Long Cheng

2.7k total citations · 1 hit paper
108 papers, 1.6k citations indexed

About

Long Cheng is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Long Cheng has authored 108 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Networks and Communications, 50 papers in Information Systems and 27 papers in Artificial Intelligence. Recurrent topics in Long Cheng's work include Cloud Computing and Resource Management (32 papers), IoT and Edge/Fog Computing (23 papers) and Business Process Modeling and Analysis (15 papers). Long Cheng is often cited by papers focused on Cloud Computing and Resource Management (32 papers), IoT and Edge/Fog Computing (23 papers) and Business Process Modeling and Analysis (15 papers). Long Cheng collaborates with scholars based in China, Ireland and United States. Long Cheng's co-authors include Cong Liu, Qingzhi Liu, Ying Mao, John Murphy, Spyros Kotoulas, Xuan Chen, Jinwei Liu, Qingtian Zeng, Tomás Ward and Ying Wang and has published in prestigious journals such as PLoS ONE, Applied Energy and Expert Systems with Applications.

In The Last Decade

Long Cheng

101 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.

A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems

2020 214 citations Long Cheng, Cong Liu et al. IEEE Systems Journal profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Long Cheng China	23	835	735	369	254	161	108	1.6k
Fan Liang United States	16	1.2k 1.5×	766 1.0×	589 1.6×	464 1.8×	260 1.6×	46	2.2k
I‐Ling Yen United States	23	908 1.1×	971 1.3×	569 1.5×	131 0.5×	181 1.1×	198	1.8k
Shingo Yamaguchi Japan	14	545 0.7×	526 0.7×	388 1.1×	108 0.4×	173 1.1×	186	1.2k
Rajat Chaudhary India	20	995 1.2×	798 1.1×	448 1.2×	517 2.0×	147 0.9×	48	1.8k
Massimo Ficco Italy	27	1.4k 1.7×	981 1.3×	664 1.8×	340 1.3×	205 1.3×	98	2.2k
Farokh Bastani United States	23	809 1.0×	975 1.3×	526 1.4×	133 0.5×	174 1.1×	205	2.0k
William G. Hatcher United States	13	1.2k 1.5×	702 1.0×	583 1.6×	426 1.7×	284 1.8×	24	2.1k
Gulshan Kumar India	25	989 1.2×	792 1.1×	478 1.3×	377 1.5×	161 1.0×	125	1.7k
Andrei Tchernykh Mexico	22	992 1.2×	974 1.3×	398 1.1×	110 0.4×	140 0.9×	174	1.7k
Ismaeel Al Ridhawi Kuwait	27	1.4k 1.7×	808 1.1×	595 1.6×	657 2.6×	179 1.1×	63	2.2k

Countries citing papers authored by Long Cheng

Since Specialization

Citations

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

Fields of papers citing papers by Long Cheng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Long Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Long Cheng. A scholar is included among the top collaborators of Long Cheng 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 Long Cheng. Long Cheng 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

Saurabh, Nishant, et al.. (2025). Quantum Reinforcement Learning for QoS-Aware Real-Time Job Scheduling in Cloud Systems. IEEE Systems Journal. 19(2). 471–482.

Xu, H. Eric, Ao Zhang, Qingle Wang, et al.. (2025). Quantum Reinforcement Learning for real-time optimization in Electric Vehicle charging systems. Applied Energy. 383. 125279–125279. 8 indexed citations

Wen, Miaowen, et al.. (2025). Deep reinforcement learning for energy-efficient workflow scheduling in edge computing. Computer Networks. 274. 111790–111790.

Ning, Xin, et al.. (2024). DNN-Based Task Partitioning and Offloading in Edge-Cloud Collaboration Within Electric Vehicles. IEEE Transactions on Consumer Electronics. 71(2). 4100–4109. 1 indexed citations

Zhang, Ao, Qingzhi Liu, Jinwei Liu, & Long Cheng. (2024). CASA: cost-effective EV charging scheduling based on deep reinforcement learning. Neural Computing and Applications. 36(15). 8355–8370. 3 indexed citations

Cheng, Long, et al.. (2024). Advancements in Accelerating Deep Neural Network Inference on AIoT Devices: A Survey. IEEE Transactions on Sustainable Computing. 9(6). 830–847. 17 indexed citations

Liu, Cheng, Ying Wang, Tao Luo, et al.. (2023). Statistical Modeling of Soft Error Influence on Neural Networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 42(11). 4152–4163. 5 indexed citations

Liu, Jinwei, et al.. (2023). CuEMS: Deep reinforcement learning for community control of energy management systems in microgrids. Energy and Buildings. 304. 113865–113865. 7 indexed citations

Cheng, Long, Ying Wang, Rutvij H. Jhaveri, Qingle Wang, & Ying Mao. (2023). Toward Network-Aware Query Execution Systems in Large Datacenters. IEEE Transactions on Network and Service Management. 20(4). 4494–4504. 3 indexed citations

10.

Cheng, Long, et al.. (2023). A Deep Reinforcement Learning-Based Preemptive Approach for Cost-Aware Cloud Job Scheduling. IEEE Transactions on Sustainable Computing. 9(3). 422–432. 29 indexed citations

11.

Mao, Ying, et al.. (2022). Elastic Resource Management for Deep Learning Applications in a Container Cluster. IEEE Transactions on Cloud Computing. 11(2). 2204–2216. 12 indexed citations

12.

Cheng, Long, et al.. (2022). Cost-aware real-time job scheduling for hybrid cloud using deep reinforcement learning. Neural Computing and Applications. 34(21). 18579–18593. 19 indexed citations

13.

Mao, Ying, et al.. (2022). Differentiate Quality of Experience Scheduling for Deep Learning Inferences With Docker Containers in the Cloud. IEEE Transactions on Cloud Computing. 11(2). 1667–1677. 12 indexed citations

14.

Liu, Qingzhi, et al.. (2021). Deep Reinforcement Learning for Load-Balancing Aware Network Control in IoT Edge Systems. IEEE Transactions on Parallel and Distributed Systems. 33(6). 1491–1502. 62 indexed citations

15.

Wang, Ying, et al.. (2021). A Fast Precision Tuning Solution for Always-On DNN Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(5). 1236–1248. 5 indexed citations

16.

Huang, Yifeng, Long Cheng, Cong Liu, et al.. (2021). Deep Adversarial Imitation Reinforcement Learning for QoS-Aware Cloud Job Scheduling. IEEE Systems Journal. 16(3). 4232–4242. 38 indexed citations

17.

Liu, Jinwei, Haiying Shen, Hongmei Chi, et al.. (2020). A Low-Cost Multi-Failure Resilient Replication Scheme for High-Data Availability in Cloud Storage. IEEE/ACM Transactions on Networking. 29(4). 1436–1451. 29 indexed citations

18.

Cheng, Long, Boudewijn F. van Dongen, & Wil M. P. van der Aalst. (2019). Scalable Discovery of Hybrid Process Models in a Cloud Computing Environment. IEEE Transactions on Services Computing. 13(2). 368–380. 29 indexed citations

19.

Cheng, Long, Spyros Kotoulas, Tomás Ward, & Georgios Theodoropoulos. (2017). Improving the robustness and performance of parallel joins over distributed systems. Journal of Parallel and Distributed Computing. 109. 310–323. 8 indexed citations

20.

Cheng, Long, Ilias Tachmazidis, Spyros Kotoulas, & Grigoris Antoniou. (2017). Design and evaluation of small–large outer joins in cloud computing environments. Journal of Parallel and Distributed Computing. 110. 2–15. 24 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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