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Tadeusz Kopec

dblp:349/7009 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0001-4073-7598ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 94% Cloud and datacenter computing · 6%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › data reduction
data deduplication
0.712023
ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication · IEEE Trans. Parallel Distributed Syst. 2023
Storage systems
metadata management
0.712023
ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication · IEEE Trans. Parallel Distributed Syst. 2023
Storage systems
object storage
0.712023
ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication · IEEE Trans. Parallel Distributed Syst. 2023
Storage systems
storage reliability
0.712023
ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication · IEEE Trans. Parallel Distributed Syst. 2023
Storage systems › storage management
backup systems
0.212023
ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication · IEEE Trans. Parallel Distributed Syst. 2023
Cloud and datacenter computing
cloud storage
0.212023
ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication · IEEE Trans. Parallel Distributed Syst. 2023

Methods — techniques the papers use, named apart from their topics

distributed data structures · 0.7
YearPublicationVenuePosition
2023 ObjDedup: High-Throughput Object Storage Layer for Backup Systems With Block-Level Deduplication
abstract
The immense popularity of object storage is also affecting the market of backup. Not only have novel backup solutions emerged that utilize cloud-based object storage as backends, but also support for object storage interfaces is increasingly expected from traditional dedicated backup appliances. This latter trend especially concerns systems with data deduplication, as they can offer compelling gains in storage capacity and throughput. However, such systems have been designed for interfaces and workloads that are markedly different from those encountered in object storage. Notably, they expect data to be written in portions that are orders of magnitude longer than those in the novel object-storage-oriented backup applications. In this light, we contribute twofold. First, contrasting the properties of object storage interfaces with usage patterns from 686 commercial deployments of backup appliances, we identify specific issues an implementation of such an interface has to address to offer adequate performance in a backup system with block-level deduplication. In particular, we show that a major challenge is efficient metadata management. Second, we present distributed data structures and algorithms to handle object metadata in backup systems with block-level deduplication. Subsequently, we implement them as an object storage layer for our HYDRAstor backup system. In comparison to object storage without in-line deduplication, our solution achieves 1.8–3.93x higher write throughput. Compared to object storage on top of a state-of-the-art file-based backup system, it processes 5.26–11.34x more object put operations per time unit.
Andrzej Jackowski, Lukasz Slusarczyk, Krzysztof Lichota, Michal Welnicki, Rafal Wijata, Mateusz Kielar, Tadeusz Kopec, Cezary Dubnicki, Konrad Iwanicki
IEEE Trans. Parallel Distributed Syst.7