A Cellular Automata Bioinspired Algorithm Designing Data Trees in Wireless Sensor Networks

Tsompanas, Michail‐Antisthenis; Mayne, Richard; Adamatzky, Andrew

doi:10.1155/2015/471045

Cited by 11 publications

(4 citation statements)

References 37 publications

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“…CAs is the most suitable paradigm to model such a structure [64,11,67,14,66,63,28,27,68,13,65]. The maze can be modeled by creating a grid of cells with standard initial and boundary conditions.…”

Section: Physarum Polycephalum Ca Modelmentioning

confidence: 99%

Cellular Automata Applications in Shortest Path Problem

Tsompanas

Dourvas

Ioannidis

et al. 2018

Emergence, Complexity and Computation

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Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm.

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Section: Physarum Polycephalum Ca Modelmentioning

confidence: 99%

Cellular Automata Applications in Shortest Path Problem

Tsompanas

Dourvas

Ioannidis

et al. 2018

Emergence, Complexity and Computation

Self Cite

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“…8. A Physarum-inspired algorithm for solution of the Steiner tree problem is proposed in [86] and applied to optimise the minimal exposure problem and worstcase coverage in wireless sensor networks [86,124]. 9.…”

Section: Modelling Creativitymentioning

confidence: 99%

Thirty Seven Things to Do with Live Slime Mould

Adamatzky

2016

Emergence, Complexity and Computation

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Slime mould Physarum polycephalum is a large single cell capable for distributed sensing, concurrent information processing, parallel computation and decentralised actuation. The ease of culturing and experimenting with Physarum makes this slime mould an ideal substrate for real-world implementations of unconventional sensing and computing devices. In the last decade the Physarum became a swiss knife of the unconventional computing: give the slime mould a problem it will solve it. We provide a concise summary of what exact computing and sensing operations are implemented with live slime mould. The Physarum devices range from morphological processors for computational geometry to experimental archeology tools, from self-routing wires to memristors, from devices approximating a shortest path to analog physical models of space exploration.

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“…Some examples of the vast range of problems tackled by P. polycephalum [3] are labyrinth solving [4,5], approximation of Voronoi diagrams and Delaunay triangulation [6], travelling salesman problem [7], simulation of Boolean logic [8] and evaluation of transport [9] and ancient road networks [10]. Nonetheless, the abilities of P. polycephalum inspired scientists to invest efforts towards the simulation of its behavior and its usage to solve complex problems, like designing routes in information networks [11]. Some examples of the computerized approximation of the behavior of the plasmodium are a mathematical model with feedback of the tube dynamics [12], agent-based particle models [13] and cellular automata (CA) [14][15][16]We propose a novel approach towards computerizing the abilities of the slime mouldby designing a hybrid model, which combines CA and a multi-agent system is introduced.…”

Section: Introductionmentioning

confidence: 99%

Hardware Implementation of a Biomimicking Hybrid CA

Madikas

Tsompanas

Dourvas

et al. 2018

Developments in Language Theory

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A hybrid model, combining a Cellular Automaton (CA) and a multi-agent system, was proposed to mimic the computation abilities of the plasmodium of Physarum polycephalum. This model was implemented on software, as well as, on hardware, namely on a Field Programmable Gate Array (FPGA). The specific ability of the P. polycephalum simulated here is given in brief, also bringing attention to the approximation of a Kolmogorov-Uspensky machine (KUM), an alternative to the Turing machine. KUM represent data and program by a labeled indirected graphs and a computation is performed by adding/removing nodes/edges. The proposed model implementation is taking full advantage of the inherent parallel nature of automaton networks, and CA, as a result of the mapping of the local rule to a digital circuit. Consequently, the acceleration of the computation for the hardware implementation, compared to the software, is as high as 6 orders of magnitude.

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A Cellular Automata Bioinspired Algorithm Designing Data Trees in Wireless Sensor Networks

Cited by 11 publications

References 37 publications

Cellular Automata Applications in Shortest Path Problem

Cellular Automata Applications in Shortest Path Problem

Thirty Seven Things to Do with Live Slime Mould

Hardware Implementation of a Biomimicking Hybrid CA

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