Long Cheng

2.7k citations
108 papers · 1.6k indexed · 1 hit paper · h-index 23
Topics
Cloud Computing and Resource Management (32 papers)IoT and Edge/Fog Computing (23 papers)Business Process Modeling and Analysis (15 papers)

In The Last Decade

Long Cheng

101 papers receiving 1.5k citations

Hit Papers

A WOA-Based Optimization Approach for Task Scheduling in ...2020202620222024202050100150200

Peers

Long Cheng
Comparison fields: 5 of 96
  • Computer Networks and Communications 835
  • Information Systems 735
  • Artificial Intelligence 369
  • Electrical and Electronic Engineering 254
  • Computer Vision and Pattern Recognition 161
Replace William J. Knottenbelt with:
William J. Knottenbelt United Kingdom
I‐Ling Yen United States
Fan Liang United States
Farokh Bastani United States
Rajat Chaudhary India
Maria Kihl Sweden
Gulshan Kumar India
P. Dhavachelvan India
Patrizio Pelliccione Italy
Cesare Stefanelli Italy
Long Cheng relative to William J. Knottenbelt United Kingdom William J. Knottenbelt's profile →
Citations per field
00.5×
William J. Knottenbelt · 1×
Citations per year

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

20 of 20 papers shown
#WorkIndexed citations
1 0
2 8
3 0
4 1
5 3
6 17
7 5
8 7
9 3
10 29
11 12
12 19
13 12
14 62
15 5
16 38
17 29
18 29
19 8
20 24

About Long Cheng

Long Cheng is a scholar working on Computer Networks and Communications, Information Systems and Management Information Systems, having authored 108 papers that have together received 1.6k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (32 papers), IoT and Edge/Fog Computing (23 papers) and Business Process Modeling and Analysis (15 papers). The work is most often cited by research in Computer Networks and Communications (835 citations), Information Systems (735 citations) and Management Information Systems (143 citations). Long Cheng has collaborated with scholars based in China, Ireland and United States. Frequent co-authors include Cong Liu, Qingzhi Liu, Ying Mao, John Murphy, Spyros Kotoulas, Xuan Chen, Jinwei Liu, Qingtian Zeng, Tomás Ward and Ying Wang. Their work appears in journals such as PLoS ONE, Applied Energy and Expert Systems with Applications.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026