Abstract
The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among Industrial IoT sense Node (IISN). ESP8266 are IISNs connected to the Internet by means of a hub to share their information. In this article, a light-diffusion algorithm in WSN to connect all the IISNs is designed, based on the Peano fractal and swarm intelligence, i.e., without using a hub, simply sharing parameters with two adjacent IINSs, assuming that any IISN knows the parameters of the rest of these devices, even if they are not adjacent. We simulated the performance of our algorithm and compared it with other state-of-the-art protocols, finding that our proposal generates a longer lifetime of the IIoT network when few IISNs were connected. Thus, there is a saving-energy of approximately 5% but with 64 nodes there is a saving of more than 20%, because the IIoT network can grow in a way and the proposed topology does not impact in a linear way but , which balances energy consumption throughout the IIoT network.
Highlights
Advances in technology at different times have given rise to three industrial revolutions, communication systems, intelligent robots, and the Internet of Things (IoT), which are thought to lead humanity to the fourth-industrial revolution by connecting devices, people, data, and processes.IoT is a new generation of networks made up of several elements for the identification, perception, communication, computing, services, and semantics of the information obtained from the environment, allowing connectivity between the digital and the physical world using different technologies [1,2].In 2020, IoT is expected to provide a huge amount of intelligence available in the cloud to billions of mobile devices, delivering an enormous amount of new values with more than 55 million applications available to almost any human
The growth in energy savings is because the Industrial Internet of Things (IIoT) network can grow in a 3n way, and the proposed topology does not impact in a linear way but log3, which balances energy consumption throughout the IIoT network, as if this topology understood where there is a need for more or less energy and balances it
Since the routing distributed learning automaton (RRDLA) [15], delay-energy tradeoff with reliable communication (DETR) [9], and reliable and energy-efficient routing (REER) [8] algorithms carried out simulations using the network simulator software ns-2 [33], these works did not report their energy consumption data, it is only possible to compare these algorithms with the present proposal in terms of reliability requirements or node density, and it is impossible to compare them in terms of energy efficiency as they are logical and not physical topologies
Summary
Advances in technology at different times have given rise to three industrial revolutions, communication systems, intelligent robots, and the Internet of Things (IoT), which are thought to lead humanity to the fourth-industrial revolution by connecting devices, people, data, and processes. In 2020, IoT is expected to provide a huge amount of intelligence available in the cloud to billions of mobile devices, delivering an enormous amount of new values with more than 55 million applications available to almost any human This implies an interconnection of four million people over the world [3]. This article proposes an algorithm that effectively allows the transmission and distribution of parameters in all devices connected to WSN. This makes it necessary to use many networked sensors to obtain information in real time and, an efficient IIoT network, which in turn allows the protocol proposed in this work to be applied in an industrial plant. Appendix A contains a list of abbreviations and notations to facilitate the reading of this work
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