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Biology Inspired Approach for Communal Behavior in Sensor Networks
Research in wireless sensor network technology has exploded in the last decade. Promises of complex and ubiquitous control of the physical environment by these networks open avenues for new kinds of science and business. Due to the small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors working in concert. Although the reduction in size has been phenomenal it results in severe limitations on the computing, communicating, and power capabilities of these devices. Under these constraints, research efforts have concentrated on developing techniques for performing relatively simple tasks with minimal energy expense assuming some form of centralized control. Unfortunately, centralized control does not scale to massive size networks and execution of simple tasks in sparsely populated networks will not lead to the sophisticated applications predicted. These must be enabled by new techniques dependent on local and autonomous cooperation between sensors to effect global functions. As a step in that direction, in this work we detail a technique whereby a large population of sensors can attain a global goal using only local information and by making only local decisions without any form of centralized control.
Distributed Transforms for Efficient Data Gathering in Sensor Networks
Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.
Wireless Sensing Opportunities for Aerospace Applications
Wireless sensors and sensor networks is an emerging technology area with many applications within the aerospace industry. Integrated vehicle health monitoring (IVHM) of aerospace vehicles is needed to ensure the safety of the crew and the vehicle, yet often high costs, weight, size and other constraints prevent the incorporation of instrumentation onto spacecraft. This paper presents a few of the areas such as IVHM, where new wireless sensing technology is needed on both existing vehicles as well as future spacecraft. From ground tests to inflatable structures to the International Space Station, many applications could receive benefits from small, low power, wireless sensors. This paper also highlights some of the challenges that need to overcome when implementing wireless sensor networks for aerospace vehicles.
Application of Machine Learning Techniques to Delay Tolerant Network Routing
This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.
Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks
Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.
Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks
Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.
Distributed Prognostic Health Management with Gaussian Process Regression
Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper. we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.
Delay Tolerant, Radio Frequency Identification (RFID )-enabled Sensing
Radio Frequency Identification (RFID) technology offers a completely passive method to transmit fixed data sequences from an RFID tag, which typically doesn’t have its own power supply, to an interrogator. Radio frequency (RF) energy harvested from the interrogator is rectified by the tag and used to charge an integrated circuit (IC). The IC then modulates the received signal with the data stored on the tag and reflects the energy back to the interrogator. RFID has seen great proliferation in terrestrial inventory management applications, and it has recently made the jump to spaceflight applications onboard the International Space Station, augmenting an existing optical bar‐code infrastructure for tracking supplies. A number of advanced automated logistics management (ALM) concepts employing RFID are currently being developed and evaluated, including so‐called “smart” shelves, cubbies, and trash receptacles using low‐power, embeddable RFID interrogators. An infrastructure where both crew members and robotic assistants, such as autonomous free flyers, are similarly equipped with small RFID interrogators seems likely. It therefore behooves us to consider extending this infrastructure beyond ALM to applications such as low power, embedded sensing. Typically, data on an RFID tag can only be written by an RFID interrogator, using interrogator energy. In recent years, however, a few efforts have focused on using that energy to drive data acquisition from the tag IC, allowing the tag to modify its stored data sequence with sensor data before replying to an interrogator. In this way, the tag can act as a completely passive sensing device. One problem exists with this approach, however: the tag cannot gather data when an interrogator is not present. Thus, strictly passive RFID sensing tags cannot gather data at regular intervals, in the manner of a typical wireless sensor network, without careful, and impractical, planning of mobile interrogator movements. To address this shortcoming, we look to a recent advance in RFID technology which allows an external microprocessor to power the tag IC and write directly into its RFID memory using a wired serial interface. In this paradigm, data gathering is driven by a small, on‐board power supply (using batteries or harvested energy), and data transfer is provided passively through the RFID interrogation service. Since communication typically consumes the lion’s share of power in WSNs, such a technique has the potential to enable extremely long‐lived, embedded wireless sensing when used with extremely low‐current microcontrollers. Since the communication channel is only open when an interrogator is present and actively interrogating the RFID sensing tag, transport of periodically‐sampled sensor data presents itself as a delay/disruption‐tolerant networking (DTN) problem. In this paper, we present the design of a DTN‐like overlay on the common EPC Global, Class 1, Generation 2 RFID standard. This overlay allows seamless, guaranteed data transfer using the EPC Global protocol, supporting extremely low‐power, embedded sensing using an infrastructure likely to be already in place for ALM applications. We evaluate a prototype implementation of a complete end‐to‐end system using a robotic RFID interrogation agent, and we present future directions for the development of this sensing technique.
Improved Testing Capability and Adaptability Through the Use of Wireless Sensors
From the first Saturn V rocket booster (S-II-T) testing in 1966 and the routine Space Shuttle Main Engine (SSME) testing beginning in 1975, to more recent test programs such as the X-33 Aerospike Engine, the Integrated Powerhead Development (IPD) program, and the Hybrid Sounding Rocket (HYSR), Stennis Space Center (SSC) continues to be a premier location for conducting large-scale testing. Central to each test program is the capability for sensor systems to deliver reliable measurements and high quality data, while also providing a means to monitor the test stand area to the highest degree of safety and sustainability. Sensor wiring is routed along piping and through cable trenches, making its way from the engine test area, through the test stand area and to the signal conditioning building before final transfer to the test control center. When sensor requirements lie outside the reach of the routine sensor cable routing, the use of wireless sensor networks becomes particularly attractive due to their versatility and ease of installation. As part of an on-going effort to enhance the testing capabilities of Stennis Space Center, the Test Technology and Development group has found numerous applications for its sensor-adaptable wireless sensor suite. While not intended for critical engine measurements or control loops, in-house hardware and software development of the sensor suite can provide improved testing capability for a range of applications including the safety monitoring of propellant storage barrels and as an experimental test-bed for embedded health monitoring paradigms.
A Modular Instrumentation System for NASA's Habitat Demonstration Unit
NASA's human spaceflight program is focused on developing technologies to expand the reaches of human exploration and science activities beyond low earth orbit. A critical aspect of living in space or on planetary surfaces is habitation, which provides a safe and comfortable space in which humans can live and work. NASA is seeking out the best option for habitation by exploring several different concepts through the Habitat Demonstration Unit (HDU) project. The purpose of this HDU is to develop a fully autonomous habitation system that enables human exploration of space. One critical feature of the HDU project that helps to accomplish its mission of autonomy is the instrumentation system that monitors key subsystems operating within a Habitat configuration. The following paper will discuss previous instrumentation systems used in analog habitat concepts and how the current instrumentation system being implemented on the HDU1-PEM, or pressurized excursion module, is building upon the lessons learned of those previous systems. Additionally, this paper will discuss the benefits and the limitations of implementing a wireless sensor network (WSN) as the basis for data transport in the instrumentation system. Finally, this paper will address the experiences and lessons learned with integration, testing prior to deployment, and field testing at the JSC rock yard. NASA is developing the HDU1-PEM as a step towards a fully autonomous habitation system that enables human exploration of space. To accomplish this purpose, the HDU project is focusing on development, integration, testing, and evaluation of habitation systems. The HDU will be used as a technology pull, testbed, and integration environment in which to advance NASA's understanding of alternative mission architectures, requirements, and operations concepts definition and validation. This project is a multi-year effort. In 2010, the HDU1-PEM will be in a pressurized excursion module configuration, and in 2011 the module will be reconfigured for a pressurized core module configuration. Each year the HDU configurations will undergo testing at NASA's Desert Research and Technology Studies (D-RaTS) in Arizona [1]. As part of this project, a modular instrumentation system is developed to meet the monitoring needs of the HDU subsystems and to integrate with the current command and data handling infrastructure that has been developed for the project. The main objective of this study is to provide for the monitoring needs of the HDU. The requirements necessary to meet this objective are developed by working with the subsystem managers of the HDU to understand their monitoring needs. Additionally, the instrumentation system design leverages knowledge and lessons learned from previous studies, such as the inflatable habitat health monitoring system that was deployed in Antarctica [2], the integrated health monitoring system developed for NASA's Microhab [3], and the JSC Lunar Habitat Wireless Testbed to demonstrate a "standardsbased" approach to a wireless instrumentation system [4]. The HDU also requires flexibility in reconfiguration options, and it is necessary to demonstrate and evaluate a modular approach to an instrumentation system. Thus, the instrumentation system is designed in two parts: the primary system employs a standard WSN configuration, and the secondary system employs a wired USB hub. The WSN design provides for reconfiguration or replacement of sensors due to malfunctions or upgrades by using a wireless node that accepts ten instrument inputs and wirelessly transmits the data to the command and data handling system. The USB hub is necessary for those instruments that operate using a wired USB connection, although the design attempts to limit the amount of sensors that need to be wired connections.
Real-Time Wireless Data Acquisition System
Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.
Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays
his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.
Communication Optimizations for a Wireless Distributed Prognostic Framework
Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication overhead is an important design problem for such systems. In this paper we focus on communication issues faced in the distributed implementation of an important class of algorithms for prognostics - particle filters. In spite of being computation and memory intensive, particle filters lend well to distributed implementation except for one significant step - resampling. We propose new resampling scheme called parameterized resampling that attempts to reduce communication between collaborating nodes in a distributed wireless sensor network. Analysis and comparison with relevant resampling schemes is also presented. A battery health management system is used as a target application. A new resampling scheme for distributed implementation of particle filters has been discussed in this paper. Analysis and comparison of this new scheme with existing resampling schemes in the context for minimizing communication overhead have also been discussed. Our proposed new resampling scheme performs significantly better compared to other schemes by attempting to reduce both the communication message length as well as number total communication messages exchanged while not compromising prediction accuracy and precision. Future work will explore the effects of the new resampling scheme in the overall computational performance of the whole system as well as full implementation of the new schemes on the Sun SPOT devices. Exploring different network architectures for efficient communication is an importance future research direction as well.
Thermoelectric Devices Cool, Power Electronics
Nextreme Thermal Solutions Inc., based in Research Triangle Park, North Carolina, licensed thermoelectric technology from NASA s Jet Propulsion Laboratory. This has allowed the company to develop cutting edge, thin-film thermoelectric coolers that effective remove heat generated by increasingly powerful and tightly packed microchip components. These solid-state coolers are ideal solutions for applications like microprocessors, laser diodes, LEDs, and even potentially for cooling the human body. Nextreme s NASA technology has also enabled the invention of thermoelectric generators capable of powering technologies like medical implants and wireless sensor networks.
Integrated Vehicle Health Management Project-Modeling and Simulation for Wireless Sensor Applications
This paper describes the efforts in modeling and simulating electromagnetic transmission and reception as in a wireless sensor network through a realistic wing model for the Integrated Vehicle Health Management project at the Glenn Research Center. A computer model in a standard format for an S-3 Viking aircraft was obtained, converted to a Microwave Studio software format, and scaled to proper dimensions in Microwave Studio. The left wing portion of the model was used with two antenna models, one transmitting and one receiving, to simulate radio frequency transmission through the wing. Transmission and reception results were inconclusive.
Wireless Technologies in Support of ISS Experimentation and Operations
Presentation reviews: (1) Wireless Communications (a) Internal (b) External (2) RFID (Radio Frequency Identification) (a) Existing and R&D (3) Wireless Sensor Networks (a) Existing and R&D (4) Ultra-Wide Band (UWB) (a) R&D
Distributive, Non-destructive Real-time System and Method for Snowpack Monitoring
A ground-based system that provides quasi real-time measurement and collection of snow-water equivalent (SWE) data in remote settings is provided. The disclosed invention is significantly less expensive and easier to deploy than current methods and less susceptible to terrain and snow bridging effects. Embodiments of the invention include remote data recovery solutions. Compared to current infrastructure using existing SWE technology, the disclosed invention allows more SWE sites to be installed for similar cost and effort, in a greater variety of terrain; thus, enabling data collection at improved spatial resolutions. The invention integrates a novel computational architecture with new sensor technologies. The invention's computational architecture is based on wireless sensor networks, comprised of programmable, low-cost, low-powered nodes capable of sophisticated sensor control and remote data communication. The invention also includes measuring attenuation of electromagnetic radiation, an approach that is immune to snow bridging and significantly reduces sensor footprints.