Cellular Automata Applications in Shortest Path Problem

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. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Methodology for Automated Design of Quantum-Dot Cellular Automata Circuits

Quantum-dot Cellular Automata (QCA) provide very high scale integration potential, very high switching frequency, and have extremely low power demands, which make the QCA technology quite attractive for the design and implementation of large-scale, high-performance nanoelectronic circuits. However, state-of-the-art QCA circuit designs were not derived by following a set of universal design rules, as is the case of CMOS circuits, and, as a result, it is either impossible or very difficult to combine QCA circuit blocks in effective large-scale circuits. In this paper, we introduce a novel automated design methodology, which builds upon a QCA specific universal design rules set. The proposed methodology assumes the availability of a generic QCA crossbar architecture and provides the means to customize it in order to implement any given logic function. The programming principles and the flow of the proposed automated design tool for crossbar QCA circuits are described analytically and we apply the proposed automated design method for the design of both combinatorial and sequential circuits. The obtained designs demonstrate that the proposed method is functional, easy to use, and provides the desired QCA circuit design unification