Energy Loss through Standby and Leakage in Energy Harvesting Wireless Sensors (original) (raw)
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Energy Consumption Model for Data Processing and Transmission in Energy Harvesting Wireless Sensors
This paper studies energy harvesting wireless sensor nodes in which energy is gathered through harvesting process and data is gathered through sensing from the environment at random rates. These packets can be stored in node buffers as discrete packet forms which were previously introduced in " Energy Packet Network " paradigm. We consider a standby energy loss in the energy buffer (battery or capacitor) in a random rate, due to the fact that energy storages have self discharge characteristic. The wireless sensor node consumes Ke and Kt amount of harvested energy for node electronics (data sensing and processing operations) and wireless data transmission, respectively. Therefore, whenever a sensor node has less than Ke amount of energy, data can not be sensed and stored, and whenever there is more than Ke amount of energy, data is sensed and stored and also it could be transmitted immediately if the remaining energy is greater or equal than the Kt. We assume that the values of both Ke and Kt as one energy packet, which leads us a one-dimensional random walk modeling for the transmission system. We obtain stationary probability distribution as a product form solution and study on other quantities of interests. We also study on transmission errors among a set of M identical sensor with the presence of interference and noise.
IEEE/ACM Transactions on Networking, 2013
As many sensor network applications require deployment in remote and hard-to-reach areas, it is critical to ensure that such networks are capable of operating unattended for long durations. Consequently, the concept of using nodes with energy replenishment capabilities has been gaining popularity. However, new techniques and protocols must be developed to maximize the performance of sensor networks with energy replenishment. Here, we analyze limits of the performance of sensor nodes with limited energy, being replenished at a variable rate. We provide a simple localized energy management scheme that achieves a performance close to that with an unlimited energy source, and at the same time keeps the probability of complete battery discharge low. Based on the insights developed, we address the problem of energy management for energyreplenishing nodes with finite battery and finite data buffer capacities. To this end, we give an energy management scheme that achieves the optimal utility asymptotically while keeping both the battery discharge and data loss probabilities low.
A Sensor Node with Energy Harvesting
We study the backlog of energy and of data packets in a sensor node that collects data and harvests energy, and using the energy to forward data packets. Assuuming that data transmission times are negligible, we compute the properties of energy and data backlogs and discuss some interesting system stability issues.
1 Performance Analysis for Energy Harvesting Communication Protocols with Fixed Rate Transmission
2016
Energy Harvesting (EH) has emerged as a promising technique for Green Communications and it is a novel technique to prolong the lifetime of the wireless networks with replenishable nodes. In this paper, we consider the energy shortage analysis of fixed rate transmission in communication systems with energy harvesting nodes. First, we study the finite-horizon transmission and provide the general formula for the energy shortage probability. We also give some examples as benchmarks. Then, we continue to derive a closed-form expression for infinite-horizon transmission, which is a lower bound for the energy shortage probability of any finite-horizon transmission. These results are proposed for both Additive White Gaussian Noise (AWGN) and fading channels. Moreover, we show that even under random energy arrival, one can transmit at a fixed rate equal to capacity in the AWGN channels with negligible aggregate shortage time. We achieve this result using our practical transmission schemes, proposed for finite-horizon. Also, comprehensive numerical simulations are performed in AWGN and fading channels with no Channel State Information (CSI) available at the transmitter, which corroborate our theoretical findings. Furthermore, we improve the performance of our transmission schemes in the fading channel with no CSI at the transmitter by optimizing the transmission initiation threshold.
Significance of Energy Harvesting for Wireless Sensor Networks
2014
Wireless Sensor Networks consist of a large number of small in size, low-power but smart sensor nodes are interfacing with one another and deployed over a certain inaccessible geographical area with portable sources like betters having limited power and storage space[1][2]. However, the battery presents several disadvantages required to be replaced or recharge them frequently. One possibility to overcome this power limitations problem is to harvest energy from the ambient limitless available energy sources in the environment surrounding to the sensor nodes are either to recharge batteries or directly use to power the sensor nodes of wireless sensor network. Most of the time, energy harvest from one source is not sufficient to meet the power requirement of sensor nodes. Therefore the hybrid energy harvesting techniques would be a solution to solve the low power problem of wireless sensor nodes. However the energy harvesting process may be irregular, thought there may be a limit on th...
Performance analysis for energy harvesting communication protocols with fixed rate transmission
IET Communications , 2014
Energy harvesting (EH) has emerged as a promising technique for Green Communications and it is a novel technique to prolong the lifetime of the wireless networks with replenishable nodes. In this study, the authors consider the energy shortage analysis of fixed rate transmission in communication systems with EH nodes. First, the authors study the finite-horizon transmission and provide the general formula for the energy shortage probability (ESP). The authors also give some examples as benchmarks. Then, the authors continue to derive a closed-form expression for infinite-horizon transmission, which is a lower bound for the ESP of any finite-horizon transmission. These results are proposed for both Additive White Gaussian Noise (AWGN) and fading channels. Moreover, the authors show that even under random energy arrival, one can transmit at a fixed rate equal to capacity in the AWGN channels with negligible aggregate shortage time. The authors achieve this result using our practical transmission schemes, proposed for finite-horizon. Also, comprehensive numerical simulations are performed in AWGN and fading channels with no Channel State Information (CSI) available at the transmitter, which corroborate our theoretical findings. Furthermore, the authors improve the performance of our transmission schemes in the fading channel with no CSI at the transmitter by optimising the transmission initiation threshold.
Performance analysis of energy harvesting sensors with time-correlated energy supply
Sensors powered by energy harvesting devices (EHD) are increasingly being deployed in practice, due to the demonstrated advantage of long-term, autonomous operation, without the hassle of battery replacement. This paper is concerned with the following fundamental problem: how should the harvested energy be managed to ensure optimal performance, if the statistical properties of the ambient energy supply are known? To formulate the problem mathematically, we consider an EHDpowered sensor which senses data of varying importance and model the availability of ambient energy by a two-state Markov chain ("GOOD" and "BAD"). Assuming that data transmission incurs an energy cost, our objective is to identify low-complexity transmission policies, which achieve good performance in terms of average long-term importance of the transmitted data. We derive the performance of a Balanced Policy (BP), which adapts the transmission probability to the ambient energy supply, so as to balance energy harvesting and consumption, and demonstrate that it performs within 10% of the globally optimal policy. Moreover, a BP which avoids energy overflow by always transmitting when the sensor battery is fully charged is shown to perform within 5% of the optimum. Finally, we identify a key performance parameter for any policy, the relative battery capacity, defined as the ratio of the battery capacity to the expected duration of the BAD harvesting period.
2016
Energy harvesting (EH) provides a means of greatly enhancing the lifetime of wireless sensor nodes. However, the randomness inherent in the EH process may cause significant delay for performing sensing operation and transmitting the sensed information to the sink. Unlike most existing studies on the delay performance of EH sensor networks, where only the energy consumption of transmission is considered, we consider the energy costs of both sensing and transmission. Specifically, we consider an EH sensor that monitors some status environmental property and adopts a harvest-then-use protocol to perform sensing and transmission. To comprehensively study the delay performance, we consider two complementary metrics and analytically derive their statistics: (i) update age - measuring the time taken from when information is obtained by the sensor to when the sensed information is successfully transmitted to the sink, i.e., how timely the updated information at the sink is, and (ii) update ...
IEEE Transactions on Circuits and Systems I: Regular Papers, 2000
Wireless transmission systems fed by ambient harvested energy power sources can operate continuously, without needing battery replacement. Such systems are ideal for applications with limited or difficult accessibility. Ambient energy sources exhibit a stochastic nature, so an energy storage device must store the harvested energy. In this work, a control method that minimizes the use of storage is developed. The strategy is to match data transmission rate as close as possible to the availability of harvested power, so the energy storage capacity can be reduced. An audio recording sensor is designed and simulated using SPICE to validate the proposed controller. For this system, the size of storage device is reduced by a factor of 24.