A novel localization algorithm for large scale wireless sensor networks

2014 ◽  
Vol 45 ◽  
pp. 32-46 ◽  
Author(s):  
Haidar Safa
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Wireless Sensor ◽  
Localization Algorithm

Advanced Sequence-Based Localization Algorithm in Wireless Sensor Networks

2014 ◽  
Vol 651-653 ◽  
pp. 387-390 ◽  
Author(s):  
Fu Bin Zhou ◽  
Shao Li Xue
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Measuring Devices ◽  
Localization Algorithms ◽  
Positioning Algorithm ◽  
Range Free

As an important application of Internet of Things , Wireless Sensor Networks utilized in surveillance and other case.Localization of nodes in wireless sensor networks is the prerequisite and base of target tracking in some surveillance applications, so localization error of sensor nodes is a key. However, due to limited energy, unreliable link and limited communication ranges of sensor nodes, high accurate positioning is difficult to achieve, which made it hot and full of challenging for wireless sensor nodes to localize without any auxiliary facilities. Range-based localization algorithm , could achieve good accuracy but require measuring devices, thus it is not appropriate for large-scale wireless sensor networks.So range-free localization algorithms are more popular.This paper analyses the algorithms in range-free localization,and proposed Advanced Sequence-Based Localization algorithm to improve the performance of positioning algorithm in wireless sensor network.

scholarly journals A Time Difference of Arrival-based Localization Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 12 (11) ◽  
pp. 80 ◽  
Author(s):  
Songbo Ji
Keyword(s):  
Wireless Sensor Networks ◽  
Electromagnetic Wave ◽  
Sensor Networks ◽  
Large Scale ◽  
Time Difference ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Time Difference Of Arrival ◽  
Positioning Accuracy ◽  
Simulation Results

<p class="Abstract"><span lang="EN-US">Aimed at solving the problem of local divergence and low data accuracy, this paper introduces a new Time Difference of Arrival(TDOA)-based localization algorithm (TBL) for the large-scale, high-density wireless sensor networks which are designed for real-time surveillance and unexpected incidents management. In particular, several means to improve the accuracy of distance measurement are investigated, and the TDOA method, based on the sound wave and electromagnetic wave to locate in the large-scale WSN, is discussed. Also, the well-designed circular location process has the advantage of better positioning accuracy and coverage percentage. Simulation results have confirmed the effectiveness of the formed TBL algorithm.</span></p>

scholarly journals A Mobile Anchor Assisted Localization Algorithm Based on Regular Hexagon in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Guangjie Han ◽  
Chenyu Zhang ◽  
Jaime Lloret ◽  
Lei Shu ◽  
Joel J. P. C. Rodrigues
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Regular Hexagon ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Location Aware ◽  
Mobile Anchor ◽  
Monitoring Area

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints of cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use several mobile anchors which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. This paper proposes a mobile anchor assisted localization algorithm based on regular hexagon (MAALRH) in two-dimensional WSNs, which can cover the whole monitoring area with a boundary compensation method. Unknown nodes calculate their positions by using trilateration. We compare the MAALRH with HILBERT, CIRCLES, and S-CURVES algorithms in terms of localization ratio, localization accuracy, and path length. Simulations show that the MAALRH can achieve high localization ratio and localization accuracy when the communication range is not smaller than the trajectory resolution.

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