Path diversification for future internet end-to-end resilience and survivability

Path Diversification is a new mechanism that can be used to select multiple paths between a given ingress and egress node pair using a quantified diversity measure to achieve maximum flow reliability. The path diversification mechanism is targeted at the end-to-end layer, but can be applied at any level for which a path discovery service is available. Path diversification also takes into account service requirements for low-latency or maximal reliability in selecting appropriate paths. Using this mechanism will allow future internetworking architectures to exploit naturally rich physical topologies to a far greater extent than is possible with shortest-path routing or equal-cost load balancing. We describe the path diversity metric and its application at various aggregation levels, and apply the path diversification process to 13 real-world network graphs as well as 4 synthetic topologies to asses the gain in flow reliability. Based on the analysis of flow reliability across a range of networks, we then extend our path diversity metric to create a composite compensated total graph diversity metric that is representative of a particular topology’s survivability with respect to distributed simultaneous link and node failures. We tune the accuracy of this metric having simulated the performance of each topology under a range of failure severities, and present the results. The topologies used are from national-scale backbone networks with a variety of characteristics, which we characterize using standard graph-theoretic metrics. The end result is a compensated total graph diversity metric that accurately predicts the survivability of a given network topology.     

Travelling-wave photodetectors with 172-GHz bandwidth and 76-GHzbandwidth-efficiency product

Results of the first fabrication and measurement of travelling-wave photodetectors are reported. The devices have bandwidths as high as 172 GHz, the highest reported for a p-i-n photodetector, and bandwidth-efficiency products as large as 76 GHz, the largest reported for any photodetector without gain. Comparisons with vertically illuminated and waveguide photodetectors fabricated on the same wafer establish the superior performance of travelling-wave photodetectors. Microwave loss on the travelling-wave photodetector structure is identified as a bandwidth limitation     

Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition

Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from super-linear increases in computational time with increasing data size and number of signals being processed (data dimension). Certain principal machine-learning algorithms are commonly found embedded in larger detection, estimation, or classification operations. Three such principal algorithms are the Parzen window-based, non-parametric estimation of Probability Density Functions (PDFs), K-means clustering and correlation. Because they form an integral part of numerous machine-learning applications, fast and efficient execution of these algorithms is extremely desirable. FPGA-based reconfigurable computing (RC) has been successfully used to accelerate computationally intensive problems in a wide variety of scientific domains to achieve speedup over traditional software implementations. However, this potential benefit is quite often not fully realized because creating efficient FPGA designs is generally carried out in a laborious, case-specific manner requiring a great amount of redundant time and effort. In this paper, an approach using pattern-based decomposition for algorithm acceleration on FPGAs is proposed that offers significant increases in productivity via design reusability. Using this approach, we design, analyze, and implement a multi-dimensional PDF estimation algorithm using Gaussian kernels on FPGAs. First, the algorithm’s amenability to a hardware paradigm and expected speedups are predicted. After implementation, actual speedup and performance metrics are compared to the predictions, showing speedup on the order of 20× over a 3.2 GHz processor. Multi-core architectures are developed to further improve performance by scaling the design. Portability of the hardware design across multiple FPGA platforms is also analyzed. After implementing the PDF algorithm, the value of pattern-based decomposition to support reuse is demonstrated by rapid development of the K-means and correlation algorithms.     

Numerical analysis on compliance and electrical behavior of multi-copper-column flip-chip interconnects for wafer-level packaging

This paper presents modeling and simulation results of a modified copper-column-based flip-chip interconnect with ultrafine pitch for wafer-level packaging, and the process and prototyping procedure are described as well. This interconnect consists of multiple copper columns which are electrically in parallel and supporting a solder bump. A simple analytical model has been developed for correlation between the interconnect geometry and the thermal fatigue life. In comparison to the conventional single-copper-column (SCC) interconnects, numerical analysis reveals that the multi-copper-column (MCC) interconnect features enhanced compliances and, hence, higher thermomechanical reliability, while the associated electrical parasitics (R, L, and C) at dc and moderate frequencies are still kept low. Parametric studies reveal the effects of geometric parameters of MCC interconnects on both compliances and electrical parasitics, which in turn facilitate design optimization for best performance. By using coplanar waveguides (CPWs) as feed lines on both chip and package substrate, a high-frequency (up to 40 GHz) S-parameter analysis is conducted to investigate the transmission characteristics of the MCC interconnects within various scenarios which combines various interconnect pitches and common chip and package substrates. An equivalent lumped circuit model is proposed and the circuit parameters (R, L, C, and G) are obtained throughout a broad frequency range. Good agreement is achieved for the transmission characteristics between the equivalent lumped circuit model and direct simulation results.     

A Spatiotemporal Framework for Estimating Trial-to-Trial Amplitude Variation in Event-Related MEG/EEG

A spatiotemporal framework for estimating trial-to-trial variability in evoked response (ER) data is presented. Spatial and temporal bases capture the aspects of the response that are consistent across trials, while the basis expansion coefficients represent the variable components of the response. We focus on the simplest case of constant spatiotemporal response shape and varying amplitude across trials. Two different constraints on the amplitude evolution are employed to effectively integrate the individual responses and improve robustness at low SNR. The linear dynamical system response constraint estimates the current trial amplitude as an unknown constant scaling of the estimate in the previous trial plus zero-mean Gaussian noise with unknown variance. The independent response constraint estimates response amplitudes across trials as independent Gaussian random variables having unknown mean and variance. We develop a generalized expectation-maximization algorithm to obtain the maximum-likelihood (ML) estimates of the signal waveform, noise covariance matrix, and unknown constraint parameters. ML source localization is achieved by scanning the likelihood over different sets of spatial bases. We demonstrate the variability estimation and source localization effectiveness of the proposed algorithms using both real and simulated ER data.     

Interconnecting networks with optimized service provisioning

Telecommunication Systems - A recent trend of peering at geo-diversified Internet exchange points (IXPs) has empowered decades-old proposal of inter-networking and opened up new avenues of business...     

Synthesis and Microwave Dielectric Properties of SrLa4−x Pr x Ti5O17 (0 ≤ x ≤ 4) Ceramics

Single-phase ceramics in the SrLa_4?x Pr _x La₄Ti₅O₁₇ (0 ≤ x ≤ 4) series were processed via a solid-state sintering route. X-ray diffraction analysis revealed single-phase ceramics for all the compositions. The molar volume (V _m) decreased while the theoretical density (ρ _th) increased with increase in the Pr content. Substitution of Pr³⁺ decreased the relative permittivity (ε _r) and temperature coefficient of resonant frequency (τ _f) due to its smaller ionic polarizability (α _d) and ionic radius than La³⁺. In the present study, ε _r ≈ 54.2, Q _u f ₀  ≈ 7935 GHz, and τ _f  ≈ ?20.3 ppm/°C were achieved for the composition with x = 2 (i.e., SrLa₂Pr₂Ti₅O₁₇).     

Digital signal propagation delay in a nano-circuit containing reactive and resistive elements

The transient switching delay in a micro/nano-scale circuit containing resistive and reactive elements are sternly affected by the surge in the resistance arising from sub-linear current-voltage (I-V) characteristics limited by the velocity and current saturation. The saturation arises due to the realignment of randomly oriented velocity vectors to the unidirectional streamlined ones in a high electric field when voltage applied across a resistor exceeds its decreasing critical value with reduced channel length. The frequency response f = 1/2πτ_t is affected by a transit time delay τ_t is lower than that predicted from the application of Ohm’s law. The resistance surge dramatically boosts the RC time constant and switching delay and attenuates the L/R time constant and switching delay.     

Least-Square Collaborative Beamforming Linear Array for Steering Capability in Green Wireless Sensor Networks

This paper presents a collaborative beamforming (CB) technique to organize the sensor node's location in a linear array for green wireless sensor network (WSN) applications. In this method, only selected clusters and active CB nodes are needed each time to perform CB in WSNs. The proposed least-square linear array (LSLA) manages to select nodes to perform as a linear antenna array (LAA), which is similar to and as outstanding as the conventional uniform linear array (ULA). The LSLA technique is also able to solve positioning error problems that exist in the random nodes deployment. The beampattern fluctuations have been analyzed due to the random positions of sensor nodes. Performances in terms of normalized power gains are given. It is demonstrated by a simulation that the proposed technique gives similar performances to the conventional ULA and at the same time exhibits lower complexity.     

Improved Hydrogen Capping Effect in n-Type Crystalline Silicon Solar Cells by SiN(Si-Rich)/SiN(N-Rich) Stacked Passivation

The effect of hydrogen capping of SiN(Si-rich)/SiN(N-rich) stacks for n-type c-Si solar cells was investigated. Use of a passivation layer consisting of Si-rich SiN with a refractive index (n) of 2.7 and N-rich SiN with a refractive index of 2.1 improved the thermal stability. A single SiN passivation layer with a refractive index of 2.05 resulted in an initial lifetime of 200 μs whereas the layer with a refractive index of 2.7 resulted in a high initial lifetime of 2 ms, but the layer degraded rapidly after firing. A stacked passivation layer with refractive indices of 2.1 and 2.7 had a stable lifetime of 1.5 ms with an implied open-circuit voltage (iV _oc) of 720 mV after firing. The thermally stable passivation mechanism with changing amounts of Si–N and Si–H bonding was analyzed by Fourier-transform infrared (FTIR) spectroscopy. Incorporation of the SiN _x stack layer (2.7 + 2.1) into the passivated rear of n-type Cz silicon screen-printed solar cells resulted in energy conversion efficiency of 19.69%. Improved internal quantum efficiency in the long-wavelength range above 900 nm, with V _oc of 630 mV, is mainly because of superior passivation of the rear surface compared with conventional solar cells.