Study of Hybrid Localization Noncooperative Scheme in Wireless Sensor Network

Sumitra, Irfan Dwiguna; R, Hou; Supatmi, Sri

doi:10.1155/2017/6596943

Cited by 3 publications

(1 citation statement)

References 34 publications

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“…Wireless sensor network applications have received wide attention in the past years [11,12]. The lifespan of a wireless sensor network is crucial to the success of an application.…”

Section: Related Workmentioning

confidence: 99%

Wireless Charging Deployment in Sensor Networks

Lai

Hsiang

2019

Sensors

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Charging schemes utilizing mobile wireless chargers can be applied to prolong the lifespan of a wireless sensor network. In considering charging schemes with mobile chargers, most current studies focus on charging each sensor from a single position, then optimizing the moving paths of the chargers. However, in reality, a wireless charger may charge the same sensor from several positions in its path. In this paper we consider this fact and seek to minimize both the number of charging locations and the total required charging time. Two charging plans are developed. The first plan considers the charging time required by each sensor and greedily selects the charging service positions. The second one is a two-phase plan, where the number of charging positions is first minimized, then minimum charging times are assigned to every position according to the charging requirements of the nearby sensors. This paper also corrects a problem neglected by some studies in minimizing the number of charging service positions and further provides a corresponding solution. Empirical studies show that compared with other minimal clique partition (MCP)-based methods, the proposed charging plan may save up to 60% in terms of both the number of charging positions and the total required charging time.

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“…Wireless sensor network applications have received wide attention in the past years [11,12]. The lifespan of a wireless sensor network is crucial to the success of an application.…”

Section: Related Workmentioning

confidence: 99%

Wireless Charging Deployment in Sensor Networks

Lai

Hsiang

2019

Sensors

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Energy-Efficient Tracking and Localization of Objects in Wireless Sensor Networks

et al. 2018

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Improved Chan Algorithm Based Optimum UWB Sensor Node Localization Using Hybrid Particle Swarm Optimization

et al. 2022

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The localization of Wireless sensor networks (WSNs) has been recognized as one of the most challenging problems to overcome. Thus, much work has been given to solving this difficult problem. In emergency services, navigational systems, civil/military surveillance etc., locating the signal source in a WSN is essential. A novel approach for sensor node localization using range-based localization methodology has been proposed to overcome this issue. The problem is expressed in the form of a maximum probability distribution function. The use of an RSSI-based Time Difference of Arrival (TDOA) measurement model, along with the Chan algorithm, is used to find the coordinates of unknown nodes has been proposed. With the help of ultra-wideband, this research aims to develop new and precise localization algorithms for wireless sensor networks (WSNs). This work offers localization using two-hybrid localization algorithms, i.e., ELPSO (Ensemble learning particle swarm optimization) and PSO-BPNN (Back-propagation neural network optimized by particle swarm optimization). Further, the error optimization accuracy has been compared between those algorithms using simulations. The proposed techniques consistently offer a better localization accuracy than the conventional algorithms available in the literature. The new localization methods with optimal techniques reduce the error value to a minimal distance. The distance value of localization error is nearly2.7cms compared to other designs from the literature. It is noted as significantly less.

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Study of Hybrid Localization Noncooperative Scheme in Wireless Sensor Network

Cited by 3 publications

References 34 publications

Wireless Charging Deployment in Sensor Networks

Wireless Charging Deployment in Sensor Networks

Energy-Efficient Tracking and Localization of Objects in Wireless Sensor Networks

Improved Chan Algorithm Based Optimum UWB Sensor Node Localization Using Hybrid Particle Swarm Optimization

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