6,740 research outputs found

    Cooperative and Distributed Localization for Wireless Sensor Networks in Multipath Environments

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    We consider the problem of sensor localization in a wireless network in a multipath environment, where time and angle of arrival information are available at each sensor. We propose a distributed algorithm based on belief propagation, which allows sensors to cooperatively self-localize with respect to one single anchor in a multihop network. The algorithm has low overhead and is scalable. Simulations show that although the network is loopy, the proposed algorithm converges, and achieves good localization accuracy

    Distributed Local Linear Parameter Estimation using Gaussian SPAWN

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    We consider the problem of estimating local sensor parameters, where the local parameters and sensor observations are related through linear stochastic models. Sensors exchange messages and cooperate with each other to estimate their own local parameters iteratively. We study the Gaussian Sum-Product Algorithm over a Wireless Network (gSPAWN) procedure, which is based on belief propagation, but uses fixed size broadcast messages at each sensor instead. Compared with the popular diffusion strategies for performing network parameter estimation, whose communication cost at each sensor increases with increasing network density, the gSPAWN algorithm allows sensors to broadcast a message whose size does not depend on the network size or density, making it more suitable for applications in wireless sensor networks. We show that the gSPAWN algorithm converges in mean and has mean-square stability under some technical sufficient conditions, and we describe an application of the gSPAWN algorithm to a network localization problem in non-line-of-sight environments. Numerical results suggest that gSPAWN converges much faster in general than the diffusion method, and has lower communication costs, with comparable root mean square errors

    Efficient Scheduling for SDMG CIOQ Switches

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    Combined input and output queuing (CIOQ) switches are being considered as high-performance switch architectures due to their ability to achieve 100% throughput and perfectly emulate output queuing (OQ) switch performance with a small speedup factor S. To realize a speedup factor S, a conventional CIOQ switch requires the switching fabric and memories to operate S times faster than the line rate. In this paper, we propose to use a CIOQ switch with space-division multiplexing expansion and grouped input/output ports (SDMG CIOQ switch for short) to realize speedup while only requiring the switching fabric and memories to operate at the line rate. The cell scheduling problem for the SDMG CIOQ switch is abstracted as a bipartite k-matching problem. Using fluid model techniques, we prove that any maximal size k-matching algorithm on an SDMG CIOQ switch with an expansion factor 2 can achieve 100% throughput assuming input line arrivals satisfy the strong law of large numbers (SLLN) and no input/output line is oversubscribed. We further propose an efficient and starvation-free maximal size k-matching scheduling algorithm, kFRR, for the SDMG CIOQ switch. Simulation results show that kFRR achieves 100% throughput for SDMG CIOQ switches with an expansion factor 2 under two SLLN traffic models, uniform traffic and polarized traffic, confirming our analysis

    Spinor Fields and Symmetries of the Spacetime

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    In the background of a stationary black hole, the "conserved current" of a particular spinor field always approaches the null Killing vector on the horizon. What's more, when the black hole is asymptotically flat and when the coordinate system is asymptotically static, then the same current also approaches the time Killing vector at the spatial infinity. We test these results against various black hole solutions and no exception is found. The spinor field only needs to satisfy a very general and simple constraint.Comment: 19 page

    Power system transient stability assessment based on quadratic approximation of stability region

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    This paper presents an approach to estimate the Critical Clearing Time (CCT) of the multi-machine power systems based on the quadratic surface which approximates the boundary of stability region relating to the controlling unstable equilibrium point. A decomposition method is developed to obtain the coefficients of the quadratic approximation surface. The CCT is determined by the crossing point of the quadratic surface and the continuous faulted trajectory. Simulations in IEEE 9-bus and New England system show the effectiveness of the proposed approach. © 2005 IEEE.published_or_final_versio

    Almost Sure Frequency Independence of the Dimension of the Spectrum of Sturmian Hamiltonians

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    We consider the spectrum of discrete Schr\"odinger operators with Sturmian potentials and show that for sufficiently large coupling, its Hausdorff dimension and its upper box counting dimension are the same for Lebesgue almost every value of the frequency.Comment: 12 pages, to appear in Commun. Math. Phy

    Nonlinear decentralized disturbance attenuation excitation control via new recursive design for multi-machine power systems

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    In this paper, a new nonlinear decentralized disturbance attenuation excitation control for multi-machine power systems is proposed based on recursive design without linearization treatment. The proposed controller improves system robustness to dynamic uncertainties and also attenuates bounded exogenous disturbances on the system in the sense of L 2-gain [1]. Computer test results on a 6-machine system show clearly that the proposed excitation control strategy can enhance transient stability of power systems more effectively than other excitation controllers.published_or_final_versio

    Scheduling Architectures for DiffServ Networks with Input Queuing Switches

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    ue to its simplicity and scalability, the differentiated services (DiffServ) model is expected to be widely deployed across wired and wireless networks. Though supporting DiffServ scheduling algorithms for output-queuing (OQ) switches have been widely studied, there are few DiffServ scheduling algorithms for input-queuing (IQ) switches in the literaure. In this paper, we propose two algorithms for scheduling DiffServ DiffServ networks with IQ switches: the dynamic DiffServ scheduling (DDS) algorithm and the hierarchical DiffServ scheduling (HDS) algorithm. The basic idea of DDS and HDS is to schedule EF and AF traffic According to Their minimum service rates with the reserved bandwidth and schedule AF and BE traffic fairly with the excess bandwidth. Both DDS and HDS find a maximal weight matching but in different ways. DDS employs a Centralized scheduling scheme. HDS features a hierarchical scheduling scheme That Consists of two levels of schedulers: the central scheduler and port schedulers. Using such a hierarchical scheme, the Implementation complexity and the amount of information needs to be Transmitted between input ports and the central scheduler for HDS are dramatically reduced Compared with DDS. Through simulations, we show That both DDS and HDS popup Guarantees a minimum bandwidth for EF and AF traffic, as well as fair bandwidth allocation for BE traffic. The delay and jitter performance of the DDS is close to That of PQWRR, an existing DiffServ supporting scheduling algorithm for OQ switches. The tradeoff of the simpler Implementation scheme of HDS is its slightly worse delay performance Compared with DDS
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