As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being exp...As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being explored as low cost alternatives to range based localization techniques. To manage cost, few location aware nodes, called anchors are deployed in the wireless sensor environment. It is from these anchors that all other free nodes are expected to estimate their own positions. This paper therefore, takes a look at some of the foremost Range-free localization algorithms, detailing their limitations, with a view to proposing a modified form of Centroid Localization Algorithm called Reach Centroid Localization Algorithm. The algorithm employs a form of anchor nodes position validation mechanism by looking at the consistency in the quality of Received Signal Strength. Each anchor within the vicinity of a free node seeks to validate the actual position or proximity of other anchors within its vicinity using received signal strength. This process mitigates multipath effects of radio waves, particularly in an enclosed environment, and consequently limits localization estimation errors and uncertainties. Centroid Localization Algorithm is then used to estimate the location of a node using the anchors selected through the validation mechanism. Our approach to localization becomes more significant, particularly in indoor environments, where radio signal signatures are inconsistent or outrightly unreliable. Simulated results show a significant improvement in localization accuracy when compared with the original Centroid Localization Algorithm, Approximate Point in Triangulation and DV-Hop.展开更多
Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typical...Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.展开更多
In this paper, the self-localization problem is studied. It is one of the key technologies in wireless sensor networks (WSNs). And five localization algorithms: Centroid algorithm, Amorphous algorithm, DV-hop algorith...In this paper, the self-localization problem is studied. It is one of the key technologies in wireless sensor networks (WSNs). And five localization algorithms: Centroid algorithm, Amorphous algorithm, DV-hop algorithm, APIT algorithm and Bounding Box algorithm are discussed. Simulation of those five localization algorithms is done by MATLAB. The simulation results show that the positioning error of Amorphous algorithm is the minimum. Considering economy and localization accuracy, the Amorphous algorithm can achieve the best localization performance under certain conditions.展开更多
Localization technology is an important support technology for WSN(Wireless Sensor Networks). The centroid algorithm is a typical range-free localization algorithm, which possesses the advantages such as simple locali...Localization technology is an important support technology for WSN(Wireless Sensor Networks). The centroid algorithm is a typical range-free localization algorithm, which possesses the advantages such as simple localization principle and easy realization. However, susceptible to be influenced by the density of anchor node and uniformity of deployment, its localization accuracy is not high. We study localization principal and error source of the centroid algorithm. Meanwhile, aim to resolve the problem of low localization accuracy, we proposes a new double-radius localization algorithm, which makes WSN node launch periodically two rounded communications area with different radius to enable localization region to achieve the second partition, thus there are some small overlapping regions which can narrow effectively localization range of unknown node. Besides, partition judgment mechanism is proposed to ascertain the area of unknown node, and then the localization of small regions is realized by the centroid algorithm. Simulation results show that the algorithm without adding additional hardware and anchor nodes but increases effectively localization accuracy and reduces the dependence on anchor node.展开更多
This study used Topological Weighted Centroid (TWC) to analyze the Coronavirus outbreak in Brazil. This analysis only uses latitude and longitude in formation of the capitals with the confirmed cases on May 24, 2020 t...This study used Topological Weighted Centroid (TWC) to analyze the Coronavirus outbreak in Brazil. This analysis only uses latitude and longitude in formation of the capitals with the confirmed cases on May 24, 2020 to illustrate the usefulness of TWC though any date could have been used. There are three types of TWC analyses, each type having five associated algorithms that produce fifteen maps, TWC-Original, TWC-Frequency and TWC-Windowing. We focus on TWC-Original to illustrate our approach. The TWC method without using the transportation information predicts the network for COVID-19 outbreak that matches very well with the main radial transportation routes network in Brazil.展开更多
文摘As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being explored as low cost alternatives to range based localization techniques. To manage cost, few location aware nodes, called anchors are deployed in the wireless sensor environment. It is from these anchors that all other free nodes are expected to estimate their own positions. This paper therefore, takes a look at some of the foremost Range-free localization algorithms, detailing their limitations, with a view to proposing a modified form of Centroid Localization Algorithm called Reach Centroid Localization Algorithm. The algorithm employs a form of anchor nodes position validation mechanism by looking at the consistency in the quality of Received Signal Strength. Each anchor within the vicinity of a free node seeks to validate the actual position or proximity of other anchors within its vicinity using received signal strength. This process mitigates multipath effects of radio waves, particularly in an enclosed environment, and consequently limits localization estimation errors and uncertainties. Centroid Localization Algorithm is then used to estimate the location of a node using the anchors selected through the validation mechanism. Our approach to localization becomes more significant, particularly in indoor environments, where radio signal signatures are inconsistent or outrightly unreliable. Simulated results show a significant improvement in localization accuracy when compared with the original Centroid Localization Algorithm, Approximate Point in Triangulation and DV-Hop.
文摘Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition.
文摘In this paper, the self-localization problem is studied. It is one of the key technologies in wireless sensor networks (WSNs). And five localization algorithms: Centroid algorithm, Amorphous algorithm, DV-hop algorithm, APIT algorithm and Bounding Box algorithm are discussed. Simulation of those five localization algorithms is done by MATLAB. The simulation results show that the positioning error of Amorphous algorithm is the minimum. Considering economy and localization accuracy, the Amorphous algorithm can achieve the best localization performance under certain conditions.
文摘Localization technology is an important support technology for WSN(Wireless Sensor Networks). The centroid algorithm is a typical range-free localization algorithm, which possesses the advantages such as simple localization principle and easy realization. However, susceptible to be influenced by the density of anchor node and uniformity of deployment, its localization accuracy is not high. We study localization principal and error source of the centroid algorithm. Meanwhile, aim to resolve the problem of low localization accuracy, we proposes a new double-radius localization algorithm, which makes WSN node launch periodically two rounded communications area with different radius to enable localization region to achieve the second partition, thus there are some small overlapping regions which can narrow effectively localization range of unknown node. Besides, partition judgment mechanism is proposed to ascertain the area of unknown node, and then the localization of small regions is realized by the centroid algorithm. Simulation results show that the algorithm without adding additional hardware and anchor nodes but increases effectively localization accuracy and reduces the dependence on anchor node.
文摘This study used Topological Weighted Centroid (TWC) to analyze the Coronavirus outbreak in Brazil. This analysis only uses latitude and longitude in formation of the capitals with the confirmed cases on May 24, 2020 to illustrate the usefulness of TWC though any date could have been used. There are three types of TWC analyses, each type having five associated algorithms that produce fifteen maps, TWC-Original, TWC-Frequency and TWC-Windowing. We focus on TWC-Original to illustrate our approach. The TWC method without using the transportation information predicts the network for COVID-19 outbreak that matches very well with the main radial transportation routes network in Brazil.
