Abstract

Recent advances in non-volatile main memory (NVM) technology have spurred research on algorithms that are resilient to intermittent failures that cause processes to crash and subsequently restart. In this paper we present a Recoverable Mutual Exclusion (RME) algorithm that supports abortability. Our algorithm guarantees FCFS and a strong liveness property: processes do not starve even in runs consisting of infinitely many crashes, provided that a process crashes at most a finite number of times in each of its attempts. On DSM and Relaxed-CC multiprocessors, a process incurs O(min (k, log n)) RMRs in a passage and O(f+ min (k, log n)) RMRs in an attempt, where n is the number of processes that the algorithm is designed for, k is the point contention of the passage or the attempt, and f is the number of times that p crashes during the attempt. On a Strict CC multiprocessor, the passage and attempt complexities are O(n) and O(f+n), respectively. Our algorithm uses only the read, write, and CAS operations, which are commonly supported by multiprocessors. Attiya, Hendler, and Woelfel proved that, with any mutual exclusion algorithm, a process incurs at least varOmega (log n) RMRs in a passage, if the algorithm uses only the read, write, and CAS operations (in: Proc. of the Fortieth ACM Symposium on Theory of Computing, New York, NY, USA, 2008). This lower bound implies that the worst-case RMR complexity of our algorithm is optimal for the DSM and Relaxed CC multiprocessors. This paper is an expanded version of our conference paper as reported by Jayanti and Joshi (in: Atig and Schwarzmann (eds) Networked Systems. Springer International Publishing, Cham, 2019), which presented the first Recoverable Mutual Exclusion (RME) algorithm that supports abortability. This algorithm from our conference paper (in: Atig and Schwarzmann (eds) Networked Systems. Springer International Publishing, Cham, 2019) admits starvation when there are infinitely many aborts in a run. In this paper, we fix this shortcoming and prove the algorithm’s properties by identifying an inductive invariant.

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