Concept Of Cellular Automata Research Articles

Memristors in Cellular-Automata-Based Computing:A Review

The development of novel hardware computing systems and methods has been a topic of increased interest for researchers worldwide. New materials, devices, and architectures are being explored as a means to deliver more efficient solutions to contemporary issues. Along with the advancement of technology, there is a continuous increase in methods available to address significant challenges. However, the increased needs to be fulfilled have also led to problems of increasing complexity that require better and faster computing and processing capabilities. Moreover, there is a wide range of problems in several applications that cannot be addressed using the currently available methods and tools. As a consequence, the need for emerging and more efficient computing methods is of utmost importance and constitutes a topic of active research. Among several proposed solutions, we distinguish the development of a novel nanoelectronic device, called a “memristor”, that can be utilized both for storing and processing, and thus it has emerged as a promising circuit element for the design of compact and energy-efficient circuits and systems. The memristor has been proposed for a wide range of applications. However, in this work, we focus on its use in computing architectures based on the concept of Cellular Automata. The combination of the memristor’s performance characteristics with Cellular Automata has boosted further the concept of processing and storing information on the same physical units of a system, which has been extensively studied in the literature as it provides a very good candidate for the implementation of Cellular Automata computing with increased potential and improved characteristics, compared to traditional hardware implementations. In this context, this paper reviews the most recent advancements toward the development of Cellular-Automata-based computing coupled with memristor devices. Several approaches for the design of such novel architectures, called “Memristive Cellular Automata”, exist in the literature. This extensive review provides a thorough insight into the most important developments so far, helping the reader to grasp all the necessary information, which is here presented in an organized and structured manner. Thus, this article aims to pave the way for further development in the field and to bring attention to technological aspects that require further investigation.

A parallel computing architecture based on cellular automata for hydraulic analysis of water distribution networks

Water distribution networks (WDNs) are one of the largest infrastructures in society. Various methods for formulation and hydraulic analysis of water distribution networks, including numerical and non-numerical methods, have been previously proposed. Due to the complexity, the nonlinearity of the hydraulic equations of water distribution networks, and the need for multiple executions and uncertainties in parameters, solving the hydraulic model of water distribution networks has high time complexity. In this paper, a parallel computational architecture based on the concept of cellular automata is proposed to accelerate the numerical solution of the steady-state water distribution network model. Taylor series is proposed to solve hydraulic equations. The presented architecture was implemented as a parallel hardware platform on a field-programmable gate array. The performance of the proposed method was compared with EPANET software for networks with different complexities and topologies. The results show that the proposed parallel algorithm can accelerate the hydraulic analysis of regular water distribution networks up to 700 times and 250 times for small and large networks, respectively.

Dynamic-wave cellular automata framework for shallow water flow modeling

A new dynamic-wave cellular automata framework for two-dimensional (2D) shallow water flow (SWF) modeling is herein proposed. During the last decade, the concept of cellular automata (CA) has been widely adopted to develop various 2D shallow water flow models. Such CA models use simple transition rules that only consider the conservation of mass and neglect the conservation of momentum, as a result, the models behave like the non-inertia wave approximation which are not suitable for modeling strong discontinuous flows (i.e., transcritical flows and wet-dry interfaces). To overcome this limitation, the present study proposes a new CA framework (SWFCA) for 2D shallow water flow modeling, in which the Bernoulli hydraulic head is adopted to replace water level as the key factor to determine water movements. A novel methodology for linking water depths and velocities in the framework is developed. Model verification is carried out through four cases of regular flows and six benchmark cases with strong discontinuous flows. Model efficiency assessment is also conducted to analyze the numerical performance under various flow conditions. The outcomes indicate that the proposed SWFCA model and a non-inertia wave CA-based model (WCA2D) both provide satisfactory results on regular flows. In modeling strong discontinuous flows, the SWFCA model performs better than the WCA2D model and provides the same accuracy as the finite volume model with a HLLC scheme (FV-HLLC). In the aspect of moving wet-dry interfaces and flows under the partially wet condition, the SWFCA model can achieve higher accuracy than the FV-HLLC model. The numerical efficiency of the SWFCA model relates to the flow conditions involved. As the portion of strong discontinuous flows in the computational domain is increasing, the SWFCA model can be up to 305.5% and 121.0%-1282.2% faster than the WCA2D model and the FV-HLLC model, respectively. This novel CA-based framework has been proved its accuracy and efficiency for shallow water flow modeling. Therefore, it has considerable potentials as a useful tool for real-time flood inundation modeling.

GoZone: A Numerical Model for Travelling Fires Based on Cellular Automata Concept

Fires in large compartments tend to burn locally and to move across the floor over a period of time; this particular behaviour has been discovered to challenge the assumption of uniform gas temperature in the fire compartment. Recent studies on fires in large compartments have led to the now widely known concept of “travelling fires”. Several models have been proposed to describe the evolution in time of travelling fires. Although these models represented an innovative step in the field of travelling fires, the major drawbacks of these models can be found in the simplification of fire dynamics (constant spread rate, 1D imposed fire path) and limited field of application (rectangular based geometries). The purpose of this paper is to present a numerical model of travelling fire. The model was based on an improved zone model combined with a cellular automata model. The software GoZone, in which the model was implemented, is intended to be a practical solution to analyse fires in large compartments of potentially any shape. GoZone is aimed to describe the complex dynamics of the fire from ignition to a phase of growing localised fire that may eventually travel in the compartment, possibly followed by a flashover. The main sub models comprising GoZone are presented. A comparison is given with the results of under ventilated fire test 2 of the BST/FSR 1993 test series and with respect to the Veselì travelling fire test is shown. GoZone shows a promising capacity to represent fires in a large compartment in both air and fuel controlled fire conditions.

Threat impact analysis to air traffic control systems through flight delay modeling

Air traffic control (ATC) systems increasingly rely on communication, navigation, and other emerging digital technologies, making them more susceptible to external threats. To better analyze the different impacts, this paper proposes a new flight delay model that models the ATC system from two perspectives. In the air delay, we view the problem as an optimal path choice with a set of capacity constraints and consider the speed change, rerouting, and pathfinding. In the ground delay, the concept of cellular automata is extended to model the flight queue at each airport. Last, the system dynamics of delays are considered, and the two stages of modeling are combined using flight delay as an indicator to achieve an intuitive description of the impact on the system threat. Compared to the current state of the art, the model is shown to be a simple way to analyze the impact of different sophisticated threats. It also helps aviation system planners better understand the impact of different threats so that effective measures can be taken to improve system performance.

Multi-Domain and Multi-Material Topology Optimization in Design and Strengthening of Innovative Sustainable Structures

Expectations and challenges of modern sustainable engineering and architecture stimulate intensive development of structural analysis and design techniques. Designing durable, light and eco-friendly constructions starts at the conceptual stage, where new efficient design and optimization tools need to be implemented. Innovative methods, like topology optimization, become more often a daily practice of engineers and architects in the process of solving more and more demanding up-to-date engineering problems efficiently. Topology optimization is a dynamically developing research area with numerous applications to many research and engineering fields, ranging from the mechanical industry, through civil engineering to architecture. The motivation behind the present study is to make an attempt to broaden the area of topology optimization applications by presenting an original approach regarding the implementation of the multi-domain and multi-material topology optimization to the design and the strengthening/retrofitting of structures. Moreover, the implementation of the design-dependent self-weight loading into the design model is taken into account as a significantly important issue, since it influences the final results of the topology optimization process, especially when considering massive engineering structures. As an optimization tool, the original efficient heuristic algorithm based on Cellular Automata concept is utilized.

Salt and Pepper Noise Reduction by Cellular Automata

An algorithm and software based on the concept of cellular automata was developed or removing salt and pepper noise efficiently. The paper shows the software programming for eveloping an algorithm and software called Cellular Automata Image Denoising (CAID) toolkit. This paper presents the CAID toolkit using examples and discusses how the CAID toolkit is designed. Matlab code was used to develop a software program for removing salt and pepper noise in gray and color images. We hope the code will help the researchers who are interested in the Image Denoising for research of image processing.

Accelerating Large-Scale Interconnection Network Simulation by Cellular Automata Concept

Accelerating Large-Scale Interconnection Network Simulation by Cellular Automata Concept

Compact CA-Based Single Byte Error Correcting Codec

Memory contents are usually corrupted due to soft errors caused by external radiation and hence the reliability of memory systems is reduced. In order to enhance the reliability of memory systems, error correcting codes (ECC) are widely used to detect and correct errors. Single bit error correcting with double bits errors detecting codes are generally used in memory systems. But in case of multiple cell errors, these codes are unable to detect and correct errors. Recently, single byte error correcting Reed Solomon (SEC-RS) codes are used to detect and correct single byte error in memory systems. In this paper, a new single byte error correcting (SEC) code is proposed based on the concept of cellular automata (termed as CASEC). The main aim of this work is to reduce the area and power of SEC encoder and decoder circuit without affecting delay. In this paper, CASEC(10,8,8), CASEC(18,16,8), 2xCASEC(10,8,4) and 2xCASEC(19,6,4) codecs are designed and implemented. CASEC(18,16,8) codec has 67.79 percent lesser hardware complexity compared to existing design. Proposed codecs are simulated and synthesized for both FPGA and ASIC platforms. It is found that speed of the proposed design is almost equal to the existing design but requires lesser area and power. Area-delay product (ADP) of proposed CASEC(10,8,8), CASEC(18,16,8), 2xCASEC(10,8,4) codecs are better compared to the existing designs.

Hydrodynamic force evaluation in lattice Boltzmann method

The lattice Boltzmann method is a mesoscopic numerical method originating from kinetic theory and the cellular automaton concept. It has been successfully used to simulate complex flows, especially particle suspensions and multiphase flows. In this paper, we review our recent work on fluid-structure interactions and nonideal force evaluations. We introduced the relative velocity into the treatment of fluid-structure interfacial dynamics and proposed a Galilean invariant momentum exchange method. The method is simple, accurate and efficient. It is independent of boundary geometries and only uses the local data, thus it is convenient to implement parallelization and 3D simulations. The numerical simulations are so vastly improved that the force fluctuations are very small and a time average procedure becomes unnecessary. To simulate phase separation and two-phase flow, we directly evaluated the nonideal force based on the free energy and proposed a multiphase flow model. Thermodynamic consistency and Galilean invariance of the model are theoretically satisfied and numerically verified. This model can be easily implemented and cooperated with various equations of state to simulate all kinds of the multiphase systems. Chemical potential is an effective way to drive phase transition or express surface wettability. In the further study, we proposed another multiphase flow model based on chemical potential. It is mathematically equivalent to the previous one, but is more computationally efficient owing to avoiding the calculations of pressure tensor and tensor divergence. Together with the chemical potential boundary condition, the model can effectively simulate wetting phenomena. The numerical results show that the contact angle can be linearly tuned by the surface chemical potential.

An approach for simulating the THMC process in single novaculite fracture using EPCA

An approach for simulating thermal, hydraulic, mechanical and chemical (THMC) coupled processes in single rock fractures has been developed under the framework of a self-developed numerical method, i.e., an elasto-plastic cellular automaton. The balance equations of multi-physics problems to describe the THMC process in single rock fracture are solved by using cellular automaton technique on space scale and finite difference method on time scale, respectively. Using the concept of cellular automaton, a single rock fracture surface is discretized into a system composed of cell elements. Different apertures, i.e., 0 for contact and nonzero for void, are assigned to each cell element based on the fracture surface topography. The fluid flow, stress-dependent chemical reaction and solute transport are simulated by using a cellular automaton updating rule, in which only local cell balance equation is considered. The contribution of cell elements in contact to cell’s transmissivity and convection can be ignored conveniently. The Lagrangian method is used to simulate the particle transport. Special treatment for particle transport to outer boundaries and internal boundaries is adopted. As a result, the local behaviors, such as the formation of local contact, dead ends in the fracture and the local aperture change, are conveniently updated dynamically. The approach is used to simulate the coupled THMC process in a single novaculite fracture. The behaviors of pressure dissolution caused by effective stress, free-face dissolution/precipitation, thermal-dependent fluid flow and ion transport are well reproduced by using the developed approach, subject to parameter calibration. The robustness of the general approach to such complex problems is demonstrated by comparing with experimental data.

BLOCKYLAND

Background BLOCKYLAND is a city building game based on the concept of cellular automata (CA), and urban cellular automata. The game has CA-like processes that invert the role of players from passive observers in other CA applications to active thinkers. The processes challenge players to apply logical thinking and decision making from the perspective of serious games. The players’ mission is to build a city by applying the provided CA rules. Two types of CA rules are provided: 1) The logical rule, whereby players apply to build the city according to the preset conditions, and 2) The optional rule, whereby they may apply to upgrade an existing building for an extra score. Aim This article aims to present the design and development of CA-based game, BLOCKYLAND and describe its effectiveness as an instructional tool to enhance logical thinking. Results Results from the mixed-method pilot study show that BLOCKYLAND enhanced players’ logical thinking after the gameplay. Additionally, from the extensive debriefing following the game, participants stated that the game aided them with transforming their game experiences into learning experiences and relating the logical thinking practice into real-life application. Results Conclusion. As a combination of logical thinking practices and a serious game, BLOCKYLAND has several implications for educational stakeholders; both theoretical and practical.

An Image Encryption Scheme Based on DNA Computing and Cellular Automata

Networks have developed very quickly, allowing the speedy transfer of image information through Internet. However, the openness of these networks poses a serious threat to the security of image information. The field of image encryption has drawn attention for this reason. In this paper, the concepts of 1-dimensional DNA cellular automata and T-DNA cellular automata are defined, and the concept of reversible T-DNA cellular automata is introduced. An efficient approach to encryption involving reversible T-DNA cellular automata as an encryption tool and natural DNA sequences as the main keys is here proposed. The results of a simulation experiment, performance analysis, and comparison to other encryption algorithms showed this algorithm to be capable of resisting brute force attacks, statistical attacks, and differential attacks. It also enlarged the key space enormously. It meets the criteria for one-time pad and resolves the problem that one-time pad is difficult to save.

Computational Modeling of Proteins based on Cellular Automata

The literature of building computational and mathematical models of proteins is rich and diverse, since its practical applications are of a vital importance in the development of many fields. Modeling proteins is not a straightforward process and in some modeling strategies, it requires to combine concepts from different fields including physics, chemistry, thermodynamics, and computer science. The focus here will be on models that are based on the concept of cellular automata and equivalent systems. Cellular automata are discrete computational models that are capable of universal computation, in other words, they are capable of doing any computation that a normal computer can do. What is special about cellular automata is its ability to produce complex and chaotic global behavior from local interactions. The paper discusses the effort done so far by the researchers community in this direction and proposes a computational model of protein folding that is based on 3D cellular automata. Unlike common models, the proposed model maintains the basic properties of cellular automata and keeps a realistic view of proteins operations. As in any cellular automata model, the dimension, neighborhood, boundary, and rules were specified. In addition, a discussion is given to clarify why these parameters are in place and what possible alternatives can be used in the protein folding context.

Analysis of the Effect of Variable Lateral Gap Maintaining Behavior of Vehicles on Traffic Flow Modeling

Vehicular interaction between different types of vehicles, in both the lateral and longitudinal directions, significantly affects the heterogeneous traffic flow modeling. From the field data it has been observed that the drivers vary gaps based on the changing traffic conditions. This variable gap maintaining behavior has been characterized using macroscopic traffic characteristic called area occupancy. Variable gaps are explained through effective vehicle width and it is found to be influenced by various factors. In this study, variable gap maintaining behavior is modeled using the concept of cellular automata (CA), with the help of a modified cell structure. Cell width in the modified cell structure has been varied corresponding to the observed variation in the effective vehicle width. It was found that the results obtained from the model incorporated with the variable gap maintaining behavior are significantly different from that of the uniform-cell-width based CA model. The effect is more significant for urban traffic conditions due to the presence of two-wheelers and three-wheelers.

Stochastic cellular automata simulation of oscillations and autowaves in reaction-diffusion systems

In this paper, the investigations on stochastic cellular automata models of stable oscillations and autowaves in active media are summarized to formulate a concept of stochastic cellular automaton (CA) corresponding to asynchronous CAs with probabilistic transition rules. A formal description of a stochastic CA and a stochastic CA model is given. The properties and methods of synthesis of CA models for a specified set of elementary physical and chemical transformations are described. Some possibilities of simulating autowave and oscillatory processes are demonstrated using, as an example, a carbon monoxide oxidation reaction on a platinum catalyst with surface restructuring. The CA-simulation has made it possible to reveal the range of reaction parameter values with stable oscillations of reagent concentrations and to observe autowaves on the platinum surface. Special attention is given to providing a highly efficient parallel implementation of the stochastic CA algorithm. For this, the asynchronous mode must be preliminarily transformed to a block-synchronous one. Its equivalence to the asynchronous mode is justified. This is done for the CA reaction model by a comparative statistical analysis of the simulation results.

Comparative Analysis of Traditional Methods with Game of Life in Cellular Automata for Edge Detection

Edge detection is one of the most commonly used operations in image analysis, which is recently receiving much attention. There are various existing traditional edge detectors which are used to estimate edge magnitude and orientation. The concept of Cellular Automata (CA) also has been used for edge detection making the technique more efficient and effective. This paper includes a comparative study of the traditional techniques with the Cellular Automata (CA) technique which is based on rules of Conway’s Game of Life (GoL). The comparative analysis is carried out based on a particular set of assumed parameters which are suitable enough to conclude the best performing edge detector General Terms Edge Detection, Cellular Automata, Game of Life, Traditional Edge Detection Methods.

Methods for Cellular Automata and Evolution Systems in Modelling and Simulation

Cellular automata provide an interesting concept for modelling and simulation. Besides advanced modelling approaches like the Lattice Boltzmann Method cellular automata are also used for simulation in population dynamics, reaction diffusion systems or bio-medicine. While the basic concepts of cellular automata are rather clear and unambiguous, there exists no general mathematical formalism as there is for other modelling approaches like differential equations or stochastic processes. Often such systems are not even labelled as cellular automata due to the historic and diverse connotation of this term. This modelling approach is however only applicable for systems that exhibit a certain topological structure. We interpret the topological concepts of such systems as graphs and vector spaces in order to provide a suitable mathematical framework for analysis. Furthermore a generalisation leads to evolution systems (strongly continuous semigroups, abstract Cauchy problems) on the one hand and stochastic processes on the other. This provides access to a variety of mathematical tools and methods for analysing and validating cellular automaton modelling approaches.

Cellular automata with dynamic structure to simulate the growth of biological tissues

A concept of cellular automaton with dynamic structure of the cellular space (DCA) is proposed. The DCA extends the capabilities of classical cellular automata (CA) and allows using a cellular automata approach to the problems of simulating biological tissue growth. A DCA differs from a classical CA in that its cells are not located on a regular lattice, and the intercellular connections are explicitly described by a neighborhood matrix. In addition, insertion and partition operators are introduced in the DCA. These operators allow one to dynamically change the cell space structure. Based on this extension, a DCA-model of growth of a shoot apical meristem of Arabidopsis Thaliana is constructed, being a parallel composition of two DCA: an asynchronous two-dimensional DCA simulating self-regulation of biological cells and a synchronous one-dimensional DCA simulating the growth and division of biological cells. The results of computer simulation have shown that the behavior of the DCA-model is the same as that of an existing model based on a composition of differential equations and L-system (Lindenmayer system) methods. The DCA-model allows one to simulate the growth of individual biological cells and to visualize the dynamics of substances in these cells (decay, synthesis, and diffusion).

Application of cellular automata and type-2 fuzzy logic to dynamic vehicle path planning

Nowadays, most road navigation systems’ planning of optimal routes is conducted by the On Board Unit (OBU). If drivers want to obtain information about the real-time road conditions, a Traffic Message Channel (TMC) module is also needed. However, this module can only provide the current road conditions, as opposed to actually planning appropriate routes for users. In this work, the concept of cellular automata is used to collect real-time road conditions and derive the appropriate paths for users. Notably, type-2 fuzzy logic is adopted for path analysis for each cell established in the cellular automata algorithm. Besides establishing the optimal routes, our model is expected to be able to automatically meet the personal demands of all drivers, achieve load balancing between all road sections to avoid the problem of traffic jams, and allow drivers to enjoy better driving experiences. A series of simulations were conducted to compare the proposed approach with the well-known A* Search algorithm and the latest state-of-the-art path planning algorithm found in the literature. The experimental results demonstrate that the proposed approach is scalable in terms of the turnaround times for individual users. The practicality and feasibility of applying the proposed approach in the real-time environment is thus justified.