A survey on various static and mobile base stations and wireless charging of sensor nodes in WSNs

Ahmad, Hifzan; Kohli, Narendra

doi:10.1109/iccn.2015.4

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…This method gained almost 70% of the average packet rate. The lightweight heuristic approach set the tour path planning [7,8]. Nikoletseas et al [9], Zhang and Ma [10] proposed two protocols to control the working of the charger.…”

Section: Charging Strategiesmentioning

confidence: 99%

Novel wireless charging algorithms to charge mobile wireless sensor network by using reinforcement learning

Soni

Shrivastava

2019

SN Appl. Sci.

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Generally, mobile wireless sensor network (MWSN) senses the sensitive and typical kind of events in various application areas along with the frequent mobility of sensor nodes as compared to traditional wireless sensor network. Due to mobility feature, MWSN extended the working of WSN. To design MWSN, certain key factors like energy efficiency, mobility, data routing, localization and charging strategy are involved. Mobile sensor nodes consume extra amount of energy due to mobility along with sensing and data routing task which exhaust network lifetime rapidly. In this research study, authors have proposed two wireless chargers (fixed and mobile) for sensor nodes. The main difference between fixed and mobile wireless charger is: fixed wireless charger invites mobile sensor nodes for wireless charging at base station whereas mobile wireless charger travels to the position of mobile sensor nodes for wireless charging. Both chargers fulfilled the charging request of sensor nodes efficiently. This is the first research study to propose such type of charging strategy for mobile wireless sensor network (MWSN) as per the available literature. The RL (reinforcement learning) technique is used here for optimization purpose of charging cost. These wireless chargers simulated in MATLAB enviorment and results showed that there is a significant improvement in network lifetime due to these charging strategies when compared to the existing algorithms.

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