847 research outputs found
Wireless Power Transfer and Data Collection in Wireless Sensor Networks
In a rechargeable wireless sensor network, the data packets are generated by
sensor nodes at a specific data rate, and transmitted to a base station.
Moreover, the base station transfers power to the nodes by using Wireless Power
Transfer (WPT) to extend their battery life. However, inadequately scheduling
WPT and data collection causes some of the nodes to drain their battery and
have their data buffer overflow, while the other nodes waste their harvested
energy, which is more than they need to transmit their packets. In this paper,
we investigate a novel optimal scheduling strategy, called EHMDP, aiming to
minimize data packet loss from a network of sensor nodes in terms of the nodes'
energy consumption and data queue state information. The scheduling problem is
first formulated by a centralized MDP model, assuming that the complete states
of each node are well known by the base station. This presents the upper bound
of the data that can be collected in a rechargeable wireless sensor network.
Next, we relax the assumption of the availability of full state information so
that the data transmission and WPT can be semi-decentralized. The simulation
results show that, in terms of network throughput and packet loss rate, the
proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular
Technolog
Efficient on-demand multi-node charging techniques for wireless sensor networks
This paper deals with wireless charging in sensor networks and explores efficient policies to perform simultaneous multi-node power transfer through a mobile charger (MC).The proposed solution, called On-demand Multi-node Charging (OMC), features an original threshold-based tour launching (TTL) strategy, using request grouping, and a path planning algorithm based on minimizing the number of stopping points in the charging tour. Contrary to existing solutions, which focus on shortening the charging delays, OMC groups incoming charging requests and optimizes the charging tour and the mobile charger energy consumption. Although slightly increasing the waiting time before nodes are charged, this allows taking advantage of multiple simultaneous charges and also reduces node failures. At the tour planning level, a new modeling approach is used. It leverages simultaneous energy transfer to multiple nodes by maximizing the number of sensors that are charged at each stop. Given its NP-hardness, tour planning is approximated through a clique partitioning problem, which is solved using a lightweight heuristic approach. The proposed schemes are evaluated in offline and on-demand scenarios and compared against relevant state-of-the-art protocols. The results in the offline scenario show that the path planning strategy reduces the number of stops and the energy consumed by the mobile charger, compared to existing offline solutions. This is with further reduction in time complexity, due to the simple heuristics that are used. The results in the on-demand scenario confirm the effectiveness of the path planning strategy. More importantly, they show the impact of path planning, TTL and multi-node charging on the efficiency of handling the requests, in a way that reduces node failures and the mobile charger energy expenditure
A Survey on Mobile Charging Techniques in Wireless Rechargeable Sensor Networks
The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the MCTs. Next, we introduce an exhaustive taxonomy of the MCTs based on various design attributes and then review the literature by categorizing it into periodic and on-demand charging techniques. In addition, we compare the state-of-the-art MCTs in terms of objectives, constraints, solution approaches, charging options, design issues, performance metrics, evaluation methods, and limitations. Finally, we highlight some potential directions for future research
Probabilistic On-Demand Charging Scheduling for ISAC-Assisted WRSNs with Multiple Mobile Charging Vehicles
The internet of things (IoT) based wireless sensor networks (WSNs) face an
energy shortage challenge that could be overcome by the novel wireless power
transfer (WPT) technology. The combination of WSNs and WPT is known as wireless
rechargeable sensor networks (WRSNs), with the charging efficiency and charging
scheduling being the primary concerns. Therefore, this paper proposes a
probabilistic on-demand charging scheduling for integrated sensing and
communication (ISAC)-assisted WRSNs with multiple mobile charging vehicles
(MCVs) that addresses three parts. First, it considers the four attributes with
their probability distributions to balance the charging load on each MCV. The
distributions are residual energy of charging node, distance from MCV to
charging node, degree of charging node, and charging node betweenness
centrality. Second, it considers the efficient charging factor strategy to
partially charge network nodes. Finally, it employs the ISAC concept to
efficiently utilize the wireless resources to reduce the traveling cost of each
MCV and to avoid the charging conflicts between them. The simulation results
show that the proposed protocol outperforms cutting-edge protocols in terms of
energy usage efficiency, charging delay, survival rate, and travel distance.Comment: Accepted for publication at the IEEE Global Communications Conference
(GLOBECOM) 202
A Hybrid Metaheuristic Algorithm for Stop Point Selection in Wireless Rechargeable Sensor Network
A wireless rechargeable sensor network (WRSN) enables charging of rechargeable sensor nodes (RSN) wirelessly through a mobile charging vehicle (MCV). Most existing works choose the MCV’s stop point (SP) at random, the cluster’s center, or the cluster head position, all without exploring the demand from RSNs. It results in a long charging delay, a low charging throughput, frequent MCV trips, and more dead nodes. To overcome these issues, this paper proposes a hybrid metaheuristic algorithm for stop point selection (HMA-SPS) that combines the techniques of the dragonfly algorithm (DA), firefly algorithm (FA), and gray wolf optimization (GWO) algorithms. Using FA and GWO techniques, DA predicts an ideal SP using the run-time metrics of RSNs, such as energy, delay, distance, and trust factors. The simulated results demonstrate faster convergence with low delay and highlight that more RSNs can be recharged with fewer MCV visits, further enhancing energy utilization, throughput, network lifetime, and trust factor
Safe and Secure Wireless Power Transfer Networks: Challenges and Opportunities in RF-Based Systems
RF-based wireless power transfer networks (WPTNs) are deployed to transfer
power to embedded devices over the air via RF waves. Up until now, a
considerable amount of effort has been devoted by researchers to design WPTNs
that maximize several objectives such as harvested power, energy outage and
charging delay. However, inherent security and safety issues are generally
overlooked and these need to be solved if WPTNs are to be become widespread.
This article focuses on safety and security problems related WPTNs and
highlight their cruciality in terms of efficient and dependable operation of
RF-based WPTNs. We provide a overview of new research opportunities in this
emerging domain.Comment: Removed some references, added new references, corrected typos,
revised some sections (mostly I-B and III-C
Optimal Save-Then-Transmit Protocol for Energy Harvesting Wireless Transmitters
In this paper, the design of a wireless communication device relying
exclusively on energy harvesting is considered. Due to the inability of
rechargeable energy sources to charge and discharge at the same time, a
constraint we term the energy half-duplex constraint, two rechargeable energy
storage devices (ESDs) are assumed so that at any given time, there is always
one ESD being recharged. The energy harvesting rate is assumed to be a random
variable that is constant over the time interval of interest. A
save-then-transmit (ST) protocol is introduced, in which a fraction of time
{\rho} (dubbed the save-ratio) is devoted exclusively to energy harvesting,
with the remaining fraction 1 - {\rho} used for data transmission. The ratio of
the energy obtainable from an ESD to the energy harvested is termed the energy
storage efficiency, {\eta}. We address the practical case of the secondary ESD
being a battery with {\eta} < 1, and the main ESD being a super-capacitor with
{\eta} = 1. The optimal save-ratio that minimizes outage probability is
derived, from which some useful design guidelines are drawn. In addition, we
compare the outage performance of random power supply to that of constant power
supply over the Rayleigh fading channel. The diversity order with random power
is shown to be the same as that of constant power, but the performance gap can
be large. Furthermore, we extend the proposed ST protocol to wireless networks
with multiple transmitters. It is shown that the system-level outage
performance is critically dependent on the relationship between the number of
transmitters and the optimal save-ratio for single-channel outage minimization.
Numerical results are provided to validate our proposed study.Comment: This is the longer version of a paper to appear in IEEE Transactions
on Wireless Communication
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