Traversal Strategies for Wireless Power Transfer in Mobile Ad-Hoc Networks

Angelopoulos, Constantinos Marios; Buwaya, Julia; Evangelatos, Orestis; Rolim, José D. P.

doi:10.1145/2811587.2811603

Cited by 24 publications

(17 citation statements)

References 12 publications

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“…Another possible direction could be to consider the natural generalization of using multiple chargers that can move around in the network, and even be able to charge each other. This, couples (in a non-trivial way) our work together with that of Angelopoulos et al [1], and definitely deserves investigation.…”

Section: Resultssupporting

confidence: 74%

“…In general, we expect q to depend heavily on the density of the network; it should be smaller for more sparse networks. On the other hand, λ = 2 seems to nicely balance the ratio considered by MCER due to the fact that the given energy is of square order according to equation (1). Finally, parameter µ can be picked by the designer to maintain a sufficient number of agents, depending on the needs of the network, the energy of the charger, etc.…”

Section: Results and Interpretationmentioning

confidence: 99%

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Mobility-Aware, Adaptive Algorithms for Wireless Power Transfer in Ad Hoc Networks

Madhja

Nikoletseas

Voudouris

2019

Algorithms for Sensor Systems

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In this work, we investigate the interesting impact of mobility on the problem of efficient wireless power transfer in ad hoc networks. We consider a set of mobile agents (consuming energy to perform certain sensing and communication tasks), and a single static charger (with finite energy) which can recharge the agents when they get in its range. In particular, we focus on the problem of efficiently computing the appropriate range of the charger with the goal of prolonging the network lifetime. We first demonstrate (under the realistic assumption of fixed energy supplies) the limitations of any fixed charging range and, therefore, the need for (and power of) a dynamic selection of the charging range, by adapting to the behavior of the mobile agents which is revealed in an online manner. We investigate the complexity of optimizing the selection of such an adaptive charging range, by showing that two simplified offline optimization problems (closely related to the online one) are NP-hard. To effectively address the involved performance trade-offs, we finally present a variety of adaptive heuristics, assuming different levels of agent information regarding their mobility and energy.

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Section: Resultssupporting

confidence: 74%

Section: Results and Interpretationmentioning

confidence: 99%

Mobility-Aware, Adaptive Algorithms for Wireless Power Transfer in Ad Hoc Networks

Madhja

Nikoletseas

Voudouris

2019

Algorithms for Sensor Systems

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“…The authors design efficient traversal and coordination strategies to extend the network lifetime of static sensor networks. In contrast, Angelopoulos et al [31] investigate mobile ad hoc networks and a single mobile charger with infinite energy that traverses the network in order to recharge the agents as required.…”

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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“…Wireless energy transfer applications in networked environments have been lately investigated, especially in sensor and ad hoc networks. Numerous works suggest the employment of mobile wireless energy chargers in networks of sensor nodes, by combining energy transfer with data transmission and routing [8,9,23], providing distributed and centralized solutions [2,20,21], and collaborative charging schemes [13,24]. Other works focus on multi-hop energy transfer in stationary networks [17,22], as well as UAV-assisted charging of ground sensors [7,10].…”

Section: Related Workmentioning

confidence: 99%

“…Without loss of generality, consider now a variation of P OWS (adapted from the original version for β = 0 to the case of β > 0) according to which, whenever two agents u, u interact, the agent with the largest amount of energy transfers |ε u −ε u | 2 energy to the other. 2 We now have that, after any significant energy exchange step, i.e., an interaction of u m with any other agent, say x, according to protocol P OWS , the new energy level of u m becomes m 2 (1 − β), the new energy level of x becomes m 2 , while the energy levels of all other agents remain the same. Therefore, the new total energy in the population becomes m 2 − m − β 2 m, and the new total variation distance becomes 3…”

Section: Energy Transfer With Lossmentioning

confidence: 99%

Interactive Wireless Charging for Energy Balance

Nikoletseas

Raptis

Raptopoulos

2016

2016 IEEE 36th International Conference on Distributed Computing Systems (ICDCS)

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We study how to efficiently transfer energy wirelessly in ad hoc networks of battery-limited devices, toward prolonging their lifetime. In contrast to the stateof-the-art, we assume a much weaker population of distributed devices which are exchanging energy in a "peer to peer", bi-directional manner with each other, without any special charger nodes. We address a quite general case of diverse energy levels and priorities in the network and study the problem of how the system can efficiently reach a weighted energy balance state distributively, under both loss-less and lossy power transfer assumptions. Three protocols are designed, analyzed, and evaluated, achieving different performance trade-offs between energy balance quality, convergence time, and energy efficiency.

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Traversal Strategies for Wireless Power Transfer in Mobile Ad-Hoc Networks

Cited by 24 publications

References 12 publications

Mobility-Aware, Adaptive Algorithms for Wireless Power Transfer in Ad Hoc Networks

Mobility-Aware, Adaptive Algorithms for Wireless Power Transfer in Ad Hoc Networks

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

Interactive Wireless Charging for Energy Balance

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