Xiumin Wang

2.2k total citations · 1 hit paper
81 papers, 1.6k citations indexed

About

Xiumin Wang is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Xiumin Wang has authored 81 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Computer Networks and Communications, 31 papers in Electrical and Electronic Engineering and 17 papers in Artificial Intelligence. Recurrent topics in Xiumin Wang's work include Cooperative Communication and Network Coding (20 papers), IoT and Edge/Fog Computing (17 papers) and Privacy-Preserving Technologies in Data (15 papers). Xiumin Wang is often cited by papers focused on Cooperative Communication and Network Coding (20 papers), IoT and Edge/Fog Computing (17 papers) and Privacy-Preserving Technologies in Data (15 papers). Xiumin Wang collaborates with scholars based in China, Singapore and Hong Kong. Xiumin Wang's co-authors include Xiaoming Chen, Weiwei Wu, Pan Zhou, Xianfu Chen, Xinglin Zhang, Jianping Wang, Kai Liu, Chau Yuen, Deyu Qi and Wenyu Zhang and has published in prestigious journals such as IEEE Access, IEEE Transactions on Wireless Communications and IEEE Transactions on Vehicular Technology.

In The Last Decade

Xiumin Wang

74 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Client Selection for Federated Learning With Non-IID Data in Mobile Edge Computing

2021 153 citations Xiumin Wang, Pan Zhou et al. IEEE Access profile →

Peers

Xiumin Wang

CNC

EEE

AI

CSA

IS

Tie Luo Singapore

Cristian Borcea United States

Takamasa Higuchi United States

Chang Xu China

Eyuphan Bulut United States

Hao Yue United States

Ke Xiao China

Jianfeng Guan China

Longbo Huang China

Tie Luo Singapore

Xiumin Wang

881 ×1.3

CNC

480 ×0.7

EEE

378 ×0.9

AI

550 ×2.0

CSA

130 ×0.5

IS

Citations per year, relative to Xiumin Wang Xiumin Wang (= 1×) peers Tie Luo

Countries citing papers authored by Xiumin Wang

Since Specialization

Citations

This map shows the geographic impact of Xiumin Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiumin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiumin Wang more than expected).

Fields of papers citing papers by Xiumin Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiumin Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiumin Wang. The network helps show where Xiumin Wang may publish in the future.

Co-authorship network of co-authors of Xiumin Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiumin Wang. A scholar is included among the top collaborators of Xiumin Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiumin Wang. Xiumin Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Lin, Weiwei, et al.. (2025). SynFlowFL: A Dynamic Synaptic Flow Framework for Efficient, Personalized Federated Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(5). 3426–3440.

2.

Liu, Guozhi, et al.. (2025). Prodigal: Backdoor defense for federated learning beyond robust aggregation. Knowledge-Based Systems. 333. 114903–114903.

3.

Liu, Guodong, et al.. (2024). A novel virtual machine consolidation algorithm with server power mode management for energy-efficient cloud data centers. Cluster Computing. 27(8). 11709–11725. 4 indexed citations

4.

Wu, Jing, Qimei Chen, Hao Jiang, et al.. (2024). Joint Power and Coverage Control of Massive UAVs in Post-Disaster Emergency Networks: An Aggregative Game-Theoretic Learning Approach. IEEE Transactions on Network Science and Engineering. 11(4). 3782–3799. 6 indexed citations

5.

Lin, Weiwei, et al.. (2024). Prediction of Heterogeneous Device Task Runtime Based on Edge Server-Oriented Deep Neuro-Fuzzy System. IEEE Transactions on Services Computing. 18(1). 372–384. 2 indexed citations

6.

Wang, Xiumin, et al.. (2024). Joint AoI-Aware UAVs Trajectory Planning and Data Collection in UAV-Based IoT Systems: A Deep Reinforcement Learning Approach. IEEE Transactions on Consumer Electronics. 70(4). 6484–6495. 13 indexed citations

7.

Ng, Wing W. Y., et al.. (2023). Fog-Enabled Privacy-Preserving Multi-Task Data Aggregation for Mobile Crowdsensing. IEEE Transactions on Dependable and Secure Computing. 21(3). 1301–1316. 12 indexed citations

8.

Lin, Weiwei, et al.. (2023). Efficient Client Selection Based on Contextual Combinatorial Multi-Arm Bandits. IEEE Transactions on Wireless Communications. 22(8). 5265–5277. 24 indexed citations

9.

Wang, Xiumin, et al.. (2023). Freshness-Aware Incentive Mechanism for Mobile Crowdsensing With Budget Constraint. IEEE Transactions on Services Computing. 16(6). 4248–4260. 16 indexed citations

10.

Wang, Xiumin, et al.. (2022). Heterogeneous Training Intensity for Federated Learning: A Deep Reinforcement Learning Approach. IEEE Transactions on Network Science and Engineering. 10(2). 990–1002. 10 indexed citations

11.

Zhang, Xinglin, et al.. (2022). Multimodal Optimization of Edge Server Placement Considering System Response Time. ACM Transactions on Sensor Networks. 19(1). 1–20. 12 indexed citations

12.

Wang, Xiumin, et al.. (2022). Optimizing the Age of Information for Multi-Source Information Update in Internet of Things. IEEE Transactions on Network Science and Engineering. 9(2). 904–917. 16 indexed citations

13.

Huang, Tiansheng, Weiwei Lin, Xiaobin Hong, et al.. (2021). Adaptive Processor Frequency Adjustment for Mobile-Edge Computing With Intermittent Energy Supply. IEEE Internet of Things Journal. 9(10). 7446–7462. 8 indexed citations

14.

Wang, Xiumin, et al.. (2020). Stable Task Assignment for Mobile Crowdsensing With Budget Constraint. IEEE Transactions on Mobile Computing. 20(12). 3439–3452. 45 indexed citations

15.

Wang, Xiumin, Wayes Tushar, Chau Yuen, & Xinglin Zhang. (2020). Promoting Users’ Participation in Mobile Crowdsourcing: A Distributed Truthful Incentive Mechanism (DTIM) Approach. IEEE Transactions on Vehicular Technology. 69(5). 5570–5582. 17 indexed citations

16.

Wang, Xiumin, Jianping Wang, Xinglin Zhang, Xiaoming Chen, & Pan Zhou. (2020). Joint Task Offloading and Payment Determination for Mobile Edge Computing: A Stable Matching Based Approach. IEEE Transactions on Vehicular Technology. 69(10). 12148–12161. 20 indexed citations

17.

Wang, Xiumin, et al.. (2018). A Distributed Truthful Auction Mechanism for Task Allocation in Mobile Cloud Computing. IEEE Transactions on Services Computing. 14(3). 628–638. 29 indexed citations

18.

Li, Minming, et al.. (2018). Non-Payment Incentive Mechanism Design for Resource Allocation in a Private Cloud System. IEEE Access. 6. 44147–44160.

19.

Guo, Hao, et al.. (2017). Load Balanced Mobile User Recruitment for Mobile Crowdsensing Systems. IEEE Communications Letters. 21(11). 2420–2423. 7 indexed citations

20.

Wang, Xiumin, Weiwei Wu, & Deyu Qi. (2017). Mobility-Aware Participant Recruitment for Vehicle-Based Mobile Crowdsensing. IEEE Transactions on Vehicular Technology. 67(5). 4415–4426. 79 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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