020
Vehicular, aerial and satellite networks
space communications
0.412020
Phase tracking approach for TDOA measurements in critical lunar spaceflights · Sci. China Inf. Sci. 2020
Wireless sensing and localization › ranging
time difference of arrival
0.412020
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
YearPublicationVenuePosition
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 Cloudlet
abstract
The 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 Fall5