RMR-Efficient Randomized Abortable Mutual Exclusion
Abhijeet Pareek, Philipp Woelfel

TL;DR
This paper introduces the first randomized abortable mutual exclusion algorithm with sub-logarithmic expected remote memory references, improving efficiency in shared-memory systems under a weak adversary model.
Contribution
It presents a novel randomized abortable mutual exclusion algorithm achieving expected RMR complexity of O(log N / log log N), breaking previous logarithmic barriers.
Findings
Achieves sub-logarithmic expected RMR complexity
Supports abort operations within finite steps
Operates efficiently against a weak adversary
Abstract
Recent research on mutual exclusion for shared-memory systems has focused on "local spin" algorithms. Performance is measured using the "remote memory references" (RMRs) metric. As common in recent literature, we consider a standard asynchronous shared memory model with N processes, which allows atomic read, write and compare-and-swap (short: CAS) operations. In such a model, the asymptotically tight upper and lower bound on the number of RMRs per passage through the Critical Section is Theta(log N) for the optimal deterministic algorithms (see Yang and Anderson,1995, and Attiya, Hendler and Woelfel, 2008). Recently, several randomized algorithms have been devised that break the Omega(log N) barrier and need only o(log N) RMRs per passage in expectation (see Hendler and Woelfel, 2010, Hendler and Woelfel, 2011, and Bender and Gilbert, 2011). In this paper we present the first…
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