Extending the Energy Framework for Network Simulator 3 (ns-3)

The problem of designing and simulating optimal transmission protocols for energy harvesting wireless networks has recently received considerable attention, thus requiring for an accurate modeling of the energy harvesting process and a consequent redesign of the simulation framework to include it. While the current ns-3 energy framework allows the definition of new energy sources that incorporate the contribution of an energy harvester, the integration of an energy harvester component into an existing energy source is not straightforward using the existing energy framework. In this poster, we propose an extension of the energy framework currently released with ns-3 in order to explicitly introduce the concept of an energy harvester. Starting from the definition of the general interface, we then provide the implementation of two simple models for the energy harvester. In addition, we extend the set of implementations of the current energy framework to include a model for a supercapacitor energy source and a device energy model for the energy consumption of a sensor. Finally, we introduce the concept of an energy predictor, that gathers information from the energy source and harvester and use this information to predict the amount of energy that will be available in the future, and we provide an example implementation. As a result of these efforts, we believe that our contributions to the ns-3 energy framework will provide a useful tool to enhance the quality of simulations of energy-aware wireless networks.Comment: 2 pages, 4 figures. Poster presented at WNS3 2014, Atlanta, G

A Survey of Multi-Source Energy Harvesting Systems

Energy harvesting allows low-power embedded devices to be powered from naturally-ocurring or unwanted environmental energy (e.g. light, vibration, or temperature difference). While a number of systems incorporating energy harvesters are now available commercially, they are specific to certain types of energy source. Energy availability can be a temporal as well as spatial effect. To address this issue, ‘hybrid’ energy harvesting systems combine multiple harvesters on the same platform, but the design of these systems is not straightforward. This paper surveys their design, including trade-offs affecting their efficiency, applicability, and ease of deployment. This survey, and the taxonomy of multi-source energy harvesting systems that it presents, will be of benefit to designers of future systems. Furthermore, we identify and comment upon the current and future research directions in this field

Energy Harvesting Solution for the UWASA Node: Applications for Wind Turbine Monitoring

The aim of this thesis was to develop an energy harvesting solution for the UWASA Node for wind power station applications. Energy harvesting is the process by which small amounts of ambient energy is collected for use by electronics such as wireless sensor nodes. The developed energy harvesting solution is capable of supplying enough energy for the UWASA Node to perform a wide variety of tasks indefinitely, without the need for changing its battery. The wireless sensor node can for example read sensors at high sampling rates and store or wirelessly transmit these readings. It can also perform complex computations and react to changes in its environment. One intended use was monitoring vibrations of wind turbines blades, but field tests have yet to be done. This master’s thesis builds on the findings of my bachelor’s thesis, Höglund (2014) in the references. In the bachelor’s thesis different methods of energy harvesting were in-vestigated to find the most suitable methods for this project. In this master’s thesis a prototype energy harvester and energy management circuit was developed and tested. The prototype is capable of harvesting tens of milliwatts from a small solar cell. It could also be modified to harvest another ambient energy source or several sources at once. Every part of the energy harvester and energy management circuit is discussed in detail and laboratory tests are presented. Different means of maximum power point tracking were tested and evaluated. The prototype energy harvester was built using a modular approach so that energy harvesting from multiple sources of energy easily can be ac-complished by adding a few components for each source to the harvesting circuit. The programming of the sensor node also needs to be adapted so that it runs optimally from the harvested energy by scheduling measurements and wireless communication. A low-power real-time clock and a latching switch were included on the prototype PCB for switching on and off the power to the sensor node completely in order to consume as little energy as possible when the sensor node is inactive.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Design Proposal of Self-Powered WSN Node for Battle Field Surveillance

AbstractA growing demand for deployment of autonomous battlefield sensors and sensor networks is leading to a subsequent increase in the demand for localized, independent energy harvesting capabilities for each node. In this paper, several methods of energy harvesting are summarized. By utilizing energy form the surroundings, small amounts of power can be harvested from wind, solar radiation and stress sources. Energy harvested is converted to battery potential via a converter. Operation flowchart of the system is presented. Meanwhile, an algorithm for the sensor network to adaptively learn its energy environment has been studied. Schemes summarized in this paper can be of guidance for design and utilize energy harvest systems on the battlefield network sensor nodes

Solar Energy Harvesting in WSN with Development Tool

The aim of this thesis was to introduce a solar energy and wsn, as well as to introduce how the solar energy harvesting development tool helps create a perpetually powered wireless sensor network and provides enough power to run a wireless sensor application with no additional batteries. Solar energy is radiant light and heat from the sun. WSN is widely used in modern society. In this project these two areas were combined and it was studied to use the solar energy harvesting in a wireless sensor network with the development tool. As a result of this thesis, the SEH module's solar panel was optimized for operating lights, which provides enough power to run a wireless sensor application with no additional batteries

A Wireless Sensor Network Based Solar Powered Harvesting System for Aquaculture

Despite improvements in battery technology and declines in electronics power demands, many new applications in wireless sensor networks (WSNs) are taking into account increasing power requirements. Furthermore, since in WSNs it is frequently desirable to deploy nodes in unobtainable places, it might be impossible to provide large enough power for such applications given the fact that battery replacement is not practicable. This results in significant interests in designing sensor nodes with the capability of extracting electrical energy from surrounding ambient sources. The ultimate goal of this research is to achieve a perpetually powered system without a necessary periodical maintenance for battery replacement or recharging. The energy harvesting system developed for this research has been experimentally verified and can increase the lifetime of an entire network to reach that of its individual hardware components. We realized a maximum power point tracking (MPPT) algorithm that could switch power source according to light conditions to ensure the continuous stable operation

Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer

Radio frequency (RF) energy harvesting and transfer techniques have recently become alternative methods to power the next generation of wireless networks. As this emerging technology enables proactive replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service (QoS) requirement. This article focuses on the resource allocation issues in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs, followed by a review of a variety of issues regarding resource allocation. Then, we present a case study of designing in the receiver operation policy, which is of paramount importance in the RF-EHNs. We focus on QoS support and service differentiation, which have not been addressed by previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs