MODELS OF SENSOR NETWORKS WITH CORRELATED SOURCES

Abstract

One of the important scientific directions in the research of the Internet of things is the analysis of monitoring systems for random events with correlated sources based on random multiple access. Taking into account the correlation of data from nearby sensors increases the energy efficiency of the system and ensures the stability of its operation. There are various models of such systems, but there is no connection between them. The purpose of this paper is to develop a unified system of assumptions for describing models of systems with random access and correlated sources. In this paper, the main scenarios of the Internet of Things are described and a scenario with a large number of sensors is selected, on the basis of which systems for monitoring random events are built. A review of papers in which systems with random access and correlated sources are studied is carried out. A method for separating existing models into two classes is proposed: models with the arrival of events and models with the arrival of users. A unified system of assumptions for models of both classes is proposed, which allows describing and comparing different models with each other. A simplified model of a system with random access and dependent sources is presented, which retains the main properties of the Internet of things systems. This model is easy to analyze and has no "edge effects". A brief overview of the research on the average age of information in various data transmission systems is also given. The results of the review showed that this characteristic is important for systems with correlated sources, but at the moment it is practically not studied in such systems. The proposed system of assumptions for describing various models with correlated sources and the presented simplified model with a circle can be used in the theoretical analysis of monitoring systems for random events.