Search results for "Pseudorandom number generator"

Dynamic Test Methods for COTS SRAMs

2014

International audience; In previous works, we have demonstrated the importance of dynamic mode testing of SRAM components under ionizing radiation. Several types of failures are difficult to expose when the device is tested under static (retention) mode. With the purpose of exploring and defining the most complete testing procedures and reveal the potential hazardous behaviors of SRAM devices, we present novel methods for the dynamic mode radiation testing of SRAMs. The proposed methods are based on different word address accessing schemes and data background: Fast Row, Fast Column, Pseudorandom, Adjacent (Gray) and Inverse Adjacent (Gray). These methods are evaluated by heavy ion and atmos…

Study on the Effects of Pseudorandom Generation Quality on the Performance of Differential Evolution

2011

Experiences in the field of Monte Carlo methods indicate that the quality of a random number generator is exceedingly significant for obtaining good results. This result has not been demonstrated in the field of evolutionary optimization, and many practitioners of the field assume that the choice of the generator is superfluous and fail to document this aspect of their algorithm. In this paper, we demonstrate empirically that the requirement of high quality generator does not hold in the case of Differential Evolution.

Compact and Field Portable Biophotonic Sensors for Automated Cell Identification (Plenary Address)

2021

In this Plenary address paper, we overview recently published work for automated cell identification using 3D optical imaging in compact and field portable biophotonic sensors. Digital holographic microscopy systems and lensless pseudorandom phase encoding systems capture 3D information of biological cells and make highly accurate automated cell identification possible. Overviewed systems include sickle cell disease diagnosis based on spatio-temporal cell dynamics in a field-portable 3D-printed shearing digital holography as well as lensless cell identification of both single and multicell samples using pseudorandom phase encoding.

On the Influence of PRNGs on Data Distribution

2012

The amount of digital information produced grows rapidly and constantly. Storage systems use clustered architectures designed to store and process this information efficiently. Their use introduces new challenges in storage systems development, like load-balancing and data distribution. A variety of randomized solutions handling data placement issues have been proposed and utilized. However, to the best of our knowledge, there has not yet been a structured analysis of the influence of pseudo random number generators (PRNGs) on the data distribution. In the first part of this paper we consider Consistent Hashing [1] as a combination of two consecutive phases: distribution of bins and distrib…

Multidimensional pseudo-random pulse signals and their coincidence properties

1996

A Hardware and Secure Pseudorandom Generator for Constrained Devices

2018

Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the $N$ -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term eff…

Characterizing Cavities in Model Inclusion Fullerenes: A Comparative Study

2001

Abstract: The fullerene-82 cavity is selected as a model system in order to test several methods for characterizing inclusion molecules. The methods are based on different technical foundations such as a square and triangular tessellation of the molecular surface, spherical tessellation of the molecular surface, numerical integration of the atomic volumes and surfaces, triangular tessellation of the molecular surface, and cubic lattice approach to the molecular volume. Accurate measures of the molecular volume and surface area have been performed with the pseudorandom Monte Carlo (MCVS) and uniform Monte Carlo (UMCVS) methods. These calculations serve as a reference for the rest of the meth…

On the collision property of chaotic iterations based post-treatments over cryptographic pseudorandom number generators

2018

International audience; There is not a proper mathematical definition of chaos, we have instead a quite big amount of definitions, each of one describes chaos in a more or less general context. Taking in account this, it is clear why it is hard to design an algorithm that produce random numbers, a kind of algorithm that could have plenty of concrete appliceautifat (anul)d bions. However we must use a finite state machine (e.g. a laptop) to produce such a sequence of random numbers, thus it is convenient, for obvious reasons, to redefine those aimed sequences as pseudorandom; also problems arise with floating point arithmetic if one wants to recover some real chaotic property (i.e. propertie…

CIPRNG: A VLSI Family of Chaotic Iterations Post-Processings for $\mathbb {F}_{2}$ -Linear Pseudorandom Number Generation Based on Zynq MPSoC

2018

Hardware pseudorandom number generators are continuously improved to satisfy both physical and ubiquitous computing security system challenges. The main contribution of this paper is to propose two post-processing modules in hardware, to improve the randomness of linear PRNGs while succeeding in passing the TestU01 statistical battery of tests. They are based on chaotic iterations and are denoted by CIPRNG-MC and CIPRNG-XOR. They have various interesting properties, encompassing the ability to improve the statistical profile of the generators on which they iterate. Such post-processing have been implemented on FPGA and ASIC without inferring any blocs (RAM or DSP). A comparison in terms of …

Random Slicing: Efficient and Scalable Data Placement for Large-Scale Storage Systems

2014

The ever-growing amount of data requires highly scalable storage solutions. The most flexible approach is to use storage pools that can be expanded and scaled down by adding or removing storage devices. To make this approach usable, it is necessary to provide a solution to locate data items in such a dynamic environment. This article presents and evaluates the Random Slicing strategy, which incorporates lessons learned from table-based, rule-based, and pseudo-randomized hashing strategies and is able to provide a simple and efficient strategy that scales up to handle exascale data. Random Slicing keeps a small table with information about previous storage system insert and remove operations…