Wireless Power Transfer Protocols in Sensor Networks: Experiments and Simulations

Nikoletseas, Sotiris; Raptis, Theofanis P.; Souroulagkas, Alexandros; Tsolovos, Dimitrios

doi:10.3390/jsan6020004

Cited by 31 publications

(12 citation statements)

References 28 publications

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“…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. The first protocol performs good charging efficiency throughout the experiments and second protocol performed uniform distribution of energy.…”

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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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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“…Mobile ad hoc networks have been extensively studied in the literature under different perspectives. Angelopoulos et al [38] studied mobile ad hoc networks that consist of multiple static chargers. They designed and experimentally evaluated two algorithms that find which of the chargers should be active at each round, in order to maximize charging efficiency and achieve energy balance, respectively.…”

Section: A Related Workmentioning

confidence: 99%

On Electromagnetic Radiation Control for Wireless Power Transfer in Adhoc Communication Networks: Key Issues and Challenges

Gabriel¹,

Madhja²,

Nikoletseas³

et al. 2019

IEEE Access

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In this paper, we provide a holistic overview of the aspect of electromagnetic radiation (EMR) and its efficient control in wireless communication networks. Especially, we focus on the emerging technology of wireless power transfer (WPT). Our global perspective is to suggest methods for the effective control of EMR while keeping at high levels the QoS experienced by users as well as the charging efficiency of WPT. First, we provide formal definitions of EMR in wireless communications and propose related performance metrics and EMR evaluations in wireless communication networks. Then, we focus on EMR control in efficient wireless power transfer, under different WPT models. For the well-known scalar model, we assume finite energy reserves and batteries, and introduce the low radiation efficient charging problem. For this problem, we identify its computational complexity and provide efficient algorithms and heuristics. A vectorial model of WPT is then employed, allowing a more precise management of radiation, via directly exploiting interesting super-additive and cancellative phenomena of received power; we provide algorithms which achieve satisfactory tradeoffs of charging efficiency and radiation. Then, we present a more futuristic model and the method of peer-to-peer wireless power transfer where no strong, central charger stations are used, thus keeping radiation at almost zero levels. Another method of controlling EMR in the case of mobile nodes is adapting the charger change in a dynamic, on-line way so as to avoid unnecessarily large fixed changing ranges. Finally, we discuss some future challenges and related research directions, toward efficiently combining high WPT provisioning and low EMR. Such directions include the effective management of mobility in the network, the use of diverse WPT signal phase-configuration as well as efficient chargers' scheduling strategies.

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“…The thermal or magnetic field will be suitable for the power transfer in determining the water quality in pipelines. An energy efficient scheduling scheme for power transfer and a wireless power transfer protocol were some of the recent developments in energy management [51], [52]. The wireless power transfer protocol consists of two protocols, one for balancing the energy and the other one for checking the power of each sensor nodes for energy transfer.…”

Section: Energy Managementmentioning

confidence: 99%

IoT Technology for Smart Water System

Radhakrishnan

2018

2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference On

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A serious drop in ensuring the water quality in the distribution system is a factor that affects public health. This could lead to increase in biological and non-biological contents, change in colour and odour of the water. These contaminants cause a serious threat to the whole water ecosystem. The conventional methods of analyzing the water quality require much time and labour. So there is a need to monitor and protect the water with a real time water quality monitoring system in order to make active measurements to reduce contamination. The growth of the technology had helped in developing efficient methods to solve many serious issues in real-time. Internet of things (IoT) has achieved a great focus due to its faster processing and intelligence. This paper focuses on discussing the architecture, applications and need of IoT in water management system.

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Wireless Power Transfer Protocols in Sensor Networks: Experiments and Simulations

Cited by 31 publications

References 28 publications

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

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

On Electromagnetic Radiation Control for Wireless Power Transfer in Adhoc Communication Networks: Key Issues and Challenges

IoT Technology for Smart Water System

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