Vasily Tarasov

40 papers receiving 794 citations

Peers

Vasily Tarasov
Comparison fields: 5 of 31
  • Computer Networks and Communications 765
  • Information Systems 528
  • Hardware and Architecture 201
  • Artificial Intelligence 119
  • Computer Vision and Pattern Recognition 37
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Countries citing papers authored by Vasily Tarasov

Since Specialization
Citations

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

Fields of papers citing papers by Vasily Tarasov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vasily Tarasov

This figure shows the co-authorship network connecting the top 25 collaborators of Vasily Tarasov. A scholar is included among the top collaborators of Vasily Tarasov 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 Vasily Tarasov. Vasily Tarasov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1
DupHunter: Flexible High-Performance Deduplication for Docker Registries.
14
2
Carving Perfect Layers out of Docker Images
14
3 24
4
Improving Docker Registry Design Based on Production Workload Analysis
27
5
Towards better understanding of black-box auto-tuning: a comparative analysis for storage systems
20
6 29
7
To FUSE or not to FUSE: performance of user-space file systems
52
8
On the performance variation in modern storage stacks
19
9 28
10
Using hints to improve inline block-layer deduplication
19
11
Filebench: A Flexible Framework for File System Benchmarking.
115
12 4
13
Improving I/O performance using virtual disk introspection
13
14 29
15
Virtual Machine Workloads: The Case for New {NAS} Benchmarks
15
16
Multi-dimensional workload analysis and synthesis for modern storage systems
3
17 32
18
Generating realistic datasets for deduplication analysis
62
19
Revisiting the storage stack in virtualized NAS environments
13
20 50

About Vasily Tarasov

Vasily Tarasov is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems, having authored 40 papers that have together received 836 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (36 papers), Cloud Computing and Resource Management (21 papers) and Caching and Content Delivery (17 papers). The work is most often cited by research in Computer Networks and Communications (765 citations), Hardware and Architecture (201 citations) and Information Systems (528 citations). Vasily Tarasov has collaborated with scholars based in United States, China and Kuwait. Frequent co-authors include Erez Zadok, Spencer Shepler, Dean Hildebrand, Geoff Kuenning, Lukas Rupprecht, Philip Shilane, Ali Anwar, Ali R. Butt, Mohamed Mohamed and Hadeel Albahar. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, ACM SIGOPS Operating Systems Review and Cluster Computing.

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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