Demo Data from EDBT 2026 / reviewers in the wild / expert
Hua Guo 0004
dblp:12/5941-4
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2021
0009-0003-4410-0636ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 first-author · 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% | |
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
concurrency control |
0.5 | 1 | 2021 | Lock Violation for Fault-tolerant Distributed Database System* · ICDE 2021 |
Distributed systems
consensus |
0.5 | 1 | 2021 | Lock Violation for Fault-tolerant Distributed Database System* · ICDE 2021 |
Distributed systems › distributed database
distributed transactions |
0.5 | 1 | 2021 | Lock Violation for Fault-tolerant Distributed Database System* · ICDE 2021 |
Distributed systems › replication
geo-replication |
0.5 | 1 | 2021 | Lock Violation for Fault-tolerant Distributed Database System* · ICDE 2021 |
Methods — techniques the papers use, named apart from their topics
speculative execution · 1.0early lock release · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Lock Violation for Fault-tolerant Distributed Database System*abstractModern distributed database systems scale horizontally by partitioning their data across a large number of nodes. Most such systems build their transactional layers on a replication layer, employing a consensus protocol to ensure data consistency to achieve fault tolerance. Synchronization among replicated state machines thus becomes a significant overhead of transaction processing. Without careful design, synchronization could amplify transactions' lock duration and impair the system's scalability. Speculative techniques, such as Controlled Lock Violation (CLV) and Early Lock Release (ELR), prove useful in shortening lock's critical path and boosting transaction processing performance. To use these techniques to optimize geo-replicated distributed databases(GDDB) is an intuitive idea. This paper shows that a naive application of speculation is often unhelpful in a distributed environment. Instead, we introduce Distributed Lock Violation (DLV), a specialized speculative technique for geo-replicated distributed databases. DLV can achieve good performance without incurring severe side effects. Hua Guo 0004, Xuan Zhou 0001, Le Cai |
ICDE | 1 |