AI 中文总结
本文探究能否用不可见读取构建自适应快照，经研究发现，即便在满足现有实现合理假设的单写者单扫描者场景下，具备不可见读取的自适应快照也不具备线性一致性。
AI 中文摘要
快照被广泛用于记录运行中执行的状态，相关研究已大量开展，目标是提升性能与扩展功能。本研究考虑针对m个组件的自适应快照，其提供Click()操作以逻辑上创建新快照，以及Observe(i)操作以返回组件i在最近一次Click()时的状态。近期已提出多种自适应快照的构造，有趣的是，即便不可见读取有时可显著提升性能，这些构造均未采用不可见读取。本文探究能否用不可见读取构建自适应快照，结果显示，即便将快照算法限制在单写者、单扫描者场景，且该场景满足所有现有自适应快照实现的合理假设，具备不可见读取的自适应快照也不具备线性一致性。
英文摘要
Snapshots are widely used to record the state of a running execution. Snapshots have been extensively studied in the literature, with the goal of improving performance and extending functionality. In this work, we consider $adaptive$ snapshots over a set of $m$ components. Adaptive snapshots provide a Click() operation that logically creates a new snapshot and an Observe$(i)$ operation that returns the state of component $i$ at the most recent Click(). Several constructions of adaptive snapshots have recently been proposed; interestingly, none of them employs invisible reads, even though invisible reads can improve performance, sometimes significantly. In this paper, we ask whether it is possible to build an adaptive snapshot with invisible reads. We show that, even when restricting the snapshot algorithm to the single-writer, single-scanner setting, under reasonable assumptions satisfied by all existing adaptive snapshot implementations, adaptive snapshots with invisible reads are not linearizable.
CommentsAccepted to the 40th International Symposium on Distributed Computing (DISC), 2026
