SELF-CONFIGURING LOCALIZATION ALGORITHMS IN WIRELESS SENSOR NETWORKS: PROBLEMS AND ISSUES IN MOBILE ROBOT APPLICATIONS

2011 ◽  
Author(s):  
MOHAMMAD MEHDI SANAATIYAN ◽  
HAMID HASSANPOUR
Author(s):  
VINOD KUMAR ◽  
SATYENDRA YADAV ◽  
ASHUTOSH KUMAR SINGH

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.


Author(s):  
Dan Pescaru ◽  
Daniel-Ioan Curiac

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.


2019 ◽  
Vol 25 (1) ◽  
pp. 87-99
Author(s):  
Hamid Reza Sharifi ◽  
Hamid Haj Seyyed Javadi ◽  
Ali Moeini ◽  
Mehdi Hosseinzadeh

Author(s):  
Santosh Ashokrao Darade ◽  
M. Akkalakshmi

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.


2020 ◽  
Vol 14 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Amanpreet Kaur ◽  
Padam Kumar ◽  
Govind P. Gupta

Localization problem has gained a significant attention in the field of wireless sensor networks in order to support location-based services or information such as supporting geographic routing protocols, tracking events, targets, and providing security protection techniques. A number of variants of DV-Hop-based localization algorithms have been proposed and their performance is measured in terms of localization error. In all these algorithms, while determining the location of a non-anchor node, all the anchor nodes are taken into consideration. However, if only the anchors close to the node are considered, it will be possible to reduce the localization error significantly. This paper explores the effect of the close anchors in the performance of the DV-Hop-based localization algorithms and an improvement is proposed by considering only the closest anchors. The simulation results show that considering closest anchors for estimation of the location reduces localization error significantly as compared to considering all the anchors.


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