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H. Beigy and M. R. Meybodi, “A Self-Organizing Channel Assignment Algorithm: A Cellular Learning Automata Approach,” Intelligent Data Engineering and Automated Learning, Vol. 2690, 2003, pp. 119-126.

has been cited by the following article:

• TITLE: Simulation of Topology Control Algorithms in Wireless Sensor Networks Using Cellular Automata

  AUTHORS: Stavros Athanassopoulos, Christos Kaklamanis, Gerasimos Kalfountzos, Panagiota Katsikouli, Evi Papaioannou

  KEYWORDS: Cellular Automata; Neighbourhood; Topology Control; WSN; Simulation; Matlab; Java; Python

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.6 No.7, July 11, 2013

  ABSTRACT: We use cellular automata for simulating a series of topology control algorithms in Wireless Sensor Networks (WSNs) using various programming environments. A cellular automaton is a decentralized computing model providing an excellent platform for performing complex computations using only local information. WSNs are composed of a large number of distributed wireless sensor nodes operating on batteries. The objective of the topology control problem in WSNs is to select an appropriate subset of nodes able to monitor a region at a minimum energy consumption cost and, therefore, extend network lifetime. Herein, we present topology control algorithms based on the selection—in a deterministic or randomized way—of an appropriate subset of sensor nodes that must remain active. We use cellular automata for conducting simulations in order to evaluate the performance of these algorithms and investigate the effect/role of the neighbourhood selection in the efficient application of our algorithms. Furthermore, we implement our simulations in Matlab, Java and Python in order to investigate in which ways the selection of an appropriate programming environment can facilitate experimentation and can result in more efficient application of our algorithms.