• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.359-364
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• 2012

Harvesting energy from the environment is essential for many applications to slow down the deterioration of energy of the devices in sensor networks and in general, the network itself. Energy from the environment is an inexhaustible supply which, if properly managed and harvested from the sources, can allow the system to last for a longer period - more than the expected lifetime at the time of deployment, or even last indefinitely. The goal of this study is to develop a simple algorithm for ns-2 to simulate energy harvesting in wireless sensor network simulations. The algorithm is implemented in the energy module of the simulator. Energy harvesting algorithms have not yet been developed for ns-2. This study will greatly contribute to the existing knowledge of simulating wireless sensor networks with energy harvesting capabilities in ns-2. This paper will also serve as a basis for future research papers that make use of energy harvesting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.504-521
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• 2016

Recently, energy harvesting technology has been integrated into wireless sensor networks to ameliorate the nodes' energy limitation problem. In theory, the wireless sensor node equipped with an energy harvesting module can work permanently until hardware failures happen. However, due to the change of power supply, the traditional hierarchical network routing protocol can not be effectively adopted in energy harvesting wireless sensor networks. In this paper, we improve the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol to make it suitable for the energy harvesting wireless sensor networks. Specifically, the cluster heads are selected according to the estimation of nodes' harvested energy and consumed energy. Preference is given to the nodes with high harvested energy while taking the energy consumption rate into account. The utilization of harvested energy is mathematically formulated as a max-min optimization problem which maximizes the minimum energy conservation of each node. We have proved that maximizing the minimum energy conservation is an NP-hard problem theoretically. Thus, a polynomial time algorithm has been proposed to derive the near-optimal performance. Extensive simulation results show that our proposed routing scheme outperforms previous works in terms of energy conservation and balanced distribution.

• Journal of Semiconductor Engineering
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• v.1 no.1
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• pp.13-30
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• 2020

Radio frequency (RF) energy harvesting technology have become a reliable and promising alternative to extend the lifetime of power-constrained wireless networks by eliminating the need for batteries. This emerging technology enables the low-power wireless devices to be self-sustaining and eco-friendly by scavenging RF energy from ambient environment or dedicated energy sources. These attributes make RF energy harvesting technology feasible and attractive to an extended range of applications. However, despite being the most reliable energy harvesting technology, there are several challenges (especially power conversion efficiency, output DC voltage and sensitivity) poised for the implementation of RF energy harvesting systems. In this article, a detailed literature on RF energy harvesting technology has been surveyed to provide guidance for RF energy harvesters design. Since signal strength of the received RF power is limited and weak, high efficiency state-of-the-art RF energy harvesters are required to design for providing sufficient DC supply voltage to wireless networks. Therefore, various designs and their trade-offs with comprehensive analysis for RF energy harvesters have been discussed. This paper can serve as a good reference for the researchers to catch new research topics in the field of RF energy harvesting.

• Smart Media Journal
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• v.4 no.1
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• pp.25-32
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• 2015

Powering wireless sensors with energy harvested from the environment is coming of age due to the increasing power densities of both storage and harvesting devices and the electronics performing energy efficient energy conversion. In order to maximize the functionality of the wireless sensor network, minimize missing packets, minimize latency and prevent the waste of energy, problems like congestion and inefficient energy usage must be addressed. Many sleep-awake protocols and efficient message priority techniques have been developed to properly manage the energy of the nodes and to minimize congestion. For a WSN that is operating in a strictly energy constrained environment, an energy-efficient transmission strategy is necessary. In this paper, we present a novel transmission priority decision scheme for a heterogeneous body sensor network composed of normal nodes and an energy harvesting node that acts as a cluster head. The energy harvesting node's decision whether or not to clear a normal node for sending is based on a set of metrics which includes the energy harvesting node's remaining energy, the total harvested energy, the type of message in a normal node's queue and finally, the implementation context of the wireless sensor network.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.25-33
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• 2021

Energy-harvesting wireless sensor networks(EH-WSNs) can collect energy from the environment and overcome the technical limitations of existing power. Since the transmission distance in a wireless sensor network is limited, the data are delivered to the destination node through multi-hop routing. In EH-WSNs, the routing protocol should consider the power situations of nodes, which is determined by the remaining power and energy-harvesting rate. In addition, in applications such as environmental monitoring, when there are urgent data, the routing protocol should be able to transmit it stably and quickly. This paper proposes an adaptive routing protocol that satisfies different requirements of normal and urgent data. To extend network lifetime, the proposed routing protocol reduces power imbalance for normal data and also minimizes transmission latency by controlling the transmission power for urgent data. Simulation results show that the proposed adaptive routing can improve network lifetime by mitigating the power imbalance and greatly reduce the transmission delay of urgent data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.98-101
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• 2019

In this paper, we propose the power-based pipelined-forwarding MAC protocol which can select relay nodes according to the residual power and energy harvesting rate in EH-WSN (energy-harvesting wireless sensor networks). The proposed MAC follows a pipelined-forwarding scheme in which nodes repeatedly sleep and wake up in an EH-WSN environment and data is continuously transmitted from a high-level node to a low-level node. The sleep interval is adaptively controlled so that nodes with low energy harvesting rate can be charged sufficiently, thereby minimizing the transmission delay and increasing the network lifetime. Simulation shows that the proposed MAC protocol improves the balance of residual power and network lifetime.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.115-122
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• 2017

In this paper, we propose an adaptive data aggregation and compression scheme for wireless sensor networks with energy-harvesting nodes, which increases the amount of data arrived at the sink node by efficient use of the harvested energy. In energy-harvesting wireless sensor networks, sensor nodes can have more than necessary energy because they harvest energy from environments continuously. In the proposed scheme, when a node judges that there is surplus energy by estimating its residual energy, the node compresses and transmits the aggregated data so far. Conversely, if the residual energy is estimated to be depleted, the node turns off its transceiver and collects only its own sensory data to reduce its energy consumption. As a result, this scheme increases the amount of data collected at the sink node by preventing the blackout of relay nodes and facilitating data transmission. Through simulation, we show that the proposed scheme suppresses the occurrence of blackout nodes and collect the largest amount of data at the sink node compared to previous schemes.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.105-116
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• 2019

Recently, there has been an increase in research on wireless sensor networks (WSNs) because they are easy to deploy in applications such as internet-of-things (IoT) and body area networks. However, WSNs have constraints in terms of power, quality-of-service (QoS), computation, and others. To overcome the power constraint issues, wireless energy harvesting has been introduced into WSNs, the application of which has been the focus of many studies. Additionally, to improve system performance in terms of achievable rate, cooperative networks are also being explored in WSNs. We present a review on current research in the area of energy harvesting in WSNs, specifically on the application of simultaneous wireless information and power transfer (SWIPT) in a cooperative sensor network. In addition, we discuss possible future extensions of SWIPT and cooperative networks in WSNs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.477-485
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• 2015

Most existing simulators for wireless sensor networks(WSNs) are modeling battery-based sensors and providing MAC and routing protocols designed for battery-based WSNs. However, recently, as energy harvesting sensor systems have been studied more extensively, there is an increasing need for appropriate simulators, but few related studies have employed such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy-harvesting model, rechargeable battery model, and energy-consuming model. Additionally, it should enable the applications of the well-known MAC and routing protocols designed for energy-harvesting WSNs, as well as a user-friendly interface for convenience. In this work, we design and implement a user-friendly simulator for solar energy-harvesting WSNs.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.215-223
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• 2015

Energy harvesting technique is an energy charging technique for communication device in energy-constrained environment. Recently, energy harvesting technique that harvests energy from wireless radio frequency signal is proposed. Representatively, there are time switching technique and power splitting technique. This paper proposes an optimal harvesting time allocation scheme in a wireless cognitive relay network when secondary user relay uses energy harvesting technique to transmit information. Secondary user relay receives information and energy simultaneously from the secondary user source's signal via time switching technique. We aim to maximize the instantaneous throughput by optimizing harvesting time of the secondary user relay. Simulation results show that using optimized harvesting time gets larger instantaneous throughput compared to using constant harvesting time.