TY - GEN
T1 - The Limits of Helping in Non-volatile Memory Data Structures
AU - Ben-Baruch, Ohad
AU - Ravi, Srivatsan
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Linearizability, the traditional correctness condition for concurrent data structures is considered insufficient for the non-volatile shared memory model where processes recover following a crash. For this crash-recovery shared memory model, strict-linearizability is considered appropriate since, unlike linearizability, it ensures operations that crash take effect prior to the crash or not at all. This work formalizes and answers the question of whether an implementation of a data type derived for the crash-stop shared memory model is also strict-linearizable in the crash-recovery model. This work presents a rigorous study to prove how helping mechanisms, typically employed by non-blocking implementations, is the algorithmic abstraction that delineates linearizability from strict-linearizability. We first formalize the crash-recovery model and how explicit process crashes and recovery introduces further dimensionalities over the standard crash-stop shared memory model. We make the following technical contributions that answer the question of whether a help-free linearizable implementation is strict-linearizable in the crash-recovery model: (i) we prove surprisingly that there exist linearizable implementations of object types that are help-free, yet not strict-linearizable; (ii) we then present a natural definition of help-freedom to prove that any obstruction-free, linearizable and help-free implementation of a total object type is also strict-linearizable. The next technical contribution addresses the question of whether a strict-linearizable implementation in the crash-recovery model is also help-free linearizable in the crash-stop model. To that end, we prove that for a large class of object types, a non-blocking strict-linearizable implementation cannot have helping. Viewed holistically, this work provides the first precise characterization of the intricacies in applying a concurrent implementation designed for the crash-stop model to the crash-recovery model, and vice-versa.
AB - Linearizability, the traditional correctness condition for concurrent data structures is considered insufficient for the non-volatile shared memory model where processes recover following a crash. For this crash-recovery shared memory model, strict-linearizability is considered appropriate since, unlike linearizability, it ensures operations that crash take effect prior to the crash or not at all. This work formalizes and answers the question of whether an implementation of a data type derived for the crash-stop shared memory model is also strict-linearizable in the crash-recovery model. This work presents a rigorous study to prove how helping mechanisms, typically employed by non-blocking implementations, is the algorithmic abstraction that delineates linearizability from strict-linearizability. We first formalize the crash-recovery model and how explicit process crashes and recovery introduces further dimensionalities over the standard crash-stop shared memory model. We make the following technical contributions that answer the question of whether a help-free linearizable implementation is strict-linearizable in the crash-recovery model: (i) we prove surprisingly that there exist linearizable implementations of object types that are help-free, yet not strict-linearizable; (ii) we then present a natural definition of help-freedom to prove that any obstruction-free, linearizable and help-free implementation of a total object type is also strict-linearizable. The next technical contribution addresses the question of whether a strict-linearizable implementation in the crash-recovery model is also help-free linearizable in the crash-stop model. To that end, we prove that for a large class of object types, a non-blocking strict-linearizable implementation cannot have helping. Viewed holistically, this work provides the first precise characterization of the intricacies in applying a concurrent implementation designed for the crash-stop model to the crash-recovery model, and vice-versa.
UR - https://www.scopus.com/pages/publications/85142695337
U2 - 10.1007/978-3-031-21017-4_6
DO - 10.1007/978-3-031-21017-4_6
M3 - Conference contribution
AN - SCOPUS:85142695337
SN - 9783031210167
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 84
EP - 98
BT - Stabilization, Safety, and Security of Distributed Systems - 24th International Symposium, SSS 2022, Proceedings
A2 - Devismes, Stéphane
A2 - Petit, Franck
A2 - Altisen, Karine
A2 - Di Luna, Giuseppe Antonio
A2 - Fernandez Anta, Antonio
PB - Springer Science and Business Media Deutschland GmbH
T2 - 24th International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2022
Y2 - 15 November 2022 through 17 November 2022
ER -