Kiran‐Kumar Muniswamy‐Reddy

1.6k citations
22 papers · 1.0k indexed · h-index 15

Kiran‐Kumar Muniswamy‐Reddy

22 papers receiving 946 citations

Peers

Kiran‐Kumar Muniswamy‐Reddy
Comparison fields: 5 of 48
  • Information Systems and Management 599
  • Computer Networks and Communications 768
  • Information Systems 589
  • Signal Processing 135
  • Management Science and Operations Research 117
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Citations per year

Countries citing papers authored by Kiran‐Kumar Muniswamy‐Reddy

Since Specialization
Citations

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

Fields of papers citing papers by Kiran‐Kumar Muniswamy‐Reddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kiran‐Kumar Muniswamy‐Reddy. 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 Kiran‐Kumar Muniswamy‐Reddy. The network helps show where Kiran‐Kumar Muniswamy‐Reddy may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Kiran‐Kumar Muniswamy‐Reddy, 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 Kiran‐Kumar Muniswamy‐Reddy Line = papers co-authored together Kiran‐Kumar Muniswamy‐Reddy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201330
2 20123
3 201233
4
Compressing Provenance Graphs.
201122
5 20112
6 2010100
7
Foundations for provenance-aware systems
201010
8
Layering in provenance systems
2009104
9
Making a cloud provenance-aware
200933
10 200919
11
Layering in Provenance-Aware Storage Systems
20088
12
Choosing a Data Model and Query Language for Provenance
200843
13 200710
14 200729
15
Deciding How to Store Provenance
20063
16
Provenance-aware storage systems
2006354
17 200654
18
A versatile and user-oriented versioning file system
200475
19
Reducing Storage Management Costs via Informed User-Based Policies
200417
20
VERSIONFS A Versatile and User-Oriented Versioning File System
20035

About Kiran‐Kumar Muniswamy‐Reddy

Kiran‐Kumar Muniswamy‐Reddy is a scholar working on Information Systems and Management, Computer Networks and Communications and Software, having authored 22 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (16 papers), Scientific Computing and Data Management (14 papers), Distributed and Parallel Computing Systems (12 papers), Software System Performance and Reliability (3 papers), Cloud Computing and Resource Management (3 papers), Software Reliability and Analysis Research (2 papers), Software Engineering Research (2 papers) and Parallel Computing and Optimization Techniques (2 papers). The work is most often cited by research in Information Systems and Management (599 citations), Computer Networks and Communications (768 citations) and Information Systems (589 citations). Kiran‐Kumar Muniswamy‐Reddy has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Margo Seltzer, David A. Holland, Uri Braun, Peter Macko, Diana MacLean, Charles P. Wright, Erez Zadok, Bor‐Rong Chen, Matt Welsh and Darrell D. E. Long. Their work appears in journals such as ACM SIGOPS Operating Systems Review, Concurrency and Computation Practice and Experience and ACM Transactions on Storage.

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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