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RMR-Efficient Randomized Abortable Mutual Exclusion

(Extended Abstract)
  • Abhijeet Pareek
  • Philipp Woelfel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7611)

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 bounds on the number of RMRs per passage through the Critical Section is Θ(logN) for the optimal deterministic algorithms [6,22]. Recently, several randomized algorithms have been devised that break the Ω(logN) barrier and need only o(logN) RMRs per passage in expectation [7,13,14]. In this paper we present the first randomized abortable mutual exclusion algorithm that achieves a sub-logarithmic expected RMR complexity. More precisely, against a weak adversary (which can make scheduling decisions based on the entire past history, but not the latest coin-flips of each process) every process needs an expected number of O(logN/loglogN) RMRs to enter end exit the critical section. If a process receives an abort-signal, it can abort an attempt to enter the critical section within a finite number of its own steps and by incurring O(logN/loglogN) RMRs.

Keywords

Abortable Mutual Exclusion Remote Memory References RMRs Weak Adversary Randomization Shared Memory 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Abhijeet Pareek
    • 1
  • Philipp Woelfel
    • 1
  1. 1.University of CalgaryCanada

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