Strongly Linearizable Implementations of Snapshots and Other Types
Sean Ovens, Philipp Woelfel

TL;DR
This paper introduces new lock-free strongly linearizable implementations of shared objects, including the first bounded-space snapshot, enhancing correctness guarantees for randomized algorithms.
Contribution
It presents the first strongly linearizable lock-free snapshot with bounded space and extends the class of objects with lock-free strongly linearizable implementations.
Findings
First bounded-space strongly linearizable snapshot implementation.
Modification of existing ABA-detecting register to be strongly linearizable.
All types in a certain class have lock-free strongly linearizable implementations from atomic registers.
Abstract
Linearizability is the gold standard of correctness conditions for shared memory algorithms, and historically has been considered the practical equivalent of atomicity. However, it has been shown [1] that replacing atomic objects with linearizable implementations can affect the probability distribution of execution outcomes in randomized algorithms. Thus, linearizable objects are not always suitable replacements for atomic objects. A stricter correctness condition called strong linearizability has been developed and shown to be appropriate for randomized algorithms in a strong adaptive adversary model [1]. We devise several new lock-free strongly linearizable implementations from atomic registers. In particular, we give the first strongly linearizable lock-free snapshot implementation that uses bounded space. This improves on the unbounded space solution of Denysyuk and Woelfel [2]. As…
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Taxonomy
TopicsDistributed systems and fault tolerance · Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices
