Prasanna Ganesan
- Computer Networks and Communications top 2%
- Artificial Intelligence top 5%
- Information Systems top 2%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Héctor García-MolinaMayank BawaJennifer WidomTyson CondieBeverly YangKrishna P. GummadiQi SunGurmeet Singh Manku
- Topics
- Peer-to-Peer Network Technologies (11 papers)Caching and Content Delivery (8 papers)Data Management and Algorithms (6 papers)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Prasanna Ganesan
18 papers receiving 978 citations
Peers
Comparison fields: 5 of 64
- Computer Networks and Communications 606
- Artificial Intelligence 364
- Information Systems 344
- Signal Processing 207
- Computer Vision and Pattern Recognition 189
Countries citing papers authored by Prasanna Ganesan
This map shows the geographic impact of Prasanna Ganesan'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 Prasanna Ganesan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prasanna Ganesan more than expected).
Fields of papers citing papers by Prasanna Ganesan
This network shows the impact of papers produced by Prasanna Ganesan. 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 Prasanna Ganesan. The network helps show where Prasanna Ganesan may publish in the future.
Co-authorship network of co-authors of Prasanna Ganesan
This figure shows the co-authorship network connecting the top 25 collaborators of Prasanna Ganesan. A scholar is included among the top collaborators of Prasanna Ganesan 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 Prasanna Ganesan. Prasanna Ganesan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 5 | |
| 4 | Retrospective Study of sub clinical mastitis in Buffaloes | 4 |
| 5 | Two Can Keep a Secret: A Distributed Architecture for Secure Database Services | 134 |
| 6 | Efficient Queries in Peer-to-Peer Systems. | 0 |
| 7 | 3 | |
| 8 | 230 | |
| 9 | Data management in peer-to-peer systems | 6 |
| 10 | 47 | |
| 11 | Enabling Privacy for the Paranoids | 6 |
| 12 | 129 | |
| 13 | 160 | |
| 14 | 67 | |
| 15 | 14 | |
| 16 | 229 | |
| 17 | Distributed Balanced Tables: Not Making a Hash of it all | 6 |
| 18 | 31 | |
| 19 | Apocrypha: Making P2P Overlays Network-aware | 4 |
| 20 | A Case for Locally-Organized Peer-to-Peer Lookup Services | 2 |
About Prasanna Ganesan
Prasanna Ganesan is a scholar working on Signal Processing, Computer Networks and Communications and Software, having authored 21 papers that have together received 1.1k indexed citations. Recurring topics across this work include Peer-to-Peer Network Technologies (11 papers), Caching and Content Delivery (8 papers) and Data Management and Algorithms (6 papers). The work is most often cited by research in Computer Networks and Communications (606 citations), Signal Processing (207 citations) and Information Systems (344 citations). Prasanna Ganesan has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Héctor García-Molina, Mayank Bawa, Jennifer Widom, Tyson Condie, Beverly Yang, Krishna P. Gummadi, Qi Sun, Gurmeet Singh Manku, Rajeev Motwani and Utkarsh Srivastava. Their work appears in journals such as Future Generation Computer Systems, ACM SIGMOD Record and ACM Transactions on Information Systems.
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.