Sanglu Lu
- Computer Networks and Communications top 0.2%
- Caching and Content Delivery 54
- IoT and Edge/Fog Computing 42
- Software-Defined Networks and 5G 39
- Mobile Ad Hoc Networks 37
- Cooperative Communication and Network Coding 32
- Opportunistic and Delay-Tolerant Networks 26
- Media Technology top 0.5%
- Human-Computer Interaction top 1%
- Signal Processing top 1%
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- Cloud Computing and Resource Management 47
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- Indoor and Outdoor Localization Technologies 46
Sanglu Lu
325 papers receiving 6.0k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Computer Networks and Communications 3.1k
- Media Technology 677
- Human-Computer Interaction 360
- Signal Processing 658
- Computer Vision and Pattern Recognition 1.2k
Countries citing papers authored by Sanglu Lu
This map shows the geographic impact of Sanglu Lu'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 Sanglu Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanglu Lu more than expected).
Fields of papers citing papers by Sanglu Lu
This network shows the impact of papers produced by Sanglu Lu. 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 Sanglu Lu. The network helps show where Sanglu Lu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sanglu Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 31 | |
| 10 | 2023 | 4 | |
| 11 | 2023 | 8 | |
| 12 | 2022 | 9 | |
| 13 | 2022 | 1 | |
| 14 | 2022 | 5 | |
| 15 | 2021 | 1 | |
| 16 | 2021 | 22 | |
| 17 | 2019 | 33 | |
| 18 | 2018 | 31 | |
| 19 | 2013 | 32 | |
| 20 | QoS-Aware Replication in Service Composition. | 2009 | 4 |
About Sanglu Lu
Sanglu Lu is a scholar working on Computer Networks and Communications, Human-Computer Interaction, Information Systems, Computer Vision and Pattern Recognition and Media Technology, having authored 342 papers that have together received 6.1k indexed citations. Recurring topics across this work include Caching and Content Delivery (54 papers), Cloud Computing and Resource Management (47 papers), Indoor and Outdoor Localization Technologies (46 papers), IoT and Edge/Fog Computing (42 papers), Software-Defined Networks and 5G (39 papers), Mobile Ad Hoc Networks (37 papers), Cooperative Communication and Network Coding (32 papers) and Opportunistic and Delay-Tolerant Networks (26 papers). The work is most often cited by research in Computer Networks and Communications (3.1k citations), Media Technology (677 citations), Human-Computer Interaction (360 citations), Signal Processing (658 citations) and Computer Vision and Pattern Recognition (1.2k citations). Sanglu Lu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Jie Wu, Zhuzhong Qian, Alex X. Liu, Kang Ling, Muhammad Shahzad, Sheng Zhang, Lei Xie, Wenzhong Li, Wei Wang and Xin Li. Their work appears in journals such as IEEE Transactions on Mobile Computing, IEEE Transactions on Parallel and Distributed Systems, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Computer Networks and IEEE/ACM Transactions on Networking.
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.