Noise-aware localization algorithms for wireless sensor networks based on multidimensional scaling and adaptive Kalman filtering

2017 ◽  
Vol 101 ◽  
pp. 57-68 ◽  
Author(s):  
Xuming Fang ◽  
Zonghua Jiang ◽  
Lei Nan ◽  
Lijun Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Multidimensional Scaling ◽  
Kalman Filtering ◽  
Wireless Sensor ◽  
Localization Algorithms

scholarly journals IMPROVING LOCALIZATION ACCURACY IN WIRELESS SENSOR NETWORKS

2013 ◽  
pp. 152-156
Author(s):  
VINOD KUMAR ◽  
SATYENDRA YADAV ◽  
ASHUTOSH KUMAR SINGH
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sequential Monte Carlo ◽  
Fundamental Problem ◽  
Geographical Location ◽  
Wireless Sensor ◽  
Localization Accuracy ◽  
Localization Algorithms ◽  
Direction Of Movement

The most fundamental problem of wireless sensor networks is localization (finding the geographical location of the sensors). Most of the localization algorithms proposed for sensor networks are based on Sequential Monte Carlo (SMC) method. To achieve high accuracy in localization it requires high seed node density and it also suffers from low sampling efficiency. There are some papers which solves this problems but they are not energy efficient. Another approach The Bounding Box method was used to reduce the scope of searching the candidate samples and thus reduces the time for finding the set of valid samples. In this paper we propose an energy efficient approach which will further reduce the scope of searching the candidate samples, so now we can remove the invalid samples from the sample space and we can introduce more valid samples to improve the localization accuracy. We will consider the direction of movement of the valid samples, so that we can predict the next position of the samples more accurately, hence we can achieve high localization accuracy.

Data Processing and Exchange Challenges in Video-Based Wireless Sensor Networks

2014 ◽  
pp. 196-215
Author(s):  
Dan Pescaru ◽  
Daniel-Ioan Curiac
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Processing ◽  
Data Exchange ◽  
Video Data ◽  
Wireless Sensor ◽  
Localization Algorithms ◽  
Innovative Solutions ◽  
Communication Efficiency ◽  
Specific Localization

This chapter presents the main challenges in developing complex systems built around the core concept of Video-Based Wireless Sensor Networks. It summarizes some innovative solutions proposed in scientific literature on this field. Besides discussion on various issues related to such systems, the authors focus on two crucial aspects: video data processing and data exchange. A special attention is paid to localization algorithms in case of random deployment of nodes having no specific localization hardware installed. Solutions for data exchange are presented by highlighting the data compression and communication efficiency in terms of energy saving. In the end, some open research topics related with Video-Based Wireless Sensor Networks are identified and explained.

Residual design of sink localization algorithms for wireless sensor networks

2019 ◽  
Vol 25 (1) ◽  
pp. 87-99
Author(s):  
Hamid Reza Sharifi ◽  
Hamid Haj Seyyed Javadi ◽  
Ali Moeini ◽  
Mehdi Hosseinzadeh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Localization Algorithms ◽  
Residual Design

Extensive Literature Survey on Load Balancing in Software-Defined Networking

2020 ◽  
Vol 16 (2) ◽  
pp. 1-19
Author(s):  
Santosh Ashokrao Darade ◽  
M. Akkalakshmi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Monitoring Station ◽  
Extensive Literature ◽  
Localization Error ◽  
Sense Data ◽  
Localization Algorithms ◽  
Whale Optimization

The localization of underwater sensors is the most crucial task in underwater wireless sensor networks (UWSNs). The sensors, which are situated under the water, sense data from the environment, and sensed data is transmitted to the monitoring station. Although the monitoring station receives the sensed data, the data is meaningless without knowing the exact position of the sensor. Localization is the major issue in UWSN to be resolved. There are several localization algorithms available for terrestrial wireless sensor networks (WSN), but there are comparatively few localization algorithms available for UWSNs. An improved range-based localization method is introduced in this paper to discover localization issue. To evaluate the location of the target sensors, localization error is further to be reduced. The localization error is reduced by applying the whale optimization algorithm (WOA) in this technique. Simulation results demonstrate that performance metrics of the proposed approach outperform the existing work in terms of localization error and localization coverage.

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