Theoretical Limits for Time Delay Based Location Estimation in Cooperative Relay Networks

Node localization in wireless networks is crucial for supporting advanced location-based services and improving the performance of network algorithms such as routing schemes. In this paper, we study the fundamental limits for time delay based location estimation in cooperative relay networks. The theoretical limits are investigated by obtaining Cramer–Rao Lower Bound (CRLB) expressions for the unknown source location under different relaying strategies when the location of the destination is known and unknown. More specifically, the effects of amplify-and-forward and decode-and-forward relaying strategies on the location estimation accuracy are studied. Furthermore, the CRLB expressions are derived for the cases where the location of only source as well as both source and destination nodes are unknown considering the relays as reference nodes. In addition, the effects of the node topology on the location estimation accuracy of the source node are investigated. The results reveal that the relaying strategy at relay nodes, the number of relays, and the node topology can have significant impacts on the location accuracy of the source node. Additionally, knowing the location of the destination node is crucial for achieving accurate source localization in cooperative relay networks.     

A comprehensive DCF performance analysis in noisy industrial wireless networks

The use of wireless technology in industrial networks is becoming more popular because of its flexibility, reduction of cable cost, and deployment time. Providing an accurate model to study the most important parameters of these networks, the timeliness and reliability, is essential in assessing the network metrics and choosing proper protocol settings. The Institute of Electrical and Electronics Engineers (IEEE) 802.11 is a common and established wireless technology, and several analytical models have been proposed to assess its performance; however, most of them are accurate only for a limited network situation, especially data networks that have large packet payloads and are used at high signal to noise ratios, and cannot be applied to study the performance of industrial networks that have short packet lengths and are used in harsh and noisy environments. In this paper, a novel three‐dimensional discrete‐time Markov chain model has been proposed for the IEEE 802.11‐based industrial wireless networks using the distributed coordination function as the medium access control mechanism in the worst‐case saturated traffic. It considers both causes of the backoff freezing: busy channel and the successive interframe space waiting time. In this way, it provides a much more accurate estimation of the channel access and error probabilities, resulting in a more accurate network parameter calculation. Also, based on the proposed model, a comprehensive packet delay analysis, including average, jitter, and cumulative distribution function, has been provided for the near 100% reliable industrial scenario and error‐prone channel condition, which in comparison with similar pieces of work provides much more accurate results. Copyright © 2014 John Wiley & Sons, Ltd.     

A multilevel parasitic interconnect capacitance modeling andextraction for reliable VLSI on-chip clock delay evaluation

This paper describes fringing and coupling interconnect capacitance models which include the nonlinear second-order effects of field interactions among multilevel parasitic interconnects for accurate circuit simulations. They are fitted well with numerical solutions by using a Poisson equation solver. A reliable parasitic distributed resistance-inductance-capacitance (RLC) extraction method is identified by using the solver with the bounded local three-dimensional (3-D) numerical analysis to reduce excessive central processing unit (CPU) time compared to full 3-D numerical simulation. We investigate the impact of input slew variations on the traversal clock delay within the slow ramp region of the driver gate as well as in the extracted parasitic interconnect networks. Input slew is found to be a dominant factor affecting clock delay sensitivity. In addition, we use indirect on-chip electron beam probing to confirm that the simulated clock delays are in reasonable agreement with the measured delays     

Analytical modeling methodology for ultrawideband low noise amplifiers with generalized filter-based impedance matching

In this paper, we present a modeling methodology for fully integrated inductively degenerated cascode ultrawideband low noise amplifiers (LNA) with generalized filter-based impedance matching networks. Our accurate analytical models capture the impact of device and passive component parasitics and transistor short channel effects to generate accurate designs. Utilizing our methodology, we are able to accurately generate an ultrawideband LNA in the 3.1–10.6 GHz frequency band using third and fifth order Chebyshev filters as input impedance matching networks. The speed and accuracy of the proposed analytical model will facilitate rapid design space exploration for ultrawideband LNAs.     

Energy consumption in RC tree circuits

In this paper, resistance-capacitance (RC) tree networks are modeled in terms of their energy consumption associated with an input transition. This work significantly extends the results that the same authors previously obtained in the specific case of ladder networks with only ramp signals. The proposed approach to model the energy consumption is based on a single-pole approximation, in which an equivalent time constant is analytically derived from an exact analysis for very slow and very fast input transitions. The model is then extended to arbitrary values of the input rise time by exploiting some intrinsic properties of RC tree networks. The approach is completely analytical and leads to closed-form results. Analytical results are explicitly derived for different inputs, such as the ramp and the exponential waveforms which are usually encountered in current VLSI circuits, as well as the saturated sine input. Due to its simplicity, the proposed energy expression is suitable for pencil-and-paper evaluation and allows for an intuitive understanding of the network dissipation. The energy expression proposed is shown to be accurate enough for modeling purposes through comparison with SPICE simulations.     

Using signal processing techniques to model worm propagation over wireless sensor networks

This paper describes how a topologically aware worm propagation model (TWPM) for wireless sensor networks is formulated and derived. The paper defines worm propagation characteristics that are specific to sensor networks. It also parameterize the effects of physical channel conditions, medium access control (MAC) layer contention, network layer routing, and transport layer protocol on worm propagation in sensor networks. The basic model formulation results in a partial differential equation, which is solved in the frequency domain to yield a closed-form solution for the TWPM. It is shown that in the spatial domain, the TWPM spread function is low-pass filtered by a two-dimensional isotropic Gaussian filter, thereby providing an intuitive feel for the dependence of the model on its underlying parameters. Simulation results demonstrate that the TWPM provides an effective and accurate worm propagation model for sensor networks     

Fast blocking probability evaluation of end-to-end optical burst switching networks with non-uniform ON–OFF input traffic model

A novel, accurate, numerically stable and fast mathematical method for network-wide blocking probability evaluation of end-to-end optical burst switching (OBS) networks with heterogeneous link capacity under non-uniform traffic is proposed. Unlike most of previous works, which have used the Poisson model for the burst traffic, this paper considers a non-uniform ON–OFF model being a more realistic choice for OBS networks. Compared with simulation, the method was proved to be very accurate and much faster (up to four orders of magnitude faster than simulation in the studied cases). These features make the proposed method very useful for network analysis, especially for large size networks where simulation time can be prohibitively high.     

Passive parameterized time-domain macromodels for high-speed transmission-line networks

There is a significant need for efficient and accurate macromodels of components during the design of microwave circuits. Increased integration levels in microwave devices and higher signal speeds have produced the need to include effects previously neglected during circuit simulations. Accurate prediction of these effects involve solution of large systems of equations, the direct simulation of which is prohibitively CPU expensive. In this paper, an algorithm is proposed to form passive parametrized macromodels of large linear networks that match the characteristics of the original network in time, as well as other design parameters of the circuit. A novel feature of the algorithm is the ability to incorporate a set of design parameters within the reduced model. The size of the reduced models obtained using the proposed algorithm were less than 5% when compared to the original circuit. A speedup of an order of magnitude was observed for typical high-speed transmission-line networks. The algorithm is general and can be applied to other disciplines such as thermal analysis.     

基于NTP的网络中心战时间同步技术研究

NTP协议用在Internet中使相互通信的计算机保持精确的时间同步,对于电子商务在内的许多网络应用有着重要价值。本文简述了NTP协议的定义、工作原理、工作模式、网络结构和处理流程,重点论述了其在网络中心战时间同步中的应用及存在的问题,这对保证网络中心战中信息和数据的时间一致性具有十分重要的意义。     

Global asymptotic and robust stability of recurrent neural networks with time delays

In this paper, two related problems, global asymptotic stability (GAS) and global robust stability (GRS) of neural networks with time delays, are studied. First, GAS of delayed neural networks is discussed based on Lyapunov method and linear matrix inequality. New criteria are given to ascertain the GAS of delayed neural networks. In the designs and applications of neural networks, it is necessary to consider the deviation effects of bounded perturbations of network parameters. In this case, a delayed neural network must be formulated as a interval neural network model. Several sufficient conditions are derived for the existence, uniqueness, and GRS of equilibria for interval neural networks with time delays by use of a new Lyapunov function and matrix inequality. These results are less restrictive than those given in the earlier references.     

All-optical networks with sparse wavelength conversion

Unlike broadcast-and-select networks, wavelength-routing networks offer the advantages of wavelength reuse and scalability and are thus suitable for wide-area networks (WANs) We study the effects of topological connectivity and wavelength conversion in circuit-switched all-optical wavelength-routing networks. A blocking analysis of such networks is given. We first propose an analytical framework for accurate analysis of networks with arbitrary topology. We then introduce a model for networks with a variable number of converters and analyze the effect of wavelength converter density on the blocking probability. This framework is applied to three regular network topologies that have varying levels of connectivity: the ring, the mesh-torus, and the hypercube. The results show that either a relatively small number of converters is sufficient for a certain level of performance or that conversion does not offer a significant advantage. The benefits of conversion are largely dependent on the network load, the number of available wavelengths, and the connectivity of the network. Finally, the tradeoff between physical connectivity, wavelength conversion, and the number of available wavelengths is studied through networks with random topologies     

Bitcoin's dynamic peer‐to‐peer topology

Topology discovery is a prerequisite when investigating the network properties; with the enormous number of Bitcoin users and performance issues, it becomes critical to analyse the network in a fashion that makes it possible to detect all Bitcoin's nodes and understand their behaviour. In massive, dynamic, and distributed peer‐to‐peer (P2P) networks like Bitcoin, where thousands of updates occur per second, it is hard to obtain an accurate topology representing the structure of the network as a graph with nodes and links by using the traditional local measurement approaches based on batches, offline data, or on the discovery of the topology around a small set of nodes and then combine them to discover an approximate network topology. All of which present some limitation when applying them on blockchain‐based networks. In this paper, we propose a topology discovery system that performs a real‐time data collection and analysis for Bitcoin P2P links, which assembles incoming nodes information for deeper graph analysis processing. The topology discovery system allows us to gain knowledge on the Bitcoin network size, the network stability in terms of reachable, churn, and well‐connected nodes, as well as some data regarding the effects of some countries' Internet infrastructure on Bitcoin traffic.     

Tight bounds for the tail of the packet waiting time distribution in buffered networks

In this paper we consider the end to end delay through a series of queues in which the service time is fixed and equal to the transmission time of constant length data packets at constant bitrate, for example real time delay sensitive traffic in IP or ATM networks. In these cases, algorithms are required either for on‐line admission control or for planning and provisioning of service partitions within such networks. Here we develop concise, accurate and easy to use solutions for the end to end delay through this series of queues, and provide numerical results quantifying the high degree of accuracy obtained. Additionally we compare against a Chernoff Bound approach, showing that our solutions are more accurate. Copyright © 2001 John Wiley & Sons, Ltd.     

On the transmission opportunity and TCP throughput in cognitive radio networks

The characteristics of cognitive radio networks have huge impacts on the end‐to‐end performance of the transmission control protocol (TCP) for secondary users. Thus, the existing TCP throughput expression, widely used in wired and wireless networks, is no longer suitable for cognitive radio networks. In this paper, we derive the transmission opportunity of secondary users, taking into account the dynamics of spectrum availability, the overhead and errors of spectrum sensing, as well as the interaction between TCP and lower layers. The amount of transmission opportunity is expressed in terms of effective data transmission time. On the basis of the analysis of the transmission opportunity, an expression of an effective TCP throughput is then derived. To evaluate this effective TCP throughput expression, two cross‐layer optimization problems are formulated as application examples to maximize the transport layer effective throughput and energy utility, respectively. Simulation results show that our analysis on transmission opportunity is accurate, and the derived effective TCP throughput expression is more precise than existing ones. Copyright © 2012 John Wiley & Sons, Ltd.     

基于GAN的ISAR图像语义分割方法

逆合成孔径雷达（ISAR）成像技术能够对空间目标进行远距离成像,刻画目标的外形、结构和尺寸等信息。ISAR图像语义分割能够获取目标的感兴趣区域,是ISAR图像解译的重要技术支撑,具有非常重要的研究价值。由于ISAR图像表征性较差,图像中散射点的不连续和强散射点存在的旁瓣效应使得人工精准标注十分困难,基于交叉熵损失的传统深度学习语义分割方法在语义标注不精准情况下无法保证分割性能的稳健。针对这一问题,提出了一种基于生成对抗网络（GAN）的ISAR图像语义分割方法,采用对抗学习思想学习ISAR图像分布到其语义分割图像分布的映射关系,同时通过构建分割图像的局部信息和全局信息来保证语义分割的精度。基于仿真卫星目标ISAR图像数据集的实验结果证明,本文方法能够取得较好的语义分割结果,且在语义标注不够精准的情况下模型更稳健。     

Using enhanced-TDOA measurement for indoor positioning

In the field of ad hoc networks, maintaining connectivity and performing efficient energy communication between several mobile stations (MS), involves the use of optimized geo localization based routing algorithms. With multipath contribution, indoor location based on a direct time difference of arrival (TDOA) measurement can dramatically increase its budget error and asks for innovative solutions allowing accurate time-of-flight measurement. A natural way of exploiting multiband ultrawide-band (UWB) technology, a simple input and multiple output (SIMO) approach can lead to the measurement of an enhanced TDOA (E-TDOA) measurement for accurate positioning.     

A cognitive model‐based approach for autonomic fault management in OpenFlow networks

Autonomic network management is an approach to the management of complex networks and services that incorporates the detection, diagnosis and reconfiguration, as well as optimization, of their performance. A control loop is fundamental as it facilitates the capture of the current state of the networks and the reconfiguration of network elements without human intervention. For new networking architectures such as software‐defined networking and OpenFlow networks, in which the control plane is moved onto a centralized controller, an efficient control loop and decision making are more crucial. In this paper, we propose a cognitive control loop based on a cognitive model for efficient problem resolving and accurate decision making. In contrast to existing control loops, the proposed control loop provides reactive, deliberative and reflective loops for managing systems based on analysis of current status. In order to validate the proposed control loop, we applied it to fault management in OpenFlow networks and found that the protection mechanism provides fast recovery from single failures in OpenFlow networks, but it cannot cover multiple‐failure cases. We therefore also propose a fast flow setup (FFS) algorithm for our control loop to manage multiple‐failure scenarios. The proposed control loop adaptively uses protection and FFS based on analysis of failure situations. We evaluate the proposed control loop and the FFS algorithm by conducting failure recovery experiments and comparing its recovery time to those of existing methods. Copyright © 2013 John Wiley & Sons, Ltd.     

Secure communications in local multipoint distribution service (LMDS) networks

The transmission of confidential information over LMDS networks is investigated in the present paper from an information-theoretic standpoint. The major factor impairing the link performance at these networks is rain attenuation, a physical phenomenon exhibiting both spatial and temporal variation. Based on an accurate channel modeling, analytical expressions of the probability of non-zero secrecy capacity and the outage probability for this type of networks are provided, giving for the first time an information-theoretic approach of the problem of secure transmission for LMDS networks. Useful conclusions are drawn through extended numerical results suggesting the increase of operational frequency and the use of more directional antennas to improve security in transmission of confidential messages for this type of networks.     

超大规模集成电路中互连结构的逻辑模型

本文首次提出一种新观点，超大规模集成电路中互连结构的等效模型应具有层次性，对于底层的电路设计，应将互加看作一种具有分布参数的多端口网络，而对于高层次的模块设计，则应将互连看作一种逻辑元件，基于这种观点，本文提出了一种表格型的逻辑模型，它可以将互连产生的三种主要负效应：串扰、延迟和信号变形人武部考虑在内。     

A new model for the performance evaluation of synchronous circuitswitched multistage interconnection networks

Patel (1981) proposed a probabilistic approach to analyze the performance of synchronous multistage interconnection networks (MINs) based on a uniform reference model and the assumption of independent requests. Patel's model and analytical results have been widely adopted by numerous researchers as a basis to investigate various aspects of MINs. We study in detail the effects of the independence assumption on the accuracy of system performance and point out the factors which cause an inaccuracy. A new queueing model is then proposed and is shown to be very accurate. Since only six states are needed, independent of the size of MINs, this new model is very efficient computationally