Buffered Cross-Bar Switches, Revisited: Design Steps, Proofs and Simulations Towards Optimal Rate and Minimum Buffer Memory

Regarding the packet-switching problem, we prove that the weighed max-min fair service rates comprise the unique Nash equilibrium point of a strategic game, specifically a throughput auction based on a “least-demanding first-served” principle. We prove that a buffered crossbar switch can converge to this equilibrium with no pre-computation or internal acceleration, with either randomized or deterministic schedulers, (the latter with a minimum buffering of a single-packet per crosspoint). Finally, we present various simulation results that corroborate and extend our analysis.      

On Accurate and Asymmetry-Aware Measurement of Link Quality in Wireless Mesh Networks

This paper presents a highly efficient and accurate link-quality measurement framework, called Efficient and Accurate link-quality monitoR (EAR), for multihop wireless mesh networks (WMNs) that has several salient features. First, it exploits three complementary measurement schemes: passive, cooperative, and active monitoring. By adopting one of these schemes dynamically and adaptively, EAR maximizes the measurement accuracy, and its opportunistic use of the unicast application traffic present in the network minimizes the measurement overhead. Second, EAR effectively identifies the existence of wireless link asymmetry by measuring the quality of each link in both directions of the link, thus improving the utilization of network capacity by up to 114%. Finally, its cross-layer architecture across both the network layer and the IEEE 802.11-based device driver makes EAR easily deployable in existing multihop wireless mesh networks without system recompilation or MAC firmware modification. EAR has been evaluated extensively via both ns-2-based simulation and experimentation on our Linux-based implementation in a real-life testbed. Both simulation and experimentation results have shown EAR to provide highly accurate link-quality measurements with minimum overhead.      

Message Scheduling for the FlexRay Protocol: The Static Segment

In recent years, time-triggered communication protocols have been developed to support time-critical applications for in-vehicle communication. In this respect, the FlexRay protocol is likely to become the de facto standard. In this paper, we investigate the scheduling problem of periodic signals in the static segment of FlexRay. We identify and solve two subproblems and introduce associated performance metrics: 1) The signals have to be packed into equal-size messages to obey the restrictions of the FlexRay protocol, while using as little bandwidth as possible. To this end, we formulate a nonlinear integer programming (NIP) problem to maximize bandwidth utilization. Furthermore, we employ the restrictions of the FlexRay protocol to decompose the NIP and compute the optimal message set efficiently. 2) A message schedule has to be determined such that the periodic messages are transmitted with minimum jitter. For this purpose, we propose an appropriate software architecture and derive an integer linear programming (ILP) problem that both minimizes the jitter and the bandwidth allocation. A case study based on a benchmark signal set illustrates our results.      

Unequal Error Protection: An Information-Theoretic Perspective

An information-theoretic framework for unequal error protection is developed in terms of the exponential error bounds. The fundamental difference between the bit-wise and message-wise unequal error protection ( UEP) is demonstrated, for fixed-length block codes on discrete memoryless channels (DMCs) without feedback. Effect of feedback is investigated via variable-length block codes. It is shown that, feedback results in a significant improvement in both bit-wise and message-wise UEPs (except the single message case for missed detection). The distinction between false-alarm and missed-detection formalizations for message-wise UEP is also considered. All results presented are at rates close to capacity.      

Novel Scheme for Joint Estimation of SNR, Doppler, and Carrier Frequency Offset in Double-Selective Wireless Channels

As receiver performance will be degraded by carrier frequency offset (CFO), Doppler shift, and low signal-to-noise ratio (SNR), a novel estimator that jointly considers CFO, Doppler shift, and SNR is proposed in this paper. The proposed algorithm uses the Fourier transform (FT) to calculate the power spectral density of time-varying channels through channel estimates. Then, a new periodogram technique is utilized to estimate CFO, Doppler shift, and SNR together. Unlike conventional methods in sinusoid estimation, which rely on the peak-value search of a periodogram, this paper exploits the hypothesis test to address the random frequency modulation of time-varying channels. Furthermore, to optimize estimation performance, a theoretical analysis is also provided on the influences of some key parameters, e.g., the length of the signal processed with fast FT , the amplitude threshold value, the SNR dynamic range, and the velocity dynamic range. Correspondingly, the appropriate key parameters are chosen according to this analysis and are validated by simulations. The results are consistent with our analysis and present high accuracy over a wide range of velocities and SNRs.      

Analysis of a Mixed Strategy for Multiple Relay Networks

Infrastructure-based wireless communications systems as well as ad-hoc networks experience a growing importance in present-day telecommunications. An increased density and popularity of mobile terminals poses the question how to exploit wireless networks more efficiently. One possibility is to use relay nodes supporting the end-to-end communication of two nodes. In their landmark paper, Cover and El Gamal proposed different coding strategies for the single-relay channel. These strategies are the decode-and-forward and compress-and-forward approach, as well as a general lower bound on the capacity of a single-relay network which relies on the combined application of the previous two strategies. So far, only parts of their work—the decode-and-forward and the compress-and-forward strategy—have been applied to networks with multiple relays. In this paper a generalizing framework for multiple-relay networks is derived using a combined approach of partial decode-and-forward and the ideas of successive refinement with different side information. After describing the protocol structure, the achievable rates for the discrete memoryless relay channel as well as the Gaussian multiple-relay channel are presented and analyzed. Using these results the derived framework is compared with protocols of lower complexity, e.g., multilevel decode-and-forward and distributed compress-and-forward.      

Noncoherent Synchronization of UWB-IR Multiple-Antenna Multipath Channels

This paper deals with the maximum-likelihood (ML) noncoherent data-aided (e.g., no blind) synchronization of multiple-antenna ultrawideband impulse-radio (UWB-IR) terminals that operate over broadband channels and are affected by multipath fading with a priori unknown number of paths and path-gain statistics. The synchronizer that we developed achieves the ML data-aided joint estimate of the number of paths and their arrival times (e.g., time delays), without requiring any a priori knowledge and/or a posteriori estimate of the amplitude (e.g., module and sign) of the channel gains. The ultimate performance of the proposed synchronizer is evaluated (in closed form) by developing the corresponding CramÉr–Rao bound (CRB), and the analytical conditions for achieving this bound are provided. The performance gain for the synchronization accuracy of multipath-affected UWB-IR signals arising from the exploitation of the multiple-antenna paradigm is (analytically) evaluated. Furthermore, a low-cost sequential implementation of the proposed synchronizer is detailed. It requires an all-analog front-end circuitry composed of a bank of sliding-window correlators, whose number is fully independent from the number of paths comprising the underlying multiple-antenna channel. Finally, the actual performance of the proposed synchronizer is numerically tested under both the signal acquisition and tracking operating conditions.      

Using Hidden Markov Models in Vehicular Crash Detection

This paper presents a system for automotive crash detection based on hidden Markov models (HMMs). The crash pulse library used for training comprises a number of head-on and oblique angular crash events involving rigid and offset deformable barriers. Stochastic distribution characteristics of crash signals are validated to ensure conformity with the modeling assumptions. This step is achieved by analyzing the quantile–quantile (Q–Q) plot of actual pulses against the assumed bivariate Gaussian distribution. HMM parameters are next induced by utilizing the expectation–maximization (EM) procedure. The search for an optimal crash pulse model proceeds using the “leave-one-out” technique with the exploration encompassing both fully connected and left–right HMM topologies. The optimal crash pulse architecture is identified as a seven-state left–right HMM with its parameters computed using real and computer-aided engineering (CAE)-generated data. The system described in the paper has the following advantages. First, it is fast and can accurately detect crashes within 6 ms. Second, its implementation is simple and uses only two sensors, which makes it less vulnerable to failures, considering the overall simplicity of interconnects. Finally, it represents a general and modularized algorithm that can be adapted to any vehicle line and readily extended to use additional sensors.      

Distributed Throughput Maximization in Wireless Mesh Networks via Pre-Partitioning

This paper considers the interaction between channel assignment and distributed scheduling in multi-channel multi-radio Wireless Mesh Networks (WMNs). Recently, a number of distributed scheduling algorithms for wireless networks have emerged. Due to their distributed operation, these algorithms can achieve only a fraction of the maximum possible throughput. As an alternative to increasing the throughput fraction by designing new algorithms, we present a novel approach that takes advantage of the inherent multi-radio capability of WMNs. We show that this capability can enable partitioning of the network into subnetworks in which simple distributed scheduling algorithms can achieve 100% throughput. The partitioning is based on the notion of Local Pooling. Using this notion, we characterize topologies in which 100% throughput can be achieved distributedly. These topologies are used in order to develop a number of centralized channel assignment algorithms that are based on a matroid intersection algorithm. These algorithms pre-partition a network in a manner that not only expands the capacity regions of the subnetworks but also allows distributed algorithms to achieve these capacity regions. We evaluate the performance of the algorithms via simulation and show that they significantly increase the distributedly achievable capacity region. We note that while the identified topologies are of general interference graphs, the partitioning algorithms are designed for networks with primary interference constraints.      

NetQuest: A Flexible Framework for Large-Scale Network Measurement

In this paper, we present NetQuest, a flexible framework for large-scale network measurement. We apply Bayesian experimental design to select active measurements that maximize the amount of information we gain about the network path properties subject to given resource constraints. We then apply network inference techniques to reconstruct the properties of interest based on the partial, indirect observations we get through these measurements.      

A Control Strategy for Four-Switch Three-Phase Brushless DC Motor Using Single Current Sensor

A control strategy based on single current sensor is proposed for a four-switch three-phase brushless dc (BLDC) motor system to lower cost and improve performance. The system's whole working process is divided into two groups. In modes 2, 3, 5, and 6, where phase c works, phase- c current is sensed to control phases a and b, and phase-c current is consequently regulated. In modes 1 and 4, the combination of four suboperating modes for controlling phase-c current is proposed based on detailed analysis on the different rules that these operating modes have on phase-c current. Phase-c current is maintained at nearly zero level first, and phase- a and phase-b currents are regulated by speed circle. To improve control performance, a single-neuron adaptive proportional–integral (PI) algorithm is adopted to realize the speed regulator. Simulation and experimental systems are set up to verify the proposed strategy. According to simulation and experimental results, the proposed strategy shows good self-adapted track ability with low current ripple and strong robustness to the given speed reference model. Also, the structure of the drive is simplified.      

Design and Analysis of Isolated Noise-Tolerant (INT) Technique in Dynamic CMOS Circuits

Along with the progress of advanced VLSI technology, noise issues in dynamic circuits have become an imperative design challenge. The twin-transistor design is the current state-of-the-art design to enhance the noise immunity in dynamic CMOS circuits. To achieve the high noise-tolerant capability, in this paper, we propose a new isolated noise-tolerant (INT) technique which is a mechanism to isolate noise tolerant circuits from noise interference. Simulation results show that the proposed 8-bit INT Manchester adder can achieve 1.66$times$ average noise threshold energy (ANTE) improvement. In addition, it can save 34% power delay product (PDP) in low signal-to-noise ratio (SNR) environments as compared with the 8-bit twin-transistor Manchester adder under TSMC 0.18-$mu$ m process.      

Single-Exclusion Number and the Stopping Redundancy of MDS Codes

For a linear block code ${cal C}$, its stopping redundancy is defined as the smallest number of check nodes in a Tanner graph for ${cal C}$, such that there exist no stopping sets of size smaller than the minimum distance of ${cal C}{bf .},$ Schwartz and Vardy conjectured that the stopping redundancy of a maximum-distance separable (MDS) code should only depend on its length and minimum distance.      

Robust Precoder Adaptation for MIMO Links With Noisy Limited Feedback

In this paper, we propose two robust limited feedback designs for multiple-input multiple-output (MIMO) adaptation. The first scheme, namely, the combined design jointly optimizes the adaptation, CSIT (channel state information at the transmitter) feedback as well as index assignment strategies. The second scheme, namely, the decoupled design, focuses on the index assignment problem given an error-free limited feedback design. Simulation results show that the proposed framework has significant capacity gain compared to the naive design (designed assuming there is no feedback error). Furthermore, for large number of feedback bits $C_{rm fb}$, we show that under two-nearest constellation feedback channel assumption, the MIMO capacity loss (due to noisy feedback) of the proposed robust design scales like ${cal O}(P_e2^{-{{C_{rm fb}}over{t+1}}})$ for some positive integer $t$. Hence, the penalty due to noisy limited feedback in the proposed robust design approaches zero as $C_{rm fb}$ increases.      

Impact of Hot-Potato Routing Changes in IP Networks

Despite the architectural separation between intradomain and interdomain routing in the Internet, intradomain protocols do influence the path-selection process in the Border Gateway Protocol (BGP). When choosing between multiple equally-good BGP routes, a router selects the one with the closest egress point, based on the intradomain path cost. Under such hot-potato routing, an intradomain event can trigger BGP routing changes. To characterize the influence of hot-potato routing, we propose a technique for associating BGP routing changes with events visible in the intradomain protocol, and apply our algorithm to a tier-1 ISP backbone network. We show that (i) BGP updates can lag 60 seconds or more behind the intradomain event; (ii) the number of BGP path changes triggered by hot-potato routing has a nearly uniform distribution across destination prefixes; and (iii) the fraction of BGP messages triggered by intradomain changes varies significantly across time and router locations. We show that hot-potato routing changes lead to longer delays in forwarding-plane convergence, shifts in the flow of traffic to neighboring domains, extra externally-visible BGP update messages, and inaccuracies in Internet performance measurements.      

Fault Tolerance Analysis for Switched Systems Via Global Passivity

In this brief, we introduce the passivity theory into the fault tolerance analysis for switched systems. We propose a “global passivity” concept which means that the total energy stored by the switched system is less than the total energy supplied from the outside. The individual passivity of each mode is not required, and the stability of the system can be achieved via the global energy dissipativity in the presence of faults. We further provide a “periodic fault tolerant passivity” to check the fault tolerance easily. The obtained results are extended to feedback interconnected systems. A switched RLC circuit example is taken to illustrate the efficiency of the proposed results.      

Site-Specific Knowledge and Interference Measurement for Improving Frequency Allocations in Wireless Networks

We present new frequency allocation schemes for wireless networks and show that they outperform all other published work. Two categories of schemes are presented: 1) those purely based on measurements and 2) those that use site-specific knowledge, which refers to knowledge of building layouts, the locations and electrical properties of access points (APs), users, and physical objects. In our site-specific knowledge-based algorithms, a central network controller communicates with all APs and has site-specific knowledge so that it can a priori predict the received power from any transmitter to any receiver. Optimal frequency assignments are based on predicted powers to minimize interference and maximize throughput. In our measurement-based algorithms, clients periodically report in situ interference measurements to their associated APs; then, the APs' frequency allocations are adjusted based on the reported measurements. Unlike other work, we minimize interference seen by both users and APs, use a physical model rather than a binary model for interference, and mitigate the impact of rogue interference. Our algorithms consistently yield high throughput gains, irrespective of the network topology, AP activity level, number of APs, rogue interferers, and available channels. Our algorithms outperform the best published work by 18.5%, 97.6%, and 1180% for median, 25th percentile, and 15th percentile user throughputs, respectively.      

A Change-of-Measure Approach to Per- Flow Delay Measurement Combining Passive and Active Methods: Mathematical Formulation for CoMPACT Monitor

One problem with active measurement is that, while it is suitable for measuring time-average network performance, it is difficult to measure per-flow quality of service (QoS), which is defined as the average over packets in the flow. To achieve such per-flow QoS measurement, the authors proposed a new technique, called the change- of- measure-based passive/active monitoring (CoMPACT Monitor), which is based on the change-of-measure framework in probability/measure theory and transforms actively obtained information by using passively monitored data. This technique enables us to concurrently measure one-way delay information about individual users, applications, and organizations in detail in a lightweight manner. This paper presents the mathematical formulation for the CoMPACT Monitor and verifies that it works well under some weak conditions. In addition, we investigate its characteristics regarding several implementation issues through simulation and actual network experiments. The results reveal that our technique provides highly qualified estimates involving only a limited amount of extra traffic from active probes.      

Analysis of Two Alternative ADI-FDTD Formulations for Transverse-Electric Waves in Lossy Materials

A numerical dispersion analysis of the alternating-direction implicit finite-difference time-domain method for transverse-electric waves in lossy materials is presented. Two different finite-difference approximations for the conduction terms are considered: the double-average and the synchronized schemes. The numerical dispersion relation is derived in a closed form and validated through numerical simulations. This study shows that, despite its popularity, the accuracy of the double-average scheme is sensitive to how well the relaxation-time constant of the material is resolved by the time step. Poor resolutions lead to unacceptably large numerical errors. On the other hand, for good conductors, the synchronized scheme allows stability factors as large as 100 to be used without deteriorating the accuracy significantly.      

Performance-Oriented Parameter Dimension Reduction of VLSI Circuits

To account for the growing process variability in modern VLSI technologies, circuit models parameterized in a multitude of parametric variations are becoming increasingly indispensable in robust circuit design. However, the high parameter dimensionality can introduce significant complexity and may even render variation-aware performance analysis and optimization completely intractable. We present a performance-oriented parameter dimension reduction framework to reduce the modeling complexity associated with high parameter dimensionality. Our framework has a theoretically sound statistical basis, namely, reduced rank regression (RRR) and its various extensions that we have introduced for more practical VLSI circuit modeling. For a variety of VLSI circuits including interconnects and CMOS digital circuits, it is shown that this parameter reduction framework can provide more than one order of magnitude reduction in parameter dimensionality. Such parameter reduction immediately leads to reduced simulation cost in sampling-based performance analysis, and more importantly, highly efficient parameterized sub-circuit models that are instrumental in tackling the complexity of variation-tolerance VLSI system design.