arXiv subjects

Ziqian Cheng

Publications and source records attributed to Ziqian Cheng.

3 recordsLinked to original sources

arXiv2026

CD-Raft: Reducing the Latency of Distributed Consensus in Cross-Domain Sites

Today's massive AI computation loads push heavy data synchronization across sites, i.e., nodes in data centers. Any reduction in such consensus latency can significantly improve the overall performance of desired systems. This consensus challenge explosively peaks at cross-domain sites. In this paper, we proposed CD-Raft to address the cross-domain latency challenge, an optimized Raft protocol for strong consistency in cross-domain sites. CD-Raft can significantly reduce consensus latency by optimizing cross-domain round-trip time (RTT) for reads and writes, as well as carefully positioning the leader node. We verified the correctness of CD-Raft in a formal specification using the TLA+ specification, guaranteeing the strong consistency across sites. We have prototyped CD-Raft and evaluated it using the YCSB benchmark. Empirical results show that compared to the classic Raft, CD-Raft reduces the average latency by 32.90% and (99th percentile) tail latency by 49.24% for renown traces across multiple sites.

cs.DC↗

arXiv2026

Nezha: A Key-Value Separated Distributed Store with Optimized Raft Integration

Distributed key-value stores are widely adopted to support elastic big data applications, leveraging purpose-built consensus algorithms like Raft to ensure data consistency. However, through systematic analysis, we reveal a critical performance issue in such consistent stores, i.e., overlapping persistence operations between consensus protocols and underlying storage engines result in significant I/O overhead. To address this issue, we present Nezha, a prototype distributed storage system that innovatively integrates key-value separation with Raft to provide scalable throughput in a strong consistency guarantee. Nezha redesigns the persistence strategy at the operation level and incorporates leveled garbage collection, significantly improving read and write performance while preserving Raft's safety properties. Experimental results demonstrate that, on average, Nezha achieves throughput improvements of 460.2%, 12.5%, and 72.6% for put, get, and scan operations, respectively.

cs.DC↗

arXiv2025

Note on the noise reduction in spectroscopic detection with compressed sensing

Spectroscopy sampling along delay time is typically performed with uniform delay spacing, which has to be low enough to satisfy the Nyquist-Shannon sampling theorem. The sampling theorem puts the lower bound for the sampling rate to ensure accurate resolution of the spectral features. However, this bound can be relaxed by leveraging prior knowledge of the signals, such as sparsity. Compressed sensing, a under-sampling technique successfully applied to spatial measurements (e.g., single-pixel imaging), has yet to be fully explored for the spectral measurements especially for the temporal sampling. In this work, we investigate the capability of compressed sensing for improving the temporal spectroscopic measurements to mitigate both measurement noise and intrinsic noise. By applying compressed sensing to single-shot pump-probe data, we demonstrate its effectiveness in noise reduction. Additionally, we propose a feasible experimental scheme using a digital mirror device to implement compressed sensing for temporal sampling. This approach provides a promising method for spectroscopy to reduce the signal noise and the number of sample measurements.

physics.chem-ph↗