Power Wireless Sensor Networks Research Articles

Increasing throughput in energy-based opportunistic spectrum access energy harvesting cognitive radio networks

The performance of large-scale cognitive radio (CR) networks with secondary users sustained by opportunistically harvesting radio-frequency (RF) energy from nearby primary transmissions is investigated. Using an advanced RF energy harvester, a secondary user is assumed to be able to collect ambient primary RF energy as long as it lies inside the harvesting zone of an active primary transmitter (PT). A variable power (VP) transmission mode is proposed, and an energy-based opportunistic spectrum access (OSA) strategy is considered, under which a secondary transmitter (ST) is allowed to transmit only if its harvested energy is larger than a predefined transmission threshold and it is outside the guard zones of all active PTs. The transmission probability of the STs is derived. The outage probabilities and the throughputs of the primary and the secondary networks, respectively, are characterized. Compared with prior work, the throughput can be increased by as much as 29%. The energy-based OSA strategy can be generally applied to a non-CR setup, where distributed power beacons (PBs) are deployed to power coexisting wireless signal transmitters (WSTs) in a wireless powered sensor network.

A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network.

Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs.

Energy-efficient and low-delay scheduling scheme for low power wireless sensor network with real-time data flows

In this paper, we propose an energy-efficient and low-delay scheduling EELDS scheme for interruptible preamble sampling-based medium access control MAC protocols e.g., BoX-MAC-2 and X-MAC in IEEE 802.15.4 wireless sensor network WSN, which considers energy efficiency while reducing delay and contention in the context of real-time data gathering and remote monitoring applications. It is built on MAC layer and exploits local information to coordinate the MAC schedules of nodes in a slowly-changing topology, just with light overhead. The scheme also considers the adaptation to data aggregation with real-time data flows. Therefore, our scheme allows for much longer network lifetime while satisfying the delay constraints. The implementation and simulation results show the performance of the proposed scheme.

Optimal Charging in Wireless Rechargeable Sensor Networks

Recent years have witnessed several new promising technologies to power wireless sensor networks, which motivate some key topics to be revisited. By integrating sensing and computation capabilities to the traditional radio-frequency identification (RFID) tags, the Wireless Identification and Sensing Platform (WISP) is an open-source platform acting as a pioneering experimental platform of wireless rechargeable sensor networks. Different from traditional tags, an RFID-based wireless rechargeable sensor node needs to charge its onboard energy storage above a threshold to power its sensing, computation, and communication components. Consequently, such charging delay imposes a unique design challenge for deploying wireless rechargeable sensor networks. In this paper, we tackle this problem by planning the optimal movement strategy of the mobile RFID reader, such that the time to charge all nodes in the network above their energy threshold is minimized. We first propose an optimal solution using the linear programming (LP) method. To further reduce the computational complexity, we then introduce a heuristic solution with a provable approximation ratio of (1 + θ)/(1 - ε) by discretizing the charging power on a 2-D space. Through extensive evaluations, we demonstrate that our design outperforms the set-cover-based design by an average of 24.7%, whereas the computational complexity is O((N/ε) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). Finally, we consider two practical issues in system implementation and provide guidelines for parameter setting.

Energy-efficient and low-delay scheduling scheme for low power wireless sensor network with real-time data flows

In this paper, we propose an energy-efficient and low-delay scheduling (EELDS) scheme for interruptible preamble sampling-based medium access control (MAC) protocols (e.g., BoX-MAC-2 and X-MAC) in IEEE 802.15.4 wireless sensor network (WSN), which considers energy efficiency while reducing delay and contention in the context of real-time data gathering and remote monitoring applications. It is built on MAC layer and exploits local information to coordinate the MAC schedules of nodes in a slowly-changing topology, just with light overhead. The scheme also considers the adaptation to data aggregation with real-time data flows. Therefore, our scheme allows for much longer network lifetime while satisfying the delay constraints. The implementation and simulation results show the performance of the proposed scheme.

Improving the limits of detection in potentiometric sensors

Potentiometric sensors will generally suffer from unwanted responses as a result to changing temperatures by generating an electromotive force. Typically, this voltage drift has a non-linear character and therefore it is difficult to compensate using linear algorithms implemented in the analogue domain. A solution is proposed to improve the sensor characteristics by combining the digitized output of two CO2 rubidium silver iodide sensors with a specially designed digital algorithm to improve the limits of detection (LOD). Experiments show that this method has the capability to improve the LOD of the sensor with a factor 4.5x during temperature variations of 22 °C over a measurement period of 22 h. It enables potentiometric sensors to be used in low power wireless sensor networks for long term air quality control. Furthermore, the influence of depletion of the rubidium silver iodide electrolyte layer can be effectively compensated by determining the decay of the active layer according to the Nernst equation. Knowing the function of depletion over time helps to correct the sensor output and thereby improves the accuracy of the sensor.

Harvested Power Wireless Sensor Network Solution for Disaggregated Current Estimation in Large Buildings

In modern economies, large service buildings are responsible for an important part of the global electrical energy consumption. The implementation of energy saving strategies can benefit from disaggregated consumption monitoring. To tackle this problem, a number of technological solutions exist, being however, expensive in equipment, installation and maintenance. Because of its decentralized operation principle, wireless sensor networks (WSNs) are an important tool to implement disaggregated electrical energy monitoring. The development of a self-powered, battery-free current sensor node for large WSNs may contribute to the implementation of monitoring solutions for large buildings. In this paper, a solution to monitor disaggregated consumption is presented, based on a contact-less power source for Zigbee nodes using a split-core toroidal coil current transformer (SCCT). The proposed device is able to power a battery-free wireless node estimating also the current drawn by the electrical load with a single SCCT. The SCCT is successfully applied to power a battery-free wireless device running a complex communication software stack. The proposed system is described through simulation as well as the experimental results.

Joint Connectivity-Coverage Temperature-Aware Algorithms for Wireless Sensor Networks

Temperature variations have a significant effect on low power wireless sensor networks as wireless communication links drastically deteriorate when temperature increases. A reliable deployment should take temperature into account to avoid network connectivity problems resulting from poor wireless links when temperature increases. A good deployment needs also to adapt its operation and save resources when temperature decreases and wireless links improve. Taking into account the probabilistic nature of the wireless communication channel, we develop a mathematical model that provides the most energy efficient deployment in function of temperature without compromising the correct operation of the network by preserving both connectivity and coverage. We use our model to design three temperature-aware algorithms that seek to save energy (i) by putting some nodes in hibernate mode as in the Stop-Operate (SO) algorithm, or (ii) by using transmission power control as in Power-Control (PC), or (iii) by doing both techniques as in Stop-Operate Power-Control (SOPC). All proposed algorithms are fully distributed and solely rely on temperature readings without any information exchange between neighbors, which makes them low overhead and robust. Our results identify the optimal operation of each algorithm and show that a significant amount of energy can be saved by taking temperature into account.

Unifying energy harvesting, sensing, and communication for ultra-low power structure health monitoring

A new ultra-low power (ULP) wireless sensor network (WSN) is proposed to monitor the vibration properties of critical structures such as buildings, bridges, and the wings and bodies of aircrafts. The new scheme integrates energy harvesting, data sensing, and wireless communication into a unified process, and it is fundamentally different from all the existing WSNs. In the new WSN, self-powered sensors are employed to harvest vibration energy and measure vibration intensity simultaneously, by utilizing the fact that the harvested energy accumulated through time is proportional to the vibration amplitude and frequency. Once the harvested energy reaches a threshold, it is released as an impulse with a wireless transmitter. An estimate of the structure vibration intensity can then be obtained by measuring the number of binary impulses in a unit time. Such an approach does not require complicated analog-to-digital conversion or signal processing, and it can achieve an ULP performance unrivaled by existing technologies. Optimum and sub-optimum impulse density estimation algorithms are proposed to take advantage of the spatial correlation among signals from the sensors. Analytical and simulation results demonstrate that the proposed scheme can efficiently operate at a low signal-to-noise ratio (SNR).

Collaborative Mobile Charging

The limited battery capacity of sensor nodes has become one of the most critical impediments that stunt the deployment of wireless sensor networks (WSNs). Recent breakthroughs in wireless energy transfer and rechargeable lithium batteries provide a promising alternative to power WSNs: mobile vehicles/robots carrying high volume batteries serve as mobile chargers to periodically deliver energy to sensor nodes. In this paper, we consider how to schedule multiple mobile chargers to optimize energy usage effectiveness, such that every sensor will not run out of energy. We introduce a novel charging paradigm, collaborative mobile charging, where mobile chargers are allowed to intentionally transfer energy between themselves. To provide some intuitive insights into the problem structure, we first consider a scenario that satisfies three conditions, and propose a scheduling algorithm, PushWait, which is proven to be optimal and can cover a one-dimensional WSN of infinite length. Then, we remove the conditions one by one, investigating chargers’ scheduling in a series of scenarios ranging from the most restricted one to a general 2D WSN. Through theoretical analysis and simulations, we demonstrate the advantages of the proposed algorithms in energy usage effectiveness and charging coverage.

Lessons learned on solar powered wireless sensor network deployments in urban, desert environments

The successful deployment of a large scale solar powered wireless sensor network in an urban, desert environment is a very complex task. Specific cities of such environments cause a variety of operational problems, ranging from hardware faults to operational challenges, for instance due to the high variability of solar energy availability. Even a seemingly functional sensor network created in the lab does not guarantee reliable long term operation, which is absolutely necessary given the cost and difficulty of accessing sensor nodes in urban environments. As part of a larger traffic flow wireless sensor network project, we conducted several deployments in the last two years to evaluate the long-term performance of solar-powered urban wireless sensor networks in a desert area. In this article, we share our experiences in all domains of sensor network operations, from the conception of hardware to post-deployment analysis, including operational constraints that directly impact the software that can be run. We illustrate these experiences using numerous experimental results, and present multiple unexpected operational problems as well as some possible solutions to address them. We also show that current technology is far from meeting all operational constraints for these demanding applications, in which sensor networks are to operate for years to become economically appealing.

On the multi‐hop performance of receiver based MAC protocol in routing protocol for low‐power and lossy networks‐based low power and lossy wireless sensor networks

In this study, the authors focus on utilising receiver-based MAC protocol (RB-MAC) and adaptive RB-MAC in routing protocol for low power and lossy wireless sensor networks routing protocol in low-power and lossy wireless channel. This results in a cross-layer approach in which routing decisions can be made based on MAC-layer functionalities. The authors study the effects of multiple receiver nodes, size of preamble and variable duty-cycle in number of retransmissions. Retransmissions increase energy consumptions and delay. Analytical and numerical results confirm that the RB-MAC and adaptive RB-MAC outperform the existing state-of-the art sender-based MAC protocols in terms of end-to-end energy-efficiency, reliability and delay. Simulation result demonstrates that using receiver-based MAC protocols in RPL-based lossy channel imply less retransmissions than sender-based MAC.

Research on the Collection of Plant Electricity in a Forest

<abstract> <bold><sc>Abstract.</sc></bold> In order to solve the difficult problem of replacing batteries in wireless sensor network nodes in a forest, a method for collecting the weak electricity from a living tree and the surrounding soil is explored in this research brief. The weak electricity is one type of plant electricity. The method for collecting the plant electricity was tested on different kinds of trees. According to the experiments, the plant electricity was in the range of 300 to 900 mV, and there was no direct relationship between the magnitude of the plant electricity and the distribution of the electrodes used for collecting electricity from the tree trunk and the soil. Based on the above findings, a device for collecting plant electricity and a passive DC-DC boost circuit were designed and fabricated. A large number of tests indicated that the weak voltage of the collected plant electricity could be boosted to approximately 3 V without other additional power sources. Two parallel inputs of plant electricity were able to generate an output energy of 0.96 J, allowing a low power consumption wireless sensor node to collect and transmit data for one day. Furthermore, four parallel inputs of plant electricity were able to generate twice the energy of two inputs, which indicated a linear relationship between the number of inputs and the output energy. Therefore, collection and storage of plant electricity has practical value in solving the problem of powering wireless sensor network nodes in a forest.

Internet of Things: Current Technological Review and New Low Power Wireless Sensor Network Protocol Proposal

This paper addresses Internet of Things (IoT) with state-of-art approach. The purpose is to give insight into concept of “smart living”, a concept that meets requirements of today’s modern society. Implementation of this new technology requires new hardware and software installed and run on devices (“things”) connected to the Internet anytime and anywhere. In order to make possible this new technology for wide use, few technological, standards and legal issues need to be solved. In a view of this a new low power wireless sensor network protocol is proposed in the IoT spirit.

Design of Antenna with Rectifying Circuit for Low Power Wireless Sensor Network Application

Design of Antenna with Rectifying Circuit for Low Power Wireless Sensor Network Application

Energy harvesting for powering wireless sensor networks in low-frequency and large-force environments

Over the past few decades, wireless sensor networks have been widely used in the field of structure health monitoring of civil, mechanical, and aerospace systems. Currently, most wireless sensor networks are battery powered and it is costly and unsustainable for maintenance because of the requirement for frequent battery replacements. As an attempt to address such issue, this paper theoretically and experimentally studies a compression-based piezoelectric energy harvester, which is suitable for the low-frequency and large-force working environments, such as in civil and transportation infrastructure applications. The proposed energy harvester employs the piezoelectric structure constructed in multilayer stack configuration to convert ambient vibrations into electrical energy. Based on the linear theory of piezoelectricity, the two-degree-of-freedom electromechanical models of the proposed energy harvester were developed to characterize its performance in generating electrical energy under external excitations. Exact closed-form expressions of the electromechanical models have been derived to analyze the maximum harvested power and the optimal resistance. The theoretical analyses were validated through several experiments for a test prototype under harmonic excitations. The test results exhibit very good agreement with the analytical analyses and numerical simulations for a range of resistive loads and input excitation levels.

Reliability of wireless sensor networks.

Wireless Sensor Networks (WSNs) consist of hundreds or thousands of sensor nodes with limited processing, storage, and battery capabilities. There are several strategies to reduce the power consumption of WSN nodes (by increasing the network lifetime) and increase the reliability of the network (by improving the WSN Quality of Service). However, there is an inherent conflict between power consumption and reliability: an increase in reliability usually leads to an increase in power consumption. For example, routing algorithms can send the same packet though different paths (multipath strategy), which it is important for reliability, but they significantly increase the WSN power consumption. In this context, this paper proposes a model for evaluating the reliability of WSNs considering the battery level as a key factor. Moreover, this model is based on routing algorithms used by WSNs. In order to evaluate the proposed models, three scenarios were considered to show the impact of the power consumption on the reliability of WSNs.

Distributed Least-Squares Estimation of a Remote Chemical Source via Convex Combination in Wireless Sensor Networks

This paper investigates the problem of locating a continuous chemical source using the concentration measurements provided by a wireless sensor network (WSN). Such a problem exists in various applications: eliminating explosives or drugs, detecting the leakage of noxious chemicals, etc. The limited power and bandwidth of WSNs have motivated collaborative in-network processing which is the focus of this paper. We propose a novel distributed least-squares estimation (DLSE) method to solve the chemical source localization (CSL) problem using a WSN. The DLSE method is realized by iteratively conducting convex combination of the locally estimated chemical source locations in a distributed manner. Performance assessments of our method are conducted using both simulations and real experiments. In the experiments, we propose a fitting method to identify both the release rate and the eddy diffusivity. The results show that the proposed DLSE method can overcome the negative interference of local minima and saddle points of the objective function, which would hinder the convergence of local search methods, especially in the case of locating a remote chemical source.

Wireless sensor network coverage measurement and planning in mixed crop farming

Wireless sensor network technology holds great promise for application in agriculture to improve crop yield, improve quality, and reduce costs. This paper presents wireless sensor network coverage measurements in a mixed crop farmland. As one of its key contributions, this study shows that general vegetation attenuation models do not apply to low power wireless sensor networks. A log-linear model is proposed in this paper and validated for application in mixed crop environment. Unlike in mono-crop environment, this study shows that the network coverage is heterogeneous with asymmetric channel between communicating node pair. Crop specific parameters of the log-linear model are derived and used to simulate network coverage in a 7 acre test-bed farm. An adaptive energy consumption model for each sensor node is proposed and used to compute energy consumption in the network. A cluster head and two antenna heights deployment model is also proposed and simulated to alleviate short network lifetime due to vegetation attenuation of signals. The results show that this network deployment model extends the lifetime of the network by a factor of more than 20 compare to a deployment where cluster heads are not used.

Perpetual Topology Control in Energy Harvesting Sensor Network

Harvesting ambient energy to power Wireless Sensor Networks (WSNs) is a promising approach. However, due to low recharging rates and the dynamics of renewable energy, energy harvesting sensors are unable to provide sufficient energy for sustained operation. This work designs a novel perpetual topology control that can enhance the energy efficiency and prolong network lifetime in energy harvesting sensor network. The proposed perpetual topology control (PTC) algorithm aims to ensure WSN sustainability and make the harvesting ambient energy usefully. Experimental results demonstrate the superiority of the PDTC algorithm in energy efficient.