Lin Gu

7.4k total citations · 5 hit papers
146 papers, 5.3k citations indexed

About

Lin Gu is a scholar working on Computer Networks and Communications, Information Systems and Electrical and Electronic Engineering. According to data from OpenAlex, Lin Gu has authored 146 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Computer Networks and Communications, 57 papers in Information Systems and 39 papers in Electrical and Electronic Engineering. Recurrent topics in Lin Gu's work include Cloud Computing and Resource Management (46 papers), IoT and Edge/Fog Computing (41 papers) and Energy Efficient Wireless Sensor Networks (31 papers). Lin Gu is often cited by papers focused on Cloud Computing and Resource Management (46 papers), IoT and Edge/Fog Computing (41 papers) and Energy Efficient Wireless Sensor Networks (31 papers). Lin Gu collaborates with scholars based in China, Hong Kong and United States. Lin Gu's co-authors include John A. Stankovic, Deze Zeng, Song Guo, Tian He, Tarek Abdelzaher, Gang Zhou, Liqian Luo, Radu Stoleru, Hai Jin and Bruce H. Krogh and has published in prestigious journals such as IEEE Journal on Selected Areas in Communications, Plant Cell & Environment and Information Sciences.

In The Last Decade

Lin Gu

141 papers receiving 5.0k citations

Hit Papers

Energy-efficient surveillance system using wireless senso... 2004 2026 2011 2018 2004 2006 2006 2016 2015 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lin Gu China 36 4.2k 2.1k 1.1k 753 719 146 5.3k
Gian Pietro Picco Italy 37 4.2k 1.0× 978 0.5× 1.2k 1.1× 985 1.3× 774 1.1× 151 5.2k
Zhetao Li China 35 2.2k 0.5× 1.5k 0.7× 1.3k 1.2× 1.1k 1.4× 649 0.9× 194 4.5k
Ren Ping Liu Australia 37 3.8k 0.9× 2.8k 1.3× 1.4k 1.3× 1.2k 1.6× 381 0.5× 345 6.5k
Lanyu Xu United States 9 3.6k 0.9× 1.3k 0.6× 1.7k 1.6× 1.0k 1.4× 1.1k 1.5× 17 5.3k
Pascal Lorenz France 30 2.4k 0.6× 1.8k 0.8× 785 0.7× 581 0.8× 354 0.5× 298 4.1k
Ruchuan Wang China 30 2.0k 0.5× 1.6k 0.8× 582 0.5× 760 1.0× 587 0.8× 369 4.1k
Dipak Ghosal United States 27 5.6k 1.3× 3.6k 1.7× 328 0.3× 662 0.9× 411 0.6× 174 7.4k
Zubair Md. Fadlullah Canada 41 4.3k 1.0× 4.1k 1.9× 636 0.6× 1.7k 2.2× 598 0.8× 176 8.1k
Prasanta K. Jana India 36 3.8k 0.9× 2.5k 1.2× 1.0k 1.0× 459 0.6× 175 0.2× 148 4.9k

Countries citing papers authored by Lin Gu

Since Specialization
Citations

This map shows the geographic impact of Lin Gu'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 Lin Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Gu more than expected).

Fields of papers citing papers by Lin Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lin Gu. 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 Lin Gu. The network helps show where Lin Gu may publish in the future.

Co-authorship network of co-authors of Lin Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Lin Gu. A scholar is included among the top collaborators of Lin Gu 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 Lin Gu. Lin Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ibrahim, Shadi, et al.. (2025). EDDE: Container Deployment Framework Beyond the Cloud. SPIRE - Sciences Po Institutional REpository. 570–585.
2.
Li, Yuepeng, et al.. (2025). Layer Redundancy Aware DNN Model Repository Planning for Fast Model Download in Edge Cloud. IEEE Transactions on Cloud Computing. 13(3). 1038–1049.
3.
Yu, Hui, Yu Zhang, Ligang He, et al.. (2024). CDA-GNN: A Chain-driven Accelerator for Efficient Asynchronous Graph Neural Network. 1–6. 2 indexed citations
5.
Zeng, Deze, et al.. (2024). PLAYS: Minimizing DNN Inference Latency in Serverless Edge Cloud for Artificial Intelligence of Things. IEEE Internet of Things Journal. 11(23). 37731–37740. 1 indexed citations
6.
Zhang, Yu, Ligang He, Hui Yu, et al.. (2023). GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing. ACM Transactions on Architecture and Code Optimization. 20(3). 1–24. 1 indexed citations
7.
Yu, Hui, Yu Zhang, Zhiying Huang, et al.. (2023). RACE: An Efficient Redundancy-aware Accelerator for Dynamic Graph Neural Network. ACM Transactions on Architecture and Code Optimization. 20(4). 1–26. 9 indexed citations
8.
Li, Yuepeng, et al.. (2023). PASTO: Enabling Secure and Efficient Task Offloading in TrustZone-Enabled Edge Clouds. IEEE Transactions on Vehicular Technology. 72(6). 8234–8238. 8 indexed citations
9.
Zeng, Deze, et al.. (2023). Enabling Efficient Spatio-Temporal GPU Sharing for Network Function Virtualization. IEEE Transactions on Computers. 72(10). 2963–2977. 5 indexed citations
10.
Li, Yuepeng, Deze Zeng, Lin Gu, et al.. (2022). Efficient and Secure Deep Learning Inference in Trusted Processor Enabled Edge Clouds. IEEE Transactions on Parallel and Distributed Systems. 33(12). 4311–4325. 8 indexed citations
11.
Li, Yuepeng, et al.. (2022). Cost Efficient Service Mesh Controller Placement for Edge Native Computing. GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 3 indexed citations
12.
Liao, Xiaofei, Yu Zhang, Bingsheng He, et al.. (2021). A Structure-Aware Storage Optimization for Out-of-Core Concurrent Graph Processing. IEEE Transactions on Computers. 71(7). 1612–1625. 3 indexed citations
13.
Liang, Yuxuan, Yu Zhang, Xiaofei Liao, et al.. (2020). GGraph: An Efficient Structure-Aware Approach for Iterative Graph Processing. IEEE Transactions on Big Data. 8(5). 1182–1194. 11 indexed citations
14.
Zhang, Yu, Xiaofei Liao, Hai Jin, et al.. (2018). Cgraph: a correlations-aware approach for efficient concurrent iterative graph processing. Warwick Research Archive Portal (University of Warwick). 441–452. 13 indexed citations
15.
Jin, Hai, Song Wu, Yin Yao, et al.. (2018). Towards Low-Latency Batched Stream Processing by Pre-Scheduling. IEEE Transactions on Parallel and Distributed Systems. 30(3). 710–722. 14 indexed citations
16.
Gu, Lin, Cheng Wang, Xiaolei Wang, Yanying Wang, & Qian Wang. (2013). [Variation characteristics of fine particulate matter PM2.5 concentration in three urban recreational forests in Hui Mountain of Wuxi City, Jiangsu Province of East China].. PubMed. 24(9). 2485–93. 6 indexed citations
17.
Gu, Lin, et al.. (2012). K Means of Cloud Computing: MapReduce, DVM, and Windows Azure. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 13–18. 2 indexed citations
18.
Ma, Zhiqiang & Lin Gu. (2010). The Limitation of MapReduce: A Probing Case and a Lightweight Solution. 68–73. 16 indexed citations
19.
Gu, Lin, et al.. (2010). Versatile Stack Management for Multitasking Sensor Networks. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 388–397. 3 indexed citations
20.
He, Tian, Lin Gu, Liqian Luo, et al.. (2006). An overview of data aggregation architecture for real-time tracking with sensor networks. International Parallel and Distributed Processing Symposium. 175–175. 17 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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