Chen Shan

dblp:26/10727 · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0001-6405-7813ORCID · reported

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

Artificial intelligence and machine learning · 2Software engineering, systems software and programming languages · 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%
Network and information security
1 paper
Blockchain and cryptocurrency security · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Blockchain and cryptocurrency security
consensus protocol
0.712023
Flexible Advancement in Asynchronous BFT Consensus · SOSP 2023
Distributed systems › consensus › fault-tolerant consensus
asynchronous consensus
0.712023
Flexible Advancement in Asynchronous BFT Consensus · SOSP 2023
Distributed systems › consensus
byzantine agreement
0.712023
Flexible Advancement in Asynchronous BFT Consensus · SOSP 2023
Distributed systems
consensus
0.712023
Flexible Advancement in Asynchronous BFT Consensus · SOSP 2023

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

asynchronous BFT protocol · 1.3
YearPublicationVenuePosition
2023 Flexible Advancement in Asynchronous BFT Consensus
abstract
Byzantine fault tolerant (BFT) consensus protocols are becoming an appealing solution to blockchains. As most blockchain systems are deployed on Wide Area Networks (WANs), with each node acting on behalf of its entity, partially synchronous BFT protocols that rely on network synchrony to elect a single leader can be ill-suited. In contrast, asynchronous protocols have no such timing assumptions. Existing asynchronous protocols confront challenges in terms of both flexibility and performance.
Shengyun Liu, Wenbo Xu 0002, Chen Shan, Xiaofeng Yan, Tianjing Xu, Bo Wang 0116, Lei Fan 0002, Fuxi Deng, Ying Yan 0002, Hui Zhang 0002
SOSP3
2013 A New Gene Expression Profiles Classifying Approach Based on Neighborhood Rough Set and Probabilistic Neural Networks Ensemble
Jiang Yun, Xie Guocheng, Chen Na, Chen Shan
ICONIP (2)4
2013 A New Hybrid Approach for Medical Image Intelligent Classifying Using Improved Wavelet Neural Network
Jiang Yun, Xie Guocheng, Chen Na, Chen Shan
ICONIP (2)4