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Jinkun Geng

Publications and source records attributed to Jinkun Geng.

7 recordsLinked to original sources
arXiv2026

Probabilistic Fair Ordering of Events

A growing class of applications depends on fair ordering, where events that occur earlier should be processed before later ones. Providing such guarantees is difficult in practice because clock synchronization is inherently imperfect: events generated at different clients within a short time window may carry timestamps that cannot be reliably ordered. Rather than attempting to eliminate synchronization error, we embrace it and establish a probabilistically fair sequencing process. Tommy is a sequencer that uses a statistical model of per-clock synchronization error to compare noisy timestamps probabilistically. Although this enables ordering of two events, the probabilistic comparator is intransitive, making global ordering non-trivial. We address this challenge by mapping the sequencing problem to a classical ranking problem from social choice theory, which offers principled mechanisms for reasoning with intransitive comparisons. Using this formulation, Tommy produces a partial order of events, achieving significantly better fairness than a Spanner TrueTime-based baseline approach.

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arXiv2026

Practical One-Round-Trip BFT Replication

As Byzantine Fault Tolerant (BFT) protocols are increasingly adopted for user-facing applications such as payments and smart contracts, it is crucial that they provide low latency. To reduce latency, some BFT consensus protocols use a leaderless, speculative, fast path where clients broadcast requests directly to replicas, enabling end-to-end commit latency of two message delays ($2\Delta$). However, such a fast path is extremely fragile: concurrent requests can cause replicas to diverge when they receive requests in different orders, triggering costly recovery procedures. This paper presents Aspen, a leaderless speculative BFT protocol that handles concurrent requests while achieving near-optimal latency of $2\Delta + \epsilon$. The $\epsilon$ term is a short waiting delay introduced by Aspen's best effort ordering layer, which uses loosely synchronized clocks and network delay estimates to provide a tentative order. To make its fast path even more robust to intermittent divergence, Aspen adds extra replicas ($n = 3f + 2p + 1$) as well as novel recovery mechanisms that allow the system to tolerate divergence while preserving safety and performance. In experiments with geo-distributed replicas, Aspen reduces the median latency of requests by $1.1\times$--$3.8\times$ compared to state-of-the-art BFT protocols, while sustaining up to $0.75\times$ the peak throughput of throughput-optimized designs.

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arXiv2025

Beyond Lamport, Towards Probabilistic Fair Ordering

A growing class of applications demands \emph{fair ordering} of events, which ensures that events generated earlier are processed before later events. However, achieving such sequencing is challenging due to the inherent errors in clock synchronization: two events at two clients generated close together may have timestamps that cannot be compared confidently. We advocate for an approach that embraces, rather than eliminates, clock synchronization errors. Instead of attempting to remove the error from a timestamp, \systemname{}, our proposed system, leverages a statistical model to compare two noisy timestamps probabilistically by learning per-clock synchronization error distributions. Our preliminary statistical model computes the probability that one event precedes another by only relying on local clocks of clients. This serves as a foundation for a new relation: \emph{likely-happened-before} denoted by $\xrightarrow{p}$ where $p$ represents the probability that an event happened before another. The $\xrightarrow{p}$ relation provides a basis for ordering multiple events which are otherwise considered \emph{concurrent} by Lamport's \emph{happened-before} ($\rightarrow$) relation. We highlight various related challenges including the intransitivity of the $\xrightarrow{p}$ relation as opposed to the transitive $\rightarrow$ relation. We outline several research directions: online fair sequencing, stochastically fair total ordering, and handling byzantine clients.

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arXiv2025

Tiga: Accelerating Geo-Distributed Transactions with Synchronized Clocks [Technical Report]

This paper presents Tiga, a new design for geo-replicated and scalable transactional databases such as Google Spanner. Tiga aims to commit transactions within 1 wide-area roundtrip time, or 1 WRTT, for a wide range of scenarios, while maintaining high throughput with minimal computational overhead. Tiga consolidates concurrency control and consensus, completing both strictly serializable execution and consistent replication in a single round. It uses synchronized clocks to proactively order transactions by assigning each a future timestamp at submission. In most cases, transactions arrive at servers before their future timestamps and are serialized according to the designated timestamp, requiring 1 WRTT to commit. In rare cases, transactions are delayed and proactive ordering fails, in which case Tiga falls back to a slow path, committing in 1.5--2 WRTTs. Compared to state-of-the-art solutions, Tiga can commit more transactions at 1-WRTT latency, and incurs much less throughput overhead. Evaluation results show that Tiga outperforms all baselines, achieving 1.3--7.2$\times$ higher throughput and 1.4--4.6$\times$ lower latency. Tiga is open-sourced at https://github.com/New-Consensus-Concurrency-Control/Tiga.

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arXiv2025

Design and Implementation of a Scalable Financial Exchange in the Public Cloud

Financial exchanges are migrating to the cloud, but the best-effort nature of the public cloud is at odds with the stringent latency requirements of exchanges. We present Jasper, a system for meeting the networking requirements of financial exchanges on the public cloud. Jasper uses an overlay tree to scalably multicast market data from an exchange to ~1000 participants with low latency (250 microseconds) and a 1-microsecond difference in data reception time between any two participants. Jasper reuses the same tree for scalable inbound communication (participants to exchange), augmenting it with order pacing and a new priority queue, Limit Order Queue (LOQ), to efficiently handle bursts of market orders. Jasper achieves better scalability and 50% lower latency than the AWS multicast service. During bursty market activity, LOQ nearly doubles the order processing rate.

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arXiv2023

Nezha: Deployable and High-Performance Consensus Using Synchronized Clocks

This paper presents a high-performance consensus protocol, Nezha, which can be deployed by cloud tenants without any support from their cloud provider. Nezha bridges the gap between protocols such as Multi-Paxos and Raft, which can be readily deployed and protocols such as NOPaxos and Speculative Paxos, that provide better performance, but require access to technologies such as programmable switches and in-network prioritization, which cloud tenants do not have. Nezha uses a new multicast primitive called deadline-ordered multicast (DOM). DOM uses high-accuracy software clock synchronization to synchronize sender and receiver clocks. Senders tag messages with deadlines in synchronized time; receivers process messages in deadline order, on or after their deadline. We compare Nezha with Multi-Paxos, Fast Paxos, Raft, a NOPaxos version we optimized for the cloud, and 2 recent protocols, Domino and TOQ-EPaxos, that use synchronized clocks. In throughput, Nezha outperforms all baselines by a median of 5.4x (range: 1.9-20.9x). In latency, Nezha outperforms five baselines by a median of 2.3x (range: 1.3-4.0x), with one exception: it sacrifices 33% latency compared with our optimized NOPaxos in one test. We also prototype two applications, a key-value store and a fair-access stock exchange, on top of Nezha to show that Nezha only modestly reduces their performance relative to an unreplicated system. Nezha is available at https://github.com/Steamgjk/Nezha.

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