Parametric Probabilistic Routing in Sensor Networks

Motivated by realistic sensor network scenarios that have mis-in-formed nodes and variable network topologies, we propose an approach to routing that combines the best features of limited-flooding and information-sensitive path-finding protocols into a reliable, low-power method that can make delivery guarantees independent of parameter values or information noise levels. We introduce Parametric Probabilistic Sensor Network Routing Protocols, a family of light-weight and robust multi-path routing protocols for sensor networks in which an intermediate sensor decides to forward a message with a probability that depends on various parameters, such as the distance of the sensor to the destination, the distance of the source sensor to the destination, or the number of hops a packet has already traveled. We propose two protocol variants of this family and compare the new methods to other probabilistic and deterministic protocols, namely constant-probability gossiping, uncontrolled flooding, random wandering, shortest path routing (and a variation), and a load-spreading shortest-path protocol inspired by (Servetto and Barrenechea, 2002). We consider sensor networks where a sensor’s knowledge of the local or global information is uncertain (parametrically noised) due to sensor mobility, and investigate the trade-off between robustness of the protocol as measured by quality of service (in particular, successful delivery rate and delivery lag) and use of resources (total network load). Our results for networks with randomly placed nodes and realistic urban networks with varying density show that the multi-path protocols are less sensitive to misinformation, and suggest that in the presence of noisy data, a limited flooding strategy will actually perform better and use fewer resources than an attempted single-path routing strategy, with the Parametric Probabilistic Sensor Network Routing Protocols outperforming other protocols. Our results also suggest that protocols using network information perform better than protocols that do not, even in the presence of strong noise. Christopher L. Barrett is leader of the Basic and Applied Simulation Science Group of the Computing and Computational Sciences Division at Los Alamos National Laboratory. His Group is a simulation science and technology (S&T) invention organization of 30 scientists devoted to providing large-scale, high performance methods for systems analysis and simulation-based assisted reasoning. His Group engages in fundamental mathematical, algorithmic, and complex systems analysis research. Current applied research is focused on interdependent simulation and analysis tools for complex, socio-technical systems like transportation, communications, public health and other critical infrastructure areas. His scientific experience is in simulation, scientific computation, algorithm theory and development, system science and control, engineering science, bio-systems analysis, decision science, cognitive human factors, testing and training. His applied science and engineering achievements include, for example, development of large-scale, high performance simulation systems (e.g., Transportation Analysis Simulation System, TRANSIMS) and development of a distributed computing approach for detailed simulation-based study of mobile, packet switched digital communications systems (Self Organizing Stochastic Rebroadcast Relay, SORSRER). He has a M.S. and Ph.D. in Bio-information Systems from California Institute of Technology. He is a decorated Navy veteran having served in both the submarine service and as a pilot. He has been awarded three Distinguished Service Awards from Los Alamos National Laboratory, one from the Alliance for Transportation Research, one from the Royal Institute of Technology, Stockholm, and one from Artificial Life and Robotics, Oita University, Japan. Stephan J. Eidenbenz is a technical staff member in the Basic and Applied Simulation Science group (CCS-5) at Los Alamos National Laboratory (LANL). He received an M.Sc. in Computer Science from the Swiss Federal Institute of Technology (ETH) in Zurich in 1997 and a Ph.D. in Computer Science from ETH in 2000; he also obtained a Bachelor’s degree in business administration from GSBA in Zurich in 1999. Stephan has worked for McKinsey & Co. in Switzerland, where he received training in business administration and microeconomics. He has held a postdoctoral position at ETH and he has been a postdoctoral fellow at LANL. Stephan’s more than 30 publications cover a wide range of subjects such as approximability and inapproximability properties of visibility problems in polygons and terrains, error modeling in sequencing problems for computation biology, and designing communication protocols robust against selfish behavior. His current research interests include selfish networking, algorithmic game theory, network modeling and simulation, network design, and network optimization. Lukas Kroc is a student of M.Sc. program in Computer Science at Charles University in Prague. In 2003, he was a Graduate Research Assistant at the Basic and Applied Simulation Science group (CCS-5) at Los Alamos National Laboratory. His research interests include simulation, wireless networking and artificial intelligence. Madhav V. Marathe is a Team Leader for Mathematics and Computer Science in the Basic and Applied Simulation Science group, Computer and Computational Sciences (CCS-5) at the Los Alamos National Laboratory. He obtained his B.Tech in 1989 in Computer Science and Engg. from IIT Madras, India and his Ph.D. in 1994 in Computer Science, from University at Albany. His team focuses on developing mathematical and computational tools for design and analysis of large scale simulations of socio-technical and critical infrastructure systems. His research interests are in modeling and simulations of large socio-technical systems, design and analysis of algorithms, computational complexity theory, theory of parallel, distributed and mobile computing and communication systems. He has published over 100 research articles in peer reviewed journals and conferences. He is an adjunct faculty in the Computer Science Department at the University of New Mexico. James P. Smith is a technical staff member in the Basic and Applied Simulation Science Group of the Computing and Computational Sciences Division at Los Alamos National Laboratory. His principal interest is in high performance computing applied to modeling, simulation and analysis of socio-technical systems. His current research applies to national infrastructure, especially telecommunication/computing, public health, and transportation. He has scientific experience in high performance computing and parallel processing applied to large-scale microscopic simulations, including original software design and debugging of very large, evolving systems of inter-operable computational systems, and efficient analysis and synthesis of massive data produced by multi-scale complex environments. Before attending graduate school he worked for a short time in nuclear theory, and had several publications in experimental biophysics from the Pennsylvania Muscle Institute and Bockus Research Institute. During graduate school he took a one year hiatus to start a company to work in analytic finance, and then spent time doing theoretical space physics at LANL. His graduate work eventually included theoretical and experimental fusion research, but concentrated on computational space plasma physics. He has publications in biophysics, analytic finance, education, space plasma physics and computer science, and is a co-inventor on the TRANSIMS patent. He has a Ph.D. in Theoretical Plasma Physics from the University of Texas at Austin.This revised version was published online in August 2005 with a corrected cover date.     

Distribution of gallium nanocrystals in Ga/MCM-41 mesocomposites by continuous-flow hyperpolarized 129Xe NMR spectroscopy

The distribution of gallium nanocrystals in mesoporous MCM-41 host were analyzed by continuous-flow hyperpolarized 129Xe NMR spectroscopy. In contrast to unclear TEM images for the high metal contents, laser-polarized 129Xe probe can detect the whole distribution of gallium in the MCM-41 host. It is found that gallium nanocrystals are included in the mesochannels of MCM-41; a part of them also remains in the interparticle voids. The distribution of gallium metal in MCM-41 is heterogeneous. Not all the mesochannels host metallic gallium even at a high gallium loading of 65.1 wt %. Variable temperature measurements can provide information on the xenon adsorption parameters. This approach opens a sensitive way to probe the distribution of high content species in porous host materials.     

Using comprehensive two-dimensional gas chromatography retention indices to estimate environmental partitioning properties for a complete set of diesel fuel hydrocarbons

Comprehensive two-dimensional gas chromatography (GCxGC) provides nearly complete composition data for some complex mixtures such as petroleum hydrocarbons. However, the potential wealth of physical property information contained in the corresponding two-dimensional chromatograms is largely untapped. We developed a simple but robust method to estimate GCxGC retention indices for diesel-range hydrocarbons. By exploiting n-alkanes as reference solutes in both dimensions, calculated retention indices were insensitive to uncertainty in the enthalpy of gas-stationary-phase transfer for a suite of representative diesel components. We used the resulting two-dimensional retention indices to estimate the liquid vapor pressures, aqueous solubilities, air-water partition coefficients, octanol-water partition coefficients, and vaporization enthalpies of a nearly complete set of diesel fuel hydrocarbons. Partitioning properties were typically estimated within a factor of 2; this is not as accurate as some previous estimation or measurement methods. However, these relationships may allow powerful and incisive analysis of phase-transfer processes affecting petroleum hydrocarbon mixtures in the environment. For example, GCxGC retention data might be used to quantitatively deconvolve the effects of water washing and evaporation on environmentally released diesel fuels.     

Harmonic phase-dispersion microscope with a Mach-Zehnder interferometer

Harmonic phase-dispersion microscopy (PDM) is a new imaging technique in which contrast is provided by differences in refractive index at two harmonically related wavelengths. We report a new configuration of the harmonic phase-dispersion microscope in a Mach-Zehnder geometry as an instrument for imaging biological samples. Several improvements on the earlier design are demonstrated, including a single-pass configuration and acousto-optic modulators for generating the heterodyne signals without mechanical arm scanning. We demonstrate quantitative phase-dispersion images of test structures and biological samples.     

Undersampling correction for array detector-based satellite spectrometers

Array detector-based instruments are now fundamental to measurements of ozone and other atmospheric trace gases from space in the ultraviolet, visible, and infrared. The present generation of such instruments suffers, to a greater or lesser degree, from undersampling of the spectra, leading to difficulties in the analysis of atmospheric radiances. We provide extended analysis of the undersampling suffered by modern satellite spectrometers, which include the Global Ozone Monitoring Experiment, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography, Ozone Monitoring Instrument, and Ozone Mapping and Profiler Suite. The analysis includes basic undersampling, the effects of binning into separate detector pixels, and the application of high-resolution Fraunhofer spectral data to correct for undersampling in many useful cases.     

On-chip HA/SSCP for the detection of hereditary haemochromatosis

Microfluidics provides a promising tool for meeting the growing demand for high-throughput and low-cost mutation detection technology. With conventional instrumentation, this need is often addressed by the combination of the single-strand conformation polymorphism (SSCP) and heteroduplex analysis (HA) methods. This paper describes an effective microchip-based method to analyse the three most commonly tested gene mutations (C282Y, H63D, and S65C) associated with hereditary haemochromatosis by simultaneously performing microchip-based SSCP and HA, directly upon samples of polymerase chain reaction (PCR) product. We have increased the sensitivity of mutation detection considerably by adapting and combining SSCP with HA. We are able to perform the analysis within several minutes by avoiding off-chip sample preparation steps for SSCP and HA (apart from the PCR). The most important mutation in the screening of populations for this disease is the C282Y mutation and this mutation has not previously been detected with methods of HA/SSCP suitable for microchip implementation. This is, to the best of our knowledge, the first microchip-based test applying SSCP and HA for all three of the most common HFE mutations.     

HIFU focusing efficiency and a twin annular array source for prostate treatment

A measure of focusing efficiency is introduced for high-intensity, focused ultrasound (HIFU). The measure consists of the fraction of the total acoustic power emitted that linearly propagates through a circle located at the focus. The medium is absorption-free water, and power is computed using pressure and the normal component of velocity. 3 MHz phased-array designs involving different element layouts and curvatures are placed in square apertures of length 2.2 cm. The acoustic fields of these devices then are propagated to on-axis foci. The resulting focal efficiencies then are calculated using a two wavelength (0.1 cm) radius circle. Among these array designs, an annular array with 27 wavelength-wide rings then is extended to be the basis of a twin phased-array device for prostate hyperthermia treatment. The two annular arrays are attached to door-like hinges to allow for joint two-dimensional focusing. The focusing efficiency of this device then is compared to rectangular element-array devices with the same 5.4 by 2.2 cm source extent. With the addition of absorption and finite-amplitude distortion, the heating rate and temperature rise produced by the twin annular device in prostate tissue is considered. As a final look at the potential of annular array-based designs, three larger 2 MHz devices are briefly considered for abdominal treatment.     

Characterization of digital waveforms using thermodynamic analogs: applications to detection of materials defects

We describe characterization of digital signals using analogs of thermodynamic quantities: the topological entropy, Shannon entropy, thermodynamic energy, partition function, specific heat at constant volume, and an idealized version of Shannon entropy in the limit of digitizing with infinite dynamic range and sampling rate. We show that analysis based on these quantities is capable of detecting differences between digital signals that are undetectable by conventional methods of characterization based on peak-to-peak amplitude or signal energy. We report the results of applying thermodynamic quantities to a problem from nondestructive materials evaluation: detection of foreign objects (FO) embedded near the surface of thin graphite/epoxy laminates using backscattered waveforms obtained by C-scanning the laminate. The characterization problem was to distinguish waveforms acquired from the region containing the FO from those acquired outside. In all cases the thermodynamic analogs exhibit significant increases (up to 20-fold) in contrast and for certain types of FO materials permit detection when energy or amplitude methods fail altogether.     

Weak correlation between the aberration dynamics of the human eye and the cardiopulmonary system

It is fairly well established that the higher-order aberrations of the eye fluctuate over relatively short time periods, but as yet there is no conclusive evidence regarding the origin of these fluctuations. We measured the aberrations and the pulse pressure wave simultaneously for five subjects. The aberrations were measured by using a Shack-Hartmann sensor sampling at 21.2 Hz. We decomposed the aberration data into Zernike coefficients up to and including fifth order and also calculated the rms wave-front error. From the pulse data the heart rate variability signal was also derived. Coherence function analysis showed that for all subjects there was a weak correlation between many of the aberrations and the pulse and the derived heart rate variability. The pulse and the heart rate variability can account for only 11% +/- 2% and 20% +/- 2%, respectively, of the aberration dynamics.