Jun Song

512 citations
43 papers · 373 · h-index 11

Impact in

    • IoT and Edge/Fog Computing
    • Network Security and Intrusion Detection
    • Opportunistic and Delay-Tolerant Networks
    • Mobile Ad Hoc Networks
    • Cloud Computing and Resource Management
    • Blockchain Technology Applications and Security

Papers in

Jun Song

42 papers receiving 360 citations

Peers

Jun Song
Comparison fields: 5 of 60
  • Computer Networks and Communications 196
  • Information Systems 153
  • Signal Processing 62
  • Software 20
  • Computer Vision and Pattern Recognition 53
Replace Jason Lu with:
Jason Lu United States
Ahthasham Sajid Pakistan
Sanjay Kumar India
Sadeeq Jan Pakistan
Khalid Aloufi Saudi Arabia
Gauhar Ali Saudi Arabia
Mohammed Q. Shatnawi Jordan
Zhonglin Liu China
Kai Cheng China
Mian Muhammad Awais Pakistan
Jun Song relative to Jason Lu United States Jason Lu's profile →
Citations per field
00.5×4.8×
Jason Lu · 1×
Citations per year

Countries citing papers authored by Jun Song

Since Specialization
Citations

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

Fields of papers citing papers by Jun Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Song, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Song Line = papers co-authored together Jun Song links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201869
2 201640
3 201722
4 201421
5 200720
6 201719
7 201717
8 201515
9 201915
10 202014
11 200712
12 20229
13 20169
14 20159
15 20188
16 20117
17 20206
18 20116
19 20145
20 20184

About Jun Song

Jun Song is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 43 papers that have together received 373 indexed citations. Recurring topics across this work include Vehicular Ad Hoc Networks (VANETs) (8 papers), Network Security and Intrusion Detection (6 papers), Advanced Authentication Protocols Security (4 papers), Advanced Steganography and Watermarking Techniques (4 papers), Mobile Ad Hoc Networks (4 papers), Advanced Malware Detection Techniques (4 papers), Opportunistic and Delay-Tolerant Networks (4 papers) and Caching and Content Delivery (4 papers). The work is most often cited by research in Computer Networks and Communications (196 citations), Information Systems (153 citations), Signal Processing (62 citations), Software (20 citations) and Computer Vision and Pattern Recognition (53 citations). Jun Song has collaborated with scholars based in China, Canada and United Kingdom. Frequent co-authors include Rajiv Ranjan, Lizhe Wang, Deepak Puthal, Huanguo Zhang, Prem Prakash Jayaraman, Fan Yang, Albert Y. Zomaya, Sambit Kumar Mishra, Bibhudatta Sahoo and Jianping Pan. Their work appears in journals such as Future Generation Computer Systems, China Communications, Scientific Reports, Sustainable Computing Informatics and Systems and Tsinghua Science & Technology.

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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