English

Mutex-based Desanonymization of an Anonymous Read/Write Memory

Distributed, Parallel, and Cluster Computing 2019-04-01 v1

Abstract

Anonymous shared memory is a memory in which processes use different names for the same shared read/write register. As an example, a shared register named AA by a process pp and a shared register named BB by another process qq can correspond to the very same register XX, and similarly for the names BB at pp and AA at qq which can correspond to the same register YXY\neq X. Hence, there is a permanent disagreement on the register names among the processes. This new notion of anonymity was recently introduced by G. Taubenfeld (PODC 2017), who presented several memory-anonymous algorithms and impossibility results. This paper introduces a new problem (new to our knowledge), that consists in "desanonymizing" an anonymous shared memory. To this end, it presents an algorithm that, starting with a shared memory made up of mm anonymous read/write atomic registers (i.e., there is no a priori agreement on their names), allows each process to compute a local addressing mapping, such that all the processes agree on the names of each register. The proposed construction is based on an underlying deadlock-free mutex algorithm for n2n\geq 2 processes (recently proposed in a paper co-authored by some of the authors of this paper), and consequently inherits its necessary and sufficient condition on the size mm of the anonymous memory, namely mm must belongs to the set M(n)={m: M(n)=\{m:~ such that  :1<n: gcd(,m)=1}{1}\forall~ \ell: 1<\ell \leq n:~ \gcd(\ell,m)=1\}\setminus \{1\}. This algorithm, which is also symmetric in the sense process identities can only be compared by equality, requires the participation of all the processes; hence it can be part of the system initialization. Last but not least, the proposed algorithm has a first-class noteworthy property, namely, its simplicity.

Keywords

Cite

@article{arxiv.1903.12204,
  title  = {Mutex-based Desanonymization of an Anonymous Read/Write Memory},
  author = {Emmanuel Godard and Damien Imbs and Michel Raynal and Gadi Taubenfeld},
  journal= {arXiv preprint arXiv:1903.12204},
  year   = {2019}
}
R2 v1 2026-06-23T08:22:35.354Z