Shawn Shi

dblp:417/0873 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0001-4282-8549ORCID · reported

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

Databases, 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.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 50% Query processing and optimization · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 100%
Network and information security
1 paper
Blockchain and cryptocurrency security · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization › secure query processing › query result verification
authenticated data structures
0.912025
BPI: A Novel Efficient and Reliable Search Structure for Hybrid Storage Blockchain · Proc. ACM Manag. Data 2025
Information retrieval › indexing
search structures
0.912025
BPI: A Novel Efficient and Reliable Search Structure for Hybrid Storage Blockchain · Proc. ACM Manag. Data 2025
Storage systems › distributed storage
blockchain storage
0.912025
BPI: A Novel Efficient and Reliable Search Structure for Hybrid Storage Blockchain · Proc. ACM Manag. Data 2025
Storage systems › distributed storage
hybrid-storage blockchain
0.912025
BPI: A Novel Efficient and Reliable Search Structure for Hybrid Storage Blockchain · Proc. ACM Manag. Data 2025

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

articulated search · 2.6authenticated data structure · 1.7authenticated data structures · 0.9
YearPublicationVenuePosition
2025 BPI: A Novel Efficient and Reliable Search Structure for Hybrid Storage Blockchain
abstract
Hybrid storage solutions have emerged as potent strategies to alleviate the data storage bottlenecks prevalent in blockchain systems. These solutions harness off-chain Storage Services Providers (SP) in conjunction with Authenticated Data Structures (ADS) to ensure data integrity and accuracy. Despite these advancements, the reliance on centralized SPs raises concerns about query correctness, as the integrity of query results depends on the SPs' trustworthiness. Although ADS can verify the integrity of individual data points, they fall short of preventing SPs from omitting valid results. In this paper, we delineate the fundamental distinctions between data retrieval in blockchains and traditional database systems. Drawing upon these insights, we introduce the BPI framework, which employs a suite of validation models that ascertain the inclusion of all valid content in retrieval outcomes, with low overhead. We further present ''Articulated Search'', a query pattern specifically tailored for blockchain environments, which not only enhances retrieval efficiency but also substantially reduces costs during data user updates. Extensive experimental evaluations demonstrate that the BPI framework achieves outstanding scalability and performance in keyword searches within blockchain environments, surpassing EthMB+ and state-of-the-art search databases commonly used in mainstream hybrid storage blockchains (HSB). Notably, the Articulated Search pattern improves query performance by over three orders of magnitude, highlighting its potential as a transformative approach to blockchain query optimization.
Xinkui Zhao, Rengrong Xiong, Guanjie Cheng, Xinhao Jin, Shawn Shi, Xiubo Liang, Gongsheng Yuan, Xiaoye Miao, Jianwei Yin, Shuiguang Deng
Proc. ACM Manag. Data5