Sensor network connectivity models

Abstract

Introduction: One of the key areas in the research of wireless sensor networks is studying the ways to increase the battery lifeby saving energy in individual devices. The article introduces and discusses a new energy-efficient stochastic measure of the qualityparameter for a wireless sensor network – connectivity, which reflects the ability of a network to establish connections betweenits elements within the boundaries of the sensor field in real time, at a certain level of the sensor device battery charge. Purpose:Identifying the interdependence between the probability-time and probability-energy characteristics, as well as the influence, on thesecharacteristics, of such parameters as geometric dimensions, distribution model of sensor devices within the sensor field, networktopology and message routing algorithms. Results: A new stochastic characteristic of wireless sensor network functioning quality isproposed, called connectivity. It encompasses the spatial, temporal and energy characteristics of the network, making it possible todescribe, from a general point of view, a wide range of problems which arise when you study the functioning of wireless networksat the stages of data collecting, distributing and processing by the sensors. Stochastic connectivity indicators are introduced forwireless sensor networks, describing a network as a whole and allowing you to investigate the delay and blocking of the informationexchange, taking into account the size of the sensor field and the power consumed by individual devices. Models are built for assessingthe probability of wireless sensor network connectivity, message delivery time and delivery time quantile, improving the accuracyof network quality assessments. Practical relevance: The obtained models and methods are supposed to be used in digitalization ofagricultural organizations and in the educational process at Knyagininsky University.