VLDB 2026 Research / reviewers in the wild / expert
Hexiang Pan
dblp:339/8942
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2025
0009-0004-6350-4887ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 3 · 1 first-author · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | NeurDB: On the Design and Implementation of an AI-powered Autonomous Database
Zhanhao Zhao, Shaofeng Cai, Hexiang Pan, Siqi Xiang, Naili Xing, Gang Chen 0001, Beng Chin Ooi, Yanyan Shen, Yuncheng Wu, Meihui Zhang 0001 |
CIDR | 4 |
| 2024 | FC: Adaptive Atomic Commit via Failure DetectionabstractAtomic commit protocols (ACPs) are crucial for ensuring transaction atomicity in distributed transaction processing. However, existing ACPs, designed specifically for fixed failure conditions, cannot work efficiently in modern environments, where failures such as node crashes and connection delays can happen anytime due to the use of commodity nodes and networks. In this paper, we propose FC, a novel and practical ACP that can adapt to changes in failure conditions. In essence, FC includes three dedicated protocols, which are specifically designed for three different failure conditions: (i) failure-free: no failure occurs, (ii) crash-failure: nodes might crash but there is no delayed connection, or (iii) network-failure: both crashed nodes and delayed connection can occur. During its operation, FC can monitor if any failure occurs and dynamically switch to the most suitable protocol, using a protocol selector, whose parameters are fine-tuned by reinforcement learning. Consequently, FC improves transaction performance and robustly ensures fault tolerance when crash failures and network failures occur. We conduct extensive experiments to evaluate FC with both YCSB and TPC-C benchmarks. The experimental results show that FC achieves up to 2.88x higher throughput and 3.76x lower latency than state-of-the-art ACPs, and its sustainable performance when integrated with two popular databases, namely MongoDB and PostgreSQL. Hexiang Pan, Quang-Trung Ta, Meihui Zhang 0001, Zhanhao Zhao, Yeow Meng Chee, Gang Chen 0001, Beng Chin Ooi |
ICDE | 1 |
| 2023 | VeriTxn: Verifiable Transactions for Cloud-Native Databases with Storage DisaggregationabstractCloud-native databases become increasingly popular while exposing to greater data security and correctness risks. Existing verifiable outsourced databases overlook either the correctness risk of transactions, or the disaggregation architecture: a key design consideration of cloud-native databases for performance and elasticity, or both. We present VeriTxn, a novel cloud-native database that efficiently provides verifiability of transaction correctness. VeriTxn relies on the trusted hardware (i.e., Intel SGX) to enable verifiable transaction processing. We build a page-structure cache in the trusted domain, where transactions can be verified with low, constant overhead. VeriTxn further optimizes the read-only transactions by exploiting disaggregation to fit the read-heavy workload in the cloud. We also integrate our proposal into MySQL, a popular open-source database. We conduct extensive experiments to compare VeriTxn against state-of-the-art verifiable databases and evaluate the performance of VeriTxn on MySQL. The results show that VeriTxn introduces tolerable performance degradation for verifiable transactions, while achieving up to 7.03× and 7.93× higher throughput than Litmus and LedgerDB, and its sustainable performance when integrated with MySQL. Zhanhao Zhao, Hexiang Pan, Gang Chen 0001, Xiaoyong Du 0001, Wei Lu 0015, Beng Chin Ooi |
Proc. ACM Manag. Data | 2 |