Tomasz Zurkowski

dblp:158/0908 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-2600-0431ORCID · reported

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

Security and privacy · 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
Distributed systems · 100%

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

TopicWeightPapersLastEvidence papers
Distributed systems
consensus
0.512021
Recovery Algorithms for Paxos-Based State Machine Replication · IEEE Trans. Dependable Secur. Comput. 2021
Distributed systems
fault tolerance
0.512021
Recovery Algorithms for Paxos-Based State Machine Replication · IEEE Trans. Dependable Secur. Comput. 2021
Distributed systems › consensus
paxos
0.512021
Recovery Algorithms for Paxos-Based State Machine Replication · IEEE Trans. Dependable Secur. Comput. 2021
Distributed systems
replication
0.512021
Recovery Algorithms for Paxos-Based State Machine Replication · IEEE Trans. Dependable Secur. Comput. 2021
Distributed systems › replication
state machine replication
0.512021
Recovery Algorithms for Paxos-Based State Machine Replication · IEEE Trans. Dependable Secur. Comput. 2021
Distributed systems › fault tolerance › failure recovery
state restoration
0.512021
Recovery Algorithms for Paxos-Based State Machine Replication · IEEE Trans. Dependable Secur. Comput. 2021

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

state recovery algorithms · 0.5
YearPublicationVenuePosition
2021 Recovery Algorithms for Paxos-Based State Machine Replication
abstract
In this article, we propose and evaluate three different state recovery algorithms aimed for Paxos-one of the most popular distributed agreement protocols. Paxos is commonly used to maintain consistency among state machine replicas despite of failures of processes. The first algorithm, that we call FullSS, originates from the original Paxos and requires that the system frequently uses stable storage during regular (non-faulty) execution. The other two state recovery algorithms, ViewSS and EpochSS, scarcely require access to stable storage, and the recovering process must do much less work to restore its lost state, and to catch up on the current state of the system. We thoroughly analyze and compare the behavior of the three algorithms during state recovery and also during regular, non-faulty system execution, under various workloads (e.g., causing the network or CPU saturation). The experimental results show that by using ViewSS and EpochSS, we can significantly improve process recovery with respect to the original Paxos, if only it can be assumed that at any time a majority of replicas are up running (excluding those replicas that are just recovering). Moreover, these algorithms do not impact the performance of Paxos during regular (non-faulty) operation. However, FullSS is the only choice out of the three, if the system must tolerate catastrophic failures.
Jan Z. Konczak, Pawel T. Wojciechowski, Tomasz Zurkowski, André Schiper
IEEE Trans. Dependable Secur. Comput.4