Network monitoring in multicast networks using network coding

In this paper we show how information contained in robust network codes can be used for passive inference of possible locations of link failures or losses in a network. For distributed randomized network coding, we bound the probability of being able to distinguish among a given set of failure events, and give some experimental results for one and two link failures in randomly generated networks. We also bound the required field size and complexity for designing a robust network code that distinguishes among a given set of failure events

On the utility of network coding in dynamic environments

Many wireless applications, such as ad-hoc networks and sensor networks, require decentralized operation in dynamically varying environments. We consider a distributed randomized network coding approach that enables efficient decentralized operation of multi-source multicast networks. We show that this approach provides substantial benefits over traditional routing methods in dynamically varying environments. We present a set of empirical trials measuring the performance of network coding versus an approximate online Steiner tree routing approach when connections vary dynamically. The results show that network coding achieves superior performance in a significant fraction of our randomly generated network examples. Such dynamic settings represent a substantially broader class of networking problems than previously recognized for which network coding shows promise of significant practical benefits compared to routing

Blending in Future Space-based Microlensing Surveys

We investigate the effect of blending in future gravitational microlensing surveys by carrying out simulation of Galactic bulge microlensing events to be detected from a proposed space-based lensing survey. From this simulation, we find that the contribution of the flux from background stars to the total blended flux will be equivalent to that from the lens itself despite the greatly improved resolution from space observations, implying that characterizing lenses from the analysis of the blended flux would not be easy. As a method to isolate events for which most of the blended flux is attributable to the lens, we propose to use astrometric information of source star image centroid motion. For the sample of events obtained by imposing a criterion that the centroid shift should be less than three times of the astrometric uncertainty among the events for which blending is noticed with blended light fractions $f_{\rm B}>0.2$, we estimate that the contamination of the blended flux by background stars will be less than 20% for most ($\sim 90$) of the sample events. The expected rate of these events is $\gtrsim 700$ events/yr, which is large enough for the statistical analysis of the lens populations.Comment: total 6 pages, including 5 figures, ApJ, in pres

ELECTROKINETICS-ASSISTED ELECTRICAL SENSORS FOR RAPID DETECTION OF BACTERIA

Department of Mechanical Enginering (Mechanical Engineering)An array of microfabricated interdigitated electrodes (IDEs) is the most commonly used form of electrode geometry for dielectrophoretic manipulation of biological particles in microfluidic biochips owing to simplicity of fabrication and ease of analysis. However, the dielectrophoretic force dramatically reduces as the distance from the electrode surface increasestherefore, the effective region is usually close to the electrode surface for a given electric potential difference. Here, I present a novel two-dimensional computational method for generating planar electrode patterns with enhanced volumetric electric fields, which I call the ???microelectrode discretization (MED)??? method. It involves discretization and reconstruction of planar electrodes followed by selection of the electrode pattern that maximizes a newly defined objective function, factor S, which is determined by the electric potentials on the electrode surface alone. In this study, IDEs were used as test planar electrodes. Two arrays of IDEs and respective MED-optimized electrodes were implemented in microfluidic devices for the selective capture of Escherichia coli against 1-??m-diameter polystyrene beads, and I experimentally observed that 1.4 to 35.8 times more bacteria were captured using the MED-optimized electrodes than the IDEs (p < 0.0016), with a bacterial purity against the beads of more than 99.8%. This simple design method offered simplicity of fabrication, highly enhanced electric field, and uniformity of particle capture, and can be used for many dielectrophoresis-based sensors and microfluidic systems. Dielectrophoresis (DEP) is usually effective close to the electrode surface. Several techniques have been developed to overcome its drawbacks and to enhance dielectrophoretic particle capture. Here a simple technique was presented of superimposing alternating current DEP (high-frequency signals) and electroosmosis (EOlow-frequency signals) between two coplanar electrodes (gap: 25 ??m) using a lab-made voltage adder for rapid and selective concentration of bacteria, viruses, and proteins, where the voltages and frequencies of DEP and EO were controlled separately. This signal superimposition technique enhanced bacterial capture (Escherichia coli K-12 against 1-??m-diameter polystyrene beads) more selectively (>99 %) and rapidly (~30 s) at lower DEP (5 Vpp) and EO (1.2 Vpp) potentials than those used in the conventional DEP capture studies. Nanometer-sized MS2 viruses and troponin I antibody proteins were also concentrated using the superimposed signals, and significantly more MS2 and cTnI-Ab were captured using the superimposed signals than the DEP (10 Vpp) or EO (2 Vpp) signals alone (p < 0.035) between the two coplanar electrodes and at a short exposure time (1 min). This technique has several advantages, such as simplicity and low cost of electrode fabrication, rapid and large collection without electrolysis. Electrokinetic technologies such as AC electro-osmosis (EO) and dielectrophoresis (DEP) have been used for effective manipulation of bacteria to enhance the sensitivity of an assay, and many previously reported electrokinetics-enhanced biosensors are based on stagnant fluids. An effective region for positive DEP for particle capture is usually too close to the electrode for the flowing particles to move toward the detection zone of a biosensor against the flow directionthis poses a technical challenge for electrokinetics-assisted biosensors implemented within pressure-driven flows, especially if the particles flow with high speed and if the detection zone is small. Here, a microfluidic single-walled carbon nanotubes (SWCNTs)-based field-effect transistor immunosensor was presented with electrohydrodynamic (EHD) focusing and DEP concentration for continuous and label-free detection of flowing Staphylococcus aureus in a 0.01?? phosphate buffered saline (PBS) solution. The EHD focusing involved AC EO and negative DEP to align the flowing particles along lines close to the bottom surface of a microfluidic channel for facilitating particle capture downstream in the detection zone. For feasibility, 380-nm-diameter fluorescence beads suspended in 0.001?? PBS were tested, and 14.6 times more beads were observed to be concentrated on the detection area with EHD focusing. Moreover, label-free, continuous, and selective measurement of S. aureus in 0.01?? PBS was demonstrated, showing good linearity between the relative changes in electrical conductance of the SWCNTs and logarithmic S. aureus concentrations, a capture/detection time of 35 min, and limit of detection of 150 CFU/mL, as well as high specificity through electrical manipulation and biological interaction.ope

All learning is local: Multi-agent learning in global reward games

In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efficient algorithm that in part uses a linear system to model the world from a single agent’s limited perspective, and takes advantage of Kalman filtering to allow an agent to construct a good training signal and effectively learn a near-optimal policy in a wide variety of settings. A sequence of increasingly complex empirical tests verifies the efficacy of this technique.Singapore-MIT Alliance (SMA