Algoritmo de localização utilizando o método MMSE para o cálculo de posição de nós sensores em uma rede móvel

Abstract

Applications that use sensor networks depends on knowing which position where each node is arranged in a particular geographic area. For this, there are algorithms that perform location calculations to estimate the exact position of each node. These algorithms use a different techniques and metrics to make it, for example: the measure of intensity of signal transmission between two nodes. In a sensor network with high density, it becomes infeasible to manually configuring each node positioning. To optimize this task, was developed different types of localization algorithms, with application in several areas, such as tracking, routing protocols, network density control, self organizing, monitoring remote areas, precision agriculture, among others. The basis for localization algorithms is to have a number of reference points, where from these, is calculated the position of each node. A network of sensors with a greater number of reference points, one can consider a network with higher accuracy for calculating the position of its nodes. This is due to being closer to the reference points. However, may result in a higher processing, thereby having a higher energy consumption. Developing a location algorithm with fewer reference points is not a trivial problem. This, because will increase the distance between the node and the reference point and may thereby inserting errors in the measurement of the criteria for the calculation of positioning. For calculation purposes, there are two types of algorithms, algorithms for centralized processing and distributed processing algorithms. Each with its advantages and disadvantages that will be discussed in this paper. The location algorithm is based on a calculation according to data coordinates in a coordinate system, which is raised according to the technique used to denote the distance between the sensor node and the reference points. The importance of knowing the location of each node, there is the need to know exactly where a particular event is occurring. For example, a forest that occupies a large geographic area is to principles of fire at different locations.