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

Wearable flexible lightweight modular RFID tag with integrated energy harvester

A novel wearable radio frequency identification (RFID) tag with sensing, processing, and decision-taking capability is presented for operation in the 2.45-GHz RFID superhigh frequency (SHF) band. The tag is powered by an integrated light harvester, with a flexible battery serving as an energy buffer. The proposed active tag features excellent wearability, very high read range, enhanced functionality, flexible interfacing with diverse low-power sensors, and extended system autonomy through an innovative holistic microwave system design paradigm that takes antenna design into consideration from the very early stages. Specifically, a dedicated textile shorted circular patch antenna with monopolar radiation pattern is designed and optimized for highly efficient and stable operation within the frequency band of operation. In this process, the textile antenna's functionality is augmented by reusing its surface as an integration platform for light-energy-harvesting, sensing, processing, and transceiver hardware, without sacrificing antenna performance or the wearer's comfort. The RFID tag is validated by measuring its stand-alone and on-body characteristics in free-space conditions. Moreover, measurements in a real-world scenario demonstrate an indoor read range up to 23 m in nonline-of-sight indoor propagation conditions, enabling interrogation by a reader situated in another room. In addition, the RFID platform only consumes 168.3 mu W, when sensing and processing are performed every 60 s

Energy Harvesting and Management for Wireless Autonomous Sensors

Wireless autonomous sensors that harvest ambient energy are attractive solutions, due to their convenience and economic benefits. A number of wireless autonomous sensor platforms which consume less than 100?W under duty-cycled operation are available. Energy harvesting technology (including photovoltaics, vibration harvesters, and thermoelectrics) can be used to power autonomous sensors. A developed system is presented that uses a photovoltaic module to efficiently charge a supercapacitor, which in turn provides energy to a microcontroller-based autonomous sensing platform. The embedded software on the node is structured around a framework in which equal precedent is given to each aspect of the sensor node through the inclusion of distinct software stacks for energy management and sensor processing. This promotes structured and modular design, allowing for efficient code reuse and encourages the standardisation of interchangeable protocols

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

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

Movers and Shakers: Kinetic Energy Harvesting for the Internet of Things

Numerous energy harvesting wireless devices that will serve as building blocks for the Internet of Things (IoT) are currently under development. However, there is still only limited understanding of the properties of various energy sources and their impact on energy harvesting adaptive algorithms. Hence, we focus on characterizing the kinetic (motion) energy that can be harvested by a wireless node with an IoT form factor and on developing energy allocation algorithms for such nodes. In this paper, we describe methods for estimating harvested energy from acceleration traces. To characterize the energy availability associated with specific human activities (e.g., relaxing, walking, cycling), we analyze a motion dataset with over 40 participants. Based on acceleration measurements that we collected for over 200 hours, we study energy generation processes associated with day-long human routines. We also briefly summarize our experiments with moving objects. We develop energy allocation algorithms that take into account practical IoT node design considerations, and evaluate the algorithms using the collected measurements. Our observations provide insights into the design of motion energy harvesters, IoT nodes, and energy harvesting adaptive algorithms.Comment: 15 pages, 11 figure

Flexible Integration of Alternative Energy Sources for Autonomous Sensing

Recent developments in energy harvesting and autonomous sensing mean that it is now possible to power sensors solely from energy harvested from the environment. Clearly this is dependent on sufficient environmental energy being present. The range of feasible environments for operation can be extended by combining multiple energy sources on a sensor node. The effective monitoring of their energy resources is also important to deliver sustained and effective operation. This paper outlines the issues concerned with combining and managing multiple energy sources on sensor nodes. This problem is approached from both a hardware and embedded software viewpoint. A complete system is described in which energy is harvested from both light and vibration, stored in a common energy store, and interrogated and managed by the node