Sangheon Pack

5.6k citations
325 papers · 3.8k indexed · 1 hit paper · h-index 30

Sangheon Pack

302 papers receiving 3.7k citations

Hit Papers

WAVE: Popularity-based and collaborative in-network cachi...272201220262016202150100150200250

Peers

Sangheon Pack
Comparison fields: 5 of 88
  • Computer Networks and Communications 3.0k
  • Electrical and Electronic Engineering 2.3k
  • Health Information Management 81
  • Information Systems 351
  • Automotive Engineering 155
Replace Guowei Wu with:
Guowei Wu China
Weisen Shi Canada
Wali Ullah Khan Luxembourg
Muhammad Awais Javed Pakistan
Kai Lin China
Latif U. Khan South Korea
Khalil El‐Khatib Canada
Shalini Batra India
Sangheon Pack relative to Guowei Wu China Guowei Wu's profile →
Citations per field
00.5×5.8×
Guowei Wu · 1×
Citations per year

Countries citing papers authored by Sangheon Pack

Since Specialization
Citations

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

Fields of papers citing papers by Sangheon Pack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Sangheon Pack, 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 Sangheon Pack Line = papers co-authored together Sangheon Pack links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 20241
5 20242
6 20241
7 202312
8 202213
9 20222
10 202225
11 202129
12 202144
13 20213
14 20209
15 202047
16 202014
17 20192
18 20188
19 201841
20
WAVE: Popularity-based and collaborative in-network caching for content-oriented networksbreakdown →
2012272

About Sangheon Pack

Sangheon Pack is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems, Media Technology and Computer Science Applications, having authored 325 papers that have together received 3.8k indexed citations. Recurring topics across this work include Wireless Networks and Protocols (89 papers), IPv6, Mobility, Handover, Networks, Security (69 papers), Software-Defined Networks and 5G (55 papers), Advanced Wireless Network Optimization (53 papers), Caching and Content Delivery (45 papers), Mobile Ad Hoc Networks (44 papers), Cooperative Communication and Network Coding (39 papers) and Wireless Communication Networks Research (38 papers). The work is most often cited by research in Computer Networks and Communications (3.0k citations), Electrical and Electronic Engineering (2.3k citations), Health Information Management (81 citations), Information Systems (351 citations) and Automotive Engineering (155 citations). Sangheon Pack has collaborated with scholars based in South Korea, Canada and United States. Frequent co-authors include Haneul Ko, Yanghee Choi, Jaewook Lee, Dongeun Suh, Taekyoung Kwon, Victor C. M. Leung, Kunwoo Park, Kideok Cho, Ted Taekyoung Kwon and Xuemin Shen. Their work appears in journals such as IEEE Transactions on Vehicular Technology, IEEE Internet of Things Journal, IEEE Access, IEEE Communications Letters and IEEE Communications Magazine.

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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