Proactive DAD: A Fast Address-Acquisition Strategy for Mobile IPv6 Networks

The increasing number of Wi-Fi-compatible mobile devices highlights various wireless access challenges, including the need for smooth hand offs between Internet attachment points in mobile IPv6 networks. To confirm address uniqueness in a new domain, mobile nodes must run duplicate address detection (DAD), which is a time-consuming process. The Proactive DAD approach uses topology information and layer-2 signals to predict the new network domains prior to or in parallel with layer-3 hand offs. Experimental results show that P-DAD can significantly reduce both hand-off latency and packet loss     

Hybrid Address Configuration for Tree-based Wireless Sensor Networks

This letter proposes a new scheme to alleviate the issue on address acquisition failure in wireless sensor networks (WSNs). The basic idea is to use a hierarchical address structure to make the proposed scheme less susceptible to physical distribution of WSN devices. Simulation results show that the new scheme significantly reduces the failure probability.     

An Optical Flow-Based Approach to Robust Face Recognition Under Expression Variations

Face recognition is one of the most intensively studied topics in computer vision and pattern recognition, but few are focused on how to robustly recognize faces with expressions under the restriction of one single training sample per class. A constrained optical flow algorithm, which combines the advantages of the unambiguous correspondence of feature point labeling and the flexible representation of optical flow computation, has been developed for face recognition from expressional face images. In this paper, we propose an integrated face recognition system that is robust against facial expressions by combining information from the computed intraperson optical flow and the synthesized face image in a probabilistic framework. Our experimental results show that the proposed system improves the accuracy of face recognition from expressional face images.     

Superresolution frequency estimation by alternating notchperiodogram

A novel periodogram-based maximum-likelihood algorithm is proposed for a frequency estimation problem. It is called an alternating notch-periodogram algorithm (ANPA), since the original multidimensional maximum likelihood problem is decomposed into a sequence of much simpler one-dimensional problems of finding the peaks of notch periodograms. The ANPA achieves superresolution and a very low SNR threshold and can be computed and implemented in several efficient ways. First, with FFT and a concurrent Gram-Schmidt procedure using Schur's recursions, the notch periodogram can be computed without any costly eigendecomposition and matrix inversion. This approach can further lead to a mapping of the notch periodogram onto a VLSI architecture consisting mainly of a highly pipelined notch processor and two FFT processors. Second, without degrading the excellent performance of ANPA, the notch periodogram can be simplified and approximated to provide further computational reduction and implementational simplicity     

Fault-Tolerant Mesh-Based NoC with Router-Level Redundancy

The aggressively scaled CMOS technology is increasingly threatening the dependability of network-on-chips (NoCs) architecture. In a mesh-based NoC, a faulty router or broken link may isolate a well functional processing element (PE). Also, a set of faulty routers may form isolated regions, which can degrade the design. In this paper, we propose a router-level redundancy (RLR) fault-tolerant scheme that differs from the traditional microarchitecture-level redundancy (MLR) approach to relieve the problem of isolated PE and isolated region. By simply adding one spare router within each router set in a mesh, RLR can be created and connection paths between adjacent routers can be diversified. To exploit this extra resource, two reconfiguration algorithms are demonstrated to detour observed faulty routers/links. The proposed RLR fault-tolerant scheme can tolerate at most one faulty router within a router set. After the reconfiguration, the original mesh topology is maintained. As a result, the proposed architecture does not need any support from the network layer routing algorithms. The scheme has been evaluated based on the three fault-tolerant metrics: reliability, mean time to failure (MTTF), and yield. The experimental results show that the performance RLR increases as the size of NoC grows; however, the relative connection cost decreases at the same time. This characteristic makes our architecture suitable for large-scale NoC designs.

     

Remote catalyzation for direct formation of graphene layers on oxides

Direct deposition of high-quality graphene layers on insulating substrates such as SiO(2) paves the way toward the development of graphene-based high-speed electronics. Here, we describe a novel growth technique that enables the direct deposition of graphene layers on SiO(2) with crystalline quality potentially comparable to graphene grown on Cu foils using chemical vapor deposition (CVD). Rather than using Cu foils as substrates, our approach uses them to provide subliming Cu atoms in the CVD process. The prime feature of the proposed technique is remote catalyzation using floating Cu and H atoms for the decomposition of hydrocarbons. This allows for the direct graphitization of carbon radicals on oxide surfaces, forming isolated low-defect graphene layers without the need for postgrowth etching or evaporation of the metal catalyst. The defect density of the resulting graphene layers can be significantly reduced by tuning growth parameters such as the gas ratios, Cu surface areas, and substrate-to-Cu distance. Under optimized conditions, graphene layers with nondiscernible Raman D peaks can be obtained when predeposited graphite flakes are used as seeds for extended growth.     

Generalized CAZA sequences

ABSTRACT

Constant amplitude zero auto-correlation (CAZA) sequences and periodic sequences have been widely used as preambles for synchronization and channel estimation in the literature. In this paper, we first construct generalized CAZA (GCAZA) sequences in the time domain. Then, their Cramer-Rao bounds containing no matrix inversion for the purpose of joint carrier frequency offset and channel impulse response estimation are derived. The properties of auto-correlation and the discrete Fourier transform of a GCAZA are then presented analytically. The latter also explains the relationship between the conventional frequency-domain CAZA and the proposed time-domain GCAZA. Finally, we conduct numerical simulations and compare the results with existing sequences in the literature for fading channels.     

Data race avoidance and replay scheme for developing and debugging parallel programs on distributed shared memory systems

Distributed shared memory (DSM) allows parallel programs to run on distributed computers by simulating a global virtual shared memory, but data racing bugs may easily occur when the threads of a multi-threaded process concurrently access the physically distributed memory. Earlier tools to help programmers locate data racing bugs in non-DSM parallel programs are not easily applied to DSM systems. This study presents the data race avoidance and replay scheme (DRARS) to assist debugging parallel programs on DSM or multi-core systems. DRARS is a novel tool which controls the consistency protocol of the target program, automatically preventing a large class of data racing bugs when the parallel program is subsequently run, obviating much of the need for manual debugging. For data racing bugs that cannot be avoided automatically, DRARS performs a deterministic replay-type function on DSM systems, faithfully reproducing the behavior of the parallel program during run time. Because one class of data racing bugs has already been eliminated, the remaining manual debugging task is greatly simplified. Unlike previous debugging methods, DRARS does not require that the parallel program be written in a specific style or programming language. Moreover, DRARS can be implemented in most consistency protocols. In this paper, DRARS is realized and verified in real experiments using the eager release consistency protocol on a DSM system with various applications.     

Dual-Metal Interbonding as the Chemical Facilitator for Single-Atom Dispersions

Atomically dispersed catalysts, with maximized atom utilization of expensive metal components and relatively stable ligand structures, offer high reactivity and selectivity. However, the formation of atomic-scale metals without aggregation remains a formidable challenge due to thermodynamic stabilization driving forces. Here, a top-down process is presented that starts from iron nanoparticles, using dual-metal interbonds (Rh Fe bonding) as a chemical facilitator to spontaneously convert Fe nanoparticles to single atoms at low temperatures. The presence of Rh Fe bonding between adjacent Fe and Rh single atoms contributes to the thermodynamic stability, which facilitates the stripping of a single Fe atom from the Fe nanoparticles, leading to the stabilized single atom. The dual single-atom Rh–Fe catalyst renders excellent electrocatalytic performance for the hydrogen evolution reaction in an acidic electrolyte. This discovery of dual-metal interbonding as a chemical facilitator paves a novel route for atomic dispersion of chemical metals and the design of efficient catalysts at the atomic scale.