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Wuping Mao

dblp:375/6388 · DBLP profile ↗
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4ranked-venue papers
0as first author
4since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 2 since 2021Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 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
Content delivery and video streaming · 44% Edge and fog computing · 44% Cellular and mobile networks · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Content delivery and video streaming › caching › distributed caching
cooperative caching
1.012026
Edge Collaborative Caching Strategy in Space-Air-Ground Integrated Networks · IEEE Trans. Commun. 2026
Edge and fog computing › edge caching
cooperative edge caching
1.012026
Edge Collaborative Caching Strategy in Space-Air-Ground Integrated Networks · IEEE Trans. Commun. 2026
Cellular and mobile networks › 6g
space-air-ground integrated network
0.312026
Edge Collaborative Caching Strategy in Space-Air-Ground Integrated Networks · IEEE Trans. Commun. 2026
YearPublicationVenuePosition
2026 Edge Collaborative Caching Strategy in Space-Air-Ground Integrated Networks
Wuping Mao, Songtao Guo, Guiyan Liu
IEEE Trans. Commun.3
2025 Meta learning-based deep reinforcement learning algorithm for task offloading in dynamic vehicular network
Tengxiang Jing, Wuping Mao, Guanyu Liu
Eng. Appl. Artif. Intell.5
2024 Edge computing offloading strategy for space-air-ground integrated network based on game theory
Wuping Mao, Guanyu Liu, Bingchuan Guo
Comput. Networks2
2024 Edge computing collaborative offloading strategy for space-air-ground integrated networks
abstract
Summary Due to geographical factors, it is impossible to build large‐scale communication network infrastructure in remote areas, which leads to poor network communication quality in these areas and a series of delay‐sensitive tasks cannot be timely processed and responded. Aiming at the problem of limited coverage in remote areas, the space‐air‐ground integrated networks (SAGIN) combined with mobile edge computing (MEC) can provide low latency and high reliability transmission for offloading delay‐sensitive tasks for users in remote areas. Considering the strong limitation of satellite resources in the space‐ground integrated network and insufficient energy of local user equipment, firstly, a satellite‐UAV cluster‐ground three‐layer edge computing network architecture is proposed in this paper. Under the condition that the delay requirements of various ground tasks are met, the task offloading problem is transformed into a Stackelberg game between ground user equipment and edge servers. In addition, it is proved that the existence of Nash equilibrium in non‐cooperative game between ground user equipment by using potential game. Finally, a Nash equilibrium iterative offloading algorithm based on Stackelberg game (NEIO‐SG) is proposed to find the optimal offloading strategy for tasks to minimize the system offloading cost and the optimal forwarding percentage strategy for offloading tasks to maximize the utility function of the edge server. Simulation results show that compared to other baseline algorithms, NEIO‐SG reduces the total system latency during task offloading by about 13 and the energy consumption of the edge server by about 35.
Biqun Xiang, Anhua Wang, Wuping Mao
Concurr. Comput. Pract. Exp.4