Optimizing a Software-Defined Network by means of the Peano Curve L-System

Oswaldo Morales Matamoros, Jesús Jaime Moreno Escobar, Ricardo Tejeida Padilla, Ana Gabriela Ramírez Gutiérrez, Pedro Flores Jiménez


At the present, millions of Microcontroller Units (MCU) are connected simultaneously in a digitally way to be our life more comfortable. These MCU not only interact with us turning on lights or identifying movement in a House but also they perform small and specific tasks such as sensing different parameters such as temperature, humidity, CO2, adjustment of the environmental lights. There is a huge kind of these MCU called small general purpose devices, ESP8266 or RaspberryPi3 or any kind of Internet of Things (IoT) devices, which are connected to internet by means of a central node for sharing their information. The main goal of this article is to design a decentralized IoT network topology in order to connect all the MCU or nodes, based on the fractal Peano, i.e., without using a central one, just sharing some parameters with two adjacent nodes, taking into account that any member of these nodes knows the parameters of the rest of these devices even if they are not adjacent nodes. Specifically, with the proposed network we can access to the entire IoT network in real time in a dynamic way since the topology of the network can be adapted and reconfigured when a new node is added using tools of Artificial Intelligence for its application in a Smart City. This proposal allows to save energy, increasing the time of life of the IoT network, when more wireless small-devices are connected and sensing parameters.


Embedded systems, swarm intelligence, Peano curve, ESP8266, RaspberryPi3, software defined network

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