doi: 10.17586/2226-1494-2018-18-5-843-849


METHODS OF LIFE CYCLE INCREASE FOR THE INTERNET OF THINGS

T. M. Tatarnikova, I. N. Dziubenko


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Tatarnikova T.M., Dziubenko I.N. Methods of life cycle increase for the Internet of things. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2018, vol. 18, no. 5, pp. 843–849 (in Russian). doi: 10.17586/2226-1494-2018-18-5-843-849


Abstract
Subject of Research. The paper proposes models that make it possible to extend the Internet of things life cycle as a result of the sensory field clustering and the transfer of the interaction functions from the base station to the head node of the cluster. The efficiency of the clustered wireless sensor network was evaluated in comparison with the nonclustered one in terms of the residual energy parameter and the network lifetime. Methods. The Internet of things sensory field clustering method was used. The method is based on the idea of​equiprobable rotation of the head nodes, taking into account the level of nodes residual energy and the distance from the sensor devices to the head node. The time division multiple accessmechanism in the interaction of sensory devices with the head node of the cluster minimizes the probability of data transmission collision. Simulation modeling provides a tool for selecting clustering parameters while providing the required characteristics of the functioning of the Internet of things. Main Results. A wireless sensor network simulation model is proposed, which can find application in the Internet of things designing tasks. Estimations are given demonstrating the clustering expediency of  the Internet of things sensory field at sensory field sizes exceeding the distance from the most remote node to the base station. Practical Relevance.Sensor field clustering provides the increase of the Internet of things life cycle. The proposed models will be useful in the early stages of the Internet of things design.

Keywords: wireless sensor networks, Internet of things, clustering, self-organization, head node, base station, sensor field, life cycle, residual energy, Time Division Multiple Access

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