Ching‐Hsien Hsu

8.7k total citations · 2 hit papers
261 papers, 5.8k citations indexed

About

Ching‐Hsien Hsu is a scholar working on Computer Networks and Communications, Information Systems and Electrical and Electronic Engineering. According to data from OpenAlex, Ching‐Hsien Hsu has authored 261 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 179 papers in Computer Networks and Communications, 109 papers in Information Systems and 44 papers in Electrical and Electronic Engineering. Recurrent topics in Ching‐Hsien Hsu's work include IoT and Edge/Fog Computing (73 papers), Cloud Computing and Resource Management (66 papers) and Distributed and Parallel Computing Systems (49 papers). Ching‐Hsien Hsu is often cited by papers focused on IoT and Edge/Fog Computing (73 papers), Cloud Computing and Resource Management (66 papers) and Distributed and Parallel Computing Systems (49 papers). Ching‐Hsien Hsu collaborates with scholars based in Taiwan, China and United States. Ching‐Hsien Hsu's co-authors include Shangguang Wang, Gunasekaran Manogaran, Fangchun Yang, Yali Zhao, Yeh‐Ching Chung, Jie Yuan, Ao Zhou, Brij B. Gupta, Hao Wu and Priyan Malarvizhi Kumar and has published in prestigious journals such as Scientific Reports, The Journal of Organic Chemistry and IEEE Access.

In The Last Decade

Ching‐Hsien Hsu

249 papers receiving 5.6k citations

Hit Papers

Edge server placement in mobile edge computing 2018 2026 2020 2023 2018 2021 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ching‐Hsien Hsu Taiwan 40 3.2k 2.3k 1.2k 1.1k 674 261 5.8k
Tiago M. Fernández‐Caramés Spain 37 2.2k 0.7× 2.1k 0.9× 750 0.6× 1.0k 0.9× 923 1.4× 103 5.6k
Gang Sun China 45 3.2k 1.0× 1.8k 0.8× 1.2k 1.1× 2.1k 1.8× 506 0.8× 292 6.1k
Pradip Kumar Sharma United Kingdom 36 2.6k 0.8× 2.4k 1.1× 1.4k 1.2× 926 0.8× 521 0.8× 134 5.2k
Honghao Gao China 44 2.6k 0.8× 1.9k 0.8× 1.9k 1.6× 1.0k 0.9× 1.0k 1.5× 248 6.0k
Deepak Puthal Australia 38 3.2k 1.0× 2.3k 1.0× 1.1k 1.0× 1.4k 1.2× 527 0.8× 178 5.2k
Wanchun Dou China 46 3.8k 1.2× 3.1k 1.3× 2.3k 2.0× 1.3k 1.1× 927 1.4× 315 7.3k
Chunsheng Zhu China 37 3.1k 1.0× 1.1k 0.5× 1.1k 0.9× 1.5k 1.4× 459 0.7× 177 4.9k
Moayad Aloqaily United Arab Emirates 43 3.2k 1.0× 2.4k 1.0× 2.0k 1.7× 2.0k 1.8× 575 0.9× 192 6.5k
Mohammad Shojafar United Kingdom 44 4.4k 1.4× 2.5k 1.1× 1.2k 1.1× 2.0k 1.8× 577 0.9× 204 6.5k
Paula Fraga‐Lamas Spain 34 2.1k 0.6× 2.0k 0.9× 633 0.5× 886 0.8× 866 1.3× 89 5.1k

Countries citing papers authored by Ching‐Hsien Hsu

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐Hsien Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching‐Hsien Hsu. 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 Ching‐Hsien Hsu. The network helps show where Ching‐Hsien Hsu may publish in the future.

Co-authorship network of co-authors of Ching‐Hsien Hsu

This figure shows the co-authorship network connecting the top 25 collaborators of Ching‐Hsien Hsu. A scholar is included among the top collaborators of Ching‐Hsien Hsu 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 Ching‐Hsien Hsu. Ching‐Hsien Hsu 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.
Xiao, Yingyuan, et al.. (2024). A graph attention network with contrastive learning for temporal review-based recommendations. Applied Soft Computing. 159. 111652–111652. 6 indexed citations
2.
Hsu, Ching‐Hsien, et al.. (2023). Federated Feature Concatenate Method for Heterogeneous Computing in Federated Learning. Computers, materials & continua/Computers, materials & continua (Print). 75(1). 351–371. 1 indexed citations
3.
Hsu, Ching‐Hsien, et al.. (2023). Big Data Intelligence and Computing. Lecture notes in computer science. 2 indexed citations
4.
Alasmary, Waleed, et al.. (2022). Balanced Energy-Aware and Fault-Tolerant Data Center Scheduling. Sensors. 22(4). 1482–1482. 15 indexed citations
5.
Zhang, Peiying, Yu Su, Jingjing Wang, et al.. (2022). Reinforcement Learning Assisted Bandwidth Aware Virtual Network Resource Allocation. IEEE Transactions on Network and Service Management. 19(4). 4111–4123. 24 indexed citations
6.
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
7.
Elgendy, Ibrahim A., Weizhe Zhang, Chuanyi Liu, & Ching‐Hsien Hsu. (2021). Correction to “An Efficient and Secured Framework For Mobile Cloud Computing”. IEEE Transactions on Cloud Computing. 9(2). 844–844. 1 indexed citations
8.
Jha, Srinidhi, et al.. (2021). A methodological framework for extreme climate risk assessment integrating satellite and location based data sets in intelligent systems. International Journal of Intelligent Systems. 37(12). 10268–10288. 3 indexed citations
9.
Khan, Muhammad Attique, et al.. (2021). A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification. International Journal of Intelligent Systems. 37(12). 10621–10649. 91 indexed citations
10.
Gupta, Koyel Datta, et al.. (2021). A Novel Lightweight Deep Learning-Based Histopathological Image Classification Model for IoMT. Neural Processing Letters. 55(1). 205–228. 35 indexed citations
11.
Wu, Wentai, et al.. (2019). A Power Consumption Model for Cloud Servers Based on Elman Neural Network. IEEE Transactions on Cloud Computing. 9(4). 1268–1277. 29 indexed citations
12.
Elgendy, Ibrahim A., et al.. (2018). An Efficient and Secured Framework for Mobile Cloud Computing. IEEE Transactions on Cloud Computing. 9(1). 79–87. 56 indexed citations
13.
Sundarasekar, Revathi, Gunasekaran Manogaran, Priyan Malarvizhi Kumar, et al.. (2018). Internet of Things with Maximal Overlap Discrete Wavelet Transform for Remote Health Monitoring of Abnormal ECG Signals. Journal of Medical Systems. 42(11). 228–228. 51 indexed citations
14.
Yang, Chao‐Tung, et al.. (2017). Implementation of a Virtualized Cluster Computing Environment. 網際網路技術學刊. 18(5). 1103–1115. 1 indexed citations
15.
Lin, Weiwei, Wentai Wu, Haoyu Wang, James Z. Wang, & Ching‐Hsien Hsu. (2016). Experimental and quantitative analysis of server power model for cloud data centers. Future Generation Computer Systems. 86. 940–950. 32 indexed citations
16.
Zhang, Weizhe, Hucheng Xie, & Ching‐Hsien Hsu. (2015). Automatic Memory Control of Multiple Virtual Machines on a Consolidated Server. IEEE Transactions on Cloud Computing. 5(1). 2–14. 33 indexed citations
17.
Hung, Shih‐Hao, et al.. (2014). A framework of cloud-based virtual phones for secure intelligent information management. International Journal of Information Management. 34(3). 329–335. 12 indexed citations
18.
Hsu, Ching‐Hsien, Laurence T. Yang, Jong Hyuk Park, & Sang-Soo Yeo. (2010). Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part II. 2 indexed citations
19.
Hsu, Ching‐Hsien, et al.. (2010). An Efficient Peer Collaboration Strategy for Optimizing P2P Services in BitTorrent-Like File Sharing Networks. 網際網路技術學刊. 11(1). 79–88.
20.
Li, Kuan‐Ching, et al.. (2006). Towards Design of a File Location Selection System in Grid Environments. 2. 250–256. 1 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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