VLDB 2026 Research / reviewers in the wild / expert
Ansh Khanna
dblp:317/1458
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 · 93% Parallel and multicore computing · 7% | |
| Databases, data mining, and information retrieval
1 paper |
Transaction processing and concurrency control · 100% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
consensus |
0.6 | 1 | 2022 | Rolis: a software approach to efficiently replicating multi-core transactions · EuroSys 2022 |
Distributed systems › consensus
paxos |
0.6 | 1 | 2022 | Rolis: a software approach to efficiently replicating multi-core transactions · EuroSys 2022 |
Distributed systems
replication |
0.6 | 1 | 2022 | Rolis: a software approach to efficiently replicating multi-core transactions · EuroSys 2022 |
Distributed systems › replication
state machine replication |
0.6 | 1 | 2022 | Rolis: a software approach to efficiently replicating multi-core transactions · EuroSys 2022 |
Methods — techniques the papers use, named apart from their topics
paxos · 1.1execute-replicate-replay · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Rolis: a software approach to efficiently replicating multi-core transactionsabstractThis paper presents Rolis, a new speedy and fault-tolerant replicated multi-core transactional database system. Rolis's aim is to mask the high cost of replication by ensuring that cores are always doing useful work and not waiting for each other or for other replicas. Rolis achieves this by not mixing the multi-core concurrency control with multi-machine replication, as is traditionally done by systems that use Paxos to replicate the transaction commit protocol. Instead, Rolis takes an "execute-replicate-replay" approach. Rolis first speculatively executes the transaction on the leader machine, and then replicates the per-thread transaction log to the followers using a novel protocol that leverages independent Paxos instances to avoid coordination, while still allowing followers to safely replay. The execution, replication, and replay are carefully designed to be scalable and have nearly zero coordination overhead across cores. Our evaluation shows that Rolis can achieve 1.03M TPS (transactions per second) on the TPC-C workload, using a 3-replica setup where each server has 32 cores. This throughput result is orders of magnitude higher than traditional software approaches we tested (e.g., 2PL), and is comparable to state-of-the-art, fault-tolerant, in-memory storage systems built using kernel bypass and advanced networking hardware, even though Rolis runs on commodity machines. Weihai Shen, Ansh Khanna, Sebastian Angel, Siddhartha Sen 0001, Shuai Mu 0001 |
EuroSys | 2 |