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Cunyang Liu

dblp:381/6160 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2026
—ORCID · none

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

Computer networks · 1 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 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
2 papers
Distributed systems · 92% Storage systems · 8%
Network and information security
2 papers
Blockchain and cryptocurrency security · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems
consensus
1.122026
SharDAG: Scaling DAG-Based Blockchains Via Adaptive Sharding · ICDE 2024
JiangZiya: Dependency-aware Smart Contract Migration for Scalable Sharded Blockchains · INFOCOM 2026
Blockchain and cryptocurrency security
smart contract
1.012026
JiangZiya: Dependency-aware Smart Contract Migration for Scalable Sharded Blockchains · INFOCOM 2026
Distributed systems › blockchain
sharded blockchain
1.012026
JiangZiya: Dependency-aware Smart Contract Migration for Scalable Sharded Blockchains · INFOCOM 2026
Blockchain and cryptocurrency security › blockchain architecture
DAG-based blockchain
0.812024
SharDAG: Scaling DAG-Based Blockchains Via Adaptive Sharding · ICDE 2024
Distributed systems › fault tolerance
byzantine fault tolerance
0.812024
SharDAG: Scaling DAG-Based Blockchains Via Adaptive Sharding · ICDE 2024

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

sharding · 3.5dependency analysis · 2.0avatar account caching · 1.5
YearPublicationVenuePosition
2026 JiangZiya: Dependency-aware Smart Contract Migration for Scalable Sharded Blockchains
Cunyang Liu, Jiang Xiao 0001, Ru Cheng, Hai Jin 0001
INFOCOM1
2024 SharDAG: Scaling DAG-Based Blockchains Via Adaptive Sharding
abstract
Directed Acyclic Graph (DAG)-based blockchain (a.k.a distributed ledger) has become prevalent for supporting highly concurrent applications. Its inherent parallel data structure accelerates block generation significantly, shifting the bottleneck from performance to storage scalability. An intuitive solution is to apply state sharding that divides the entire ledger (i.e., transactions and states) into multiple shards. While each node only stores proportional transactions, it suffers from the challenges of storing and ensuring the processing consistency of cross-shard transactions. In this paper, we propose SharDAG, a new mechanism that leverages adaptive sharding for DAG-based blockchains to achieve high performance and strong consistency. The key idea of SharDAG is to exploit unique characteristics - silent assets - and design a lightweight processing mechanism based on avatar account caching. Furthermore, we design a Byzantine resilient cross-shard verification mechanism with a theoretically optimal number of participating nodes, which guarantees the consistency and security of avatar account aggregation. Our comprehensive evaluations on real-world workloads demonstrate that SharDAG presents up to 3.8 x throughput improvement compared to the state-of-the-art and reduces the storage overhead of cross-shard transactions.
Jiang Xiao 0001, Cunyang Liu, Bo Li 0001, Baochun Li, Hai Jin 0001
ICDE3