Bin Dai

493 citations
15 papers · 202 · h-index 7

Impact in

    • Software-Defined Networks and 5G
    • IoT and Edge/Fog Computing
    • Caching and Content Delivery
    • Energy Efficient Wireless Sensor Networks
    • Wireless Networks and Protocols
    • Network Security and Intrusion Detection
    • Cloud Computing and Resource Management

Papers in

Bin Dai

13 papers receiving 193 citations

Peers

Bin Dai
Comparison fields: 5 of 33
  • Computer Networks and Communications 170
  • Information Systems 68
  • Electrical and Electronic Engineering 69
  • Urban Studies 7
  • Automotive Engineering 10
Replace Glaucio H. S. Carvalho with:
Glaucio H. S. Carvalho Canada
Sergio Beker Germany
Christina Thorpe Ireland
Jiong Lou China
Dongeun Suh South Korea
Abdelkader Outtagarts France
Ioannis Giannoulakis Greece
Shuping Peng Spain
Nadezhda Chukhno Finland
Leobino N. Sampaio Brazil
Bin Dai relative to Glaucio H. S. Carvalho Canada Glaucio H. S. Carvalho's profile →
Citations per field
00.5×1.5×2.3×
Glaucio H. S. Carvalho · 1×
Citations per year

Countries citing papers authored by Bin Dai

Since Specialization
Citations

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

Fields of papers citing papers by Bin Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Bin Dai, 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 Bin Dai Line = papers co-authored together Bin Dai links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201566
2 201732
3 202031
4 200823
5 202122
6 20226
7 20066
8 20204
9 20084
10
Sensor Placement in the Ultrasonic Positioning System
20143
11 20062
12 20152
13 20061
14 20240
15 20240

About Bin Dai

Bin Dai is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems, Sociology and Political Science and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 202 indexed citations. Recurring topics across this work include Software-Defined Networks and 5G (6 papers), Caching and Content Delivery (5 papers), Network Traffic and Congestion Control (5 papers), Peer-to-Peer Network Technologies (4 papers), IoT and Edge/Fog Computing (4 papers), Advanced Optical Network Technologies (2 papers), Cloud Computing and Resource Management (2 papers) and Energy Efficient Wireless Sensor Networks (2 papers). The work is most often cited by research in Computer Networks and Communications (170 citations), Information Systems (68 citations), Electrical and Electronic Engineering (69 citations), Urban Studies (7 citations) and Automotive Engineering (10 citations). Bin Dai has collaborated with scholars based in China, Canada and Japan. Frequent co-authors include Xu Guan, Yang Xu, Benxiong Huang, Furong Wang, Fanglin Xu, Fan Zhang, Xia Xie, Jianhua Ma, Jian Liu and Yijun Mo. Their work appears in journals such as IEEE Systems Journal, Computer Networks, Journal of Network and Computer Applications, Neurocomputing and Peer-to-Peer Networking and 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.

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