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Zijian Qin

dblp:281/5239 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0006-8728-0501ORCID · 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
Distributed systems · 100%

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

TopicWeightPapersLastEvidence papers
Distributed systems
consensus
1.012026
Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation · EuroSys 2026
Distributed systems › consensus
geo-distributed consensus
1.012026
Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation · EuroSys 2026
Distributed systems
replication
1.012026
Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation · EuroSys 2026
Distributed systems › replication
state machine replication
1.012026
Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation · EuroSys 2026
Distributed systems › fault tolerance › failure models
crash failures
0.312026
Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation · EuroSys 2026
Distributed systems
fault tolerance
0.312026
Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation · EuroSys 2026

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

counterfactual evaluation · 1.0
YearPublicationVenuePosition
2026 Avicenna: Masking Slowdowns in Replicated State Machines with Counterfactual Evaluation
abstract
Geo-distributed replicated state machines (RSMs) are at the heart of many production distributed systems, offering linearizability and fault tolerance via consensus protocols. Most existing protocols target crash fault tolerance, however, and are vulnerable to fail-slow faults, where a single slow replica can significantly degrade system latency. Existing protocols that tolerate fail-slow faults do so with much higher normal-case latency in geo-distributed settings.
Christopher Hodsdon, Zijian Qin, Khiem Ngo, Siddhartha Sen 0001, Ethan Katz-Bassett, Wyatt Lloyd
EuroSys2