TinyMT32 Pseudo Random Number Generator (PRNG)
draft-ietf-tsvwg-tinymt32-03

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Document Type Active Internet-Draft (tsvwg WG)
Last updated 2019-05-30 (latest revision 2019-05-27)
Replaces draft-roca-tsvwg-tinymt32
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Send notices to Wesley Eddy <wes@mti-systems.com>
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TSVWG                                                           M. Saito
Internet-Draft                                              M. Matsumoto
Intended status: Standards Track                    Hiroshima University
Expires: November 28, 2019                                 V. Roca (Ed.)
                                                             E. Baccelli
                                                                   INRIA
                                                            May 27, 2019

             TinyMT32 Pseudo Random Number Generator (PRNG)
                      draft-ietf-tsvwg-tinymt32-03

Abstract

   This document describes the TinyMT32 Pseudo Random Number Generator
   (PRNG) that produces 32-bit pseudo-random unsigned integers and aims
   at having a simple-to-use and deterministic solution.  This PRNG is a
   small-sized variant of Mersenne Twister (MT) PRNG [MT98].  The main
   advantage of TinyMT32 over MT is the use of a small internal state,
   compatible with most target platforms including embedded devices,
   while keeping a reasonably good randomness.

Status of This Memo

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   This Internet-Draft will expire on November 28, 2019.

Copyright Notice

   Copyright (c) 2019 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents

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   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Definitions . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  TinyMT32 PRNG Specification . . . . . . . . . . . . . . . . .   3
     3.1.  TinyMT32 Source Code  . . . . . . . . . . . . . . . . . .   3
     3.2.  TinyMT32 Usage  . . . . . . . . . . . . . . . . . . . . .   7
     3.3.  Specific Implementation Validation and Deterministic
           Behavior  . . . . . . . . . . . . . . . . . . . . . . . .   8
   4.  Security Considerations . . . . . . . . . . . . . . . . . . .   9
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   9
   6.  Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .   9
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   9
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .   9
     7.2.  Informative References  . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  10

1.  Introduction

   This document specifies the TinyMT32 PRNG, as a specialization of the
   reference implementation version 1.1 (2015/04/24) by Mutsuo Saito and
   Makoto Matsumoto, from Hiroshima University:

   o  Official web site [TinyMT-web]
   o  Official github site and reference implementation [TinyMT-dev]

   This specialisation aims at having a simple-to-use and deterministic
   PRNG, as explained below.

   TinyMT is a new small-sized variant introduced by Mutsuo Saito and
   Makoto Matsumoto in 2011 of the Mersenne Twister (MT) PRNG [MT98].
   This document focusses on the TinyMT32 variant (rather than TinyMT64)
   of the TinyMT PRNG, which outputs 32-bit unsigned integers.

   The purpose of TinyMT is not to replace Mersenne Twister: TinyMT has
   a far shorter period (2^^127 - 1) than MT.  The merit of TinyMT is in
   its small size of the internal state of 127 bits, far smaller than
   the 19937 bits of MT.  According to statistical tests (BigCrush in
   TestU01 and AdaptiveCrush), the quality of the outputs of TinyMT
   seems pretty good in terms of randomnes (in particular the uniformity
   of generated numbers), taking the small size of the internal state
   into consideration (see [TinyMT-web]).  From this point of view,

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