Distributed control over structured and packet‐dropping networks

In this paper we consider distributed control of n dynamic agents to optimize an overall system performance metric. Due to limited communication resources, there exist structured interconnections among the agents and the interest is placed on synthesizing a suitably distributed control law to provide a given performance level. Based on a Youla–Kucera (Y–K) parameterization approach, the problem of designing a distributed controller to deliver given performance levels for different network topologies is shown to be convex in the Y–K parameter Q. Furthermore, if in addition to structured interconnections, packet drops exist in information transmission among the agents, we provide convex conditions to guarantee mean square (MS) stability and to optimize ℋ︁₂ system performance. The proposed method is also extended to deal with systems of triangular structure. Copyright © 2007 John Wiley & Sons, Ltd.     

基于误码率与中断概率约束的femtocell网络分布式功率控制

家庭基站(femtocell)网络可有效改善无线通信业务的室内覆盖性能,提高信道容量.然而,复杂的动态通信环境导致信道的不确定性,影响用户服务质量.基于此,研究双层femtocell网络在快衰落信道环境下基于误码率约束的功率控制问题;考虑信号传输的中断概率,以及服务质量指标–误码率等方面的要求,构造在此约束下的优化问题;最大化双层femtocell网络的净收益,使得网络系统的通信性能最优;通过对概率约束进行数学处理,将其转化为确定性形式,并提出分布式鲁棒优化算法对等价的确定性优化问题进行求解,从而获得最优功率分配策略.最后,通过仿真验证了所提出算法的收敛性和有效性.     

OTIS-MOT: an efficient interconnection network for parallel processing

Mesh of trees (MOT) is well known for its small diameter, high bisection width, simple decomposability and area universality. On the other hand, OTIS (Optical Transpose Interconnection System) provides an efficient optoelectronic model for massively parallel processing system. In this paper, we present OTIS-MOT as a competent candidate for a two-tier architecture that can take the advantages of both the OTIS and the MOT. We show that an n⁴_-n^{4}_{-} processor OTIS-MOT has diameter 8log n ^∗+1 (The base of the logarithm is assumed to be 2 throughout this paper.) and fault diameter 8log n+2 under single node failure. We establish other topological properties such as bisection width, multiple paths and the modularity. We show that many communication as well as application algorithms can run on this network in comparable time or even faster than other similar tree-based two-tier architectures. The communication algorithms including row/column-group broadcast and one-to-all broadcast are shown to require O(log n) time, multicast in O(n ²log n) time and the bit-reverse permutation in O(n) time. Many parallel algorithms for various problems such as finding polynomial zeros, sales forecasting, matrix-vector multiplication and the DFT computation are proposed to map in O(log n) time. Sorting and prefix computation are also shown to run in O(log n) time.     

Comments on the erratum to “Supply planning model for remanufacturing system in reverse logistics environment” [Comput. Ind. Eng. 51 (2006) 279–287]

To maximize the total cost of savings, a mixed-integer programming model for remanufacturing proposed by Kim et al. [Kim, K., Song, I., Kim, J., & Jeong, B. (2006). Supply planning model for remanufacturing system in reverse logistics environment. Computers & Industrial Engineering, 51, 279–287] was published in Computers & Industrial Engineering journal to decide optimally the quantity of parts to be processed at each remanufacturing facilities, the number of purchased parts from subcontractor. In this work, comments and suggestions are given to the published model of Kim, Song, Kim, and Jeong (2006). Comments like partial and complete disassembly, disassembly cost, optimum level of disassembly and finally, the modification of constraints are suggested in this work.     

Nonlinear L2-by-3 transform for PAPR reduction in OFDM systems

Orthogonal frequency division multiplexing (OFDM), the multicarrier modulation technique with high bandwidth efficiency and robustness against multipath fading, is used in several high-speed broadband communication systems including digital video broadcasting (DVB), digital audio broadcasting (DAB), asymmetric digital subscriber line (ADSL), wireless local area network (WLAN IEEE 802.11a,g), high performance radio local area network (HIPERLAN 2), and worldwide interoperability for microwave access (WiMAX IEEE 802.16). However, the transmit signal in OFDM system has a high peak-to-average power ratio (PAPR), one of the major drawbacks of multicarrier transmission, and therefore high dynamic range is required in both the digital to analog converter (DAC) and the power amplifier (PA) for proper operation. Otherwise, the nonlinearities of PA cause out-of-band distortion and increase in bit error rate (BER). Therefore, the reduction in PAPR in OFDM system is desirable in order to obtain power efficiency and increase BER performance. In this paper, a new parametric PAPR reduction technique, L₂-by-3 transform from sliding norm transform (SNT) family is proposed. Based on its parameter, a significant PAPR reduction is obtained. This paper presents the analysis of power saving and computational complexity of the proposed method L₂-by-3 and comparison to two other methods; selected mapping and partial transmit sequence.     

基于Stackelberg博弈的双层水下传感器网络功率分配算法

针对水下传感器协作通信网络中能量消耗严重的问题,为了平衡节点间的能量消耗,同时提高系统的信道容量,提出了基于节点剩余能量的分布式博弈功率分配算法。将用户节点和中继节点间的交易模型构建为双层的Stackelberg博弈,使剩余能量少的节点提供较少的功率进行转发服务,反之则提供较多的功率进行服务,从而平衡节点间的能量消耗。与未考虑剩余能量的算法相比,在有2、3和4个中继节点时,信道容量分别提升了9.4%、23.1%和16.7%。仿真结果表明,该算法不仅提高了系统总的信道容量,而且延长了水下传感器协作通信网络的生存时间。     

An improved smart card based password authentication scheme with provable security

Password authentication has been adopted as one of the most commonly used solutions in network environment to protect resources from unauthorized access. Recently, Lee–Kim–Yoo [S.W. Lee, H.S. Kim, K.Y. Yoo, Improvement of Chien et al.'s remote user authentication scheme using smart cards, Computer Standards & Interfaces 27 (2) (2005) 181–183] and Lee-Chiu [N.Y. Lee, Y.C. Chiu, Improved remote authentication scheme with smart card, Computer Standards & Interfaces 27 (2) (2005) 177–180] respectively proposed a smart card based password authentication scheme. We show that these two schemes are both subject to forgery attacks provided that the information stored in the smart card is disclosed by the adversary. We also propose an improved scheme with formal security proof.     

A network approach to the French system of legal codes—part I: analysis of a dense network

We explore one aspect of the structure of a codified legal system at the national level using a new type of representation to understand the strong or weak dependencies between the various fields of law. In Part I of this study, we analyze the graph associated with the network in which each French legal code is a vertex and an edge is produced between two vertices when a code cites another code at least one time. We show that this network distinguishes from many other real networks from a high density, giving it a particular structure that we call concentrated world and that differentiates a national legal system (as considered with a resolution at the code level) from small-world graphs identified in many social networks. Our analysis then shows that a few communities (groups of highly wired vertices) of codes covering large domains of regulation are structuring the whole system. Indeed we mainly find a central group of influent codes, a group of codes related to social issues and a group of codes dealing with territories and natural resources. The study of this codified legal system is also of interest in the field of the analysis of real networks. In particular we examine the impact of the high density on the structural characteristics of the graph and on the ways communities are searched for. Finally we provide an original visualization of this graph on an hemicyle-like plot, this representation being based on a statistical reduction of dissimilarity measures between vertices. In Part II (a following paper) we show how the consideration of the weights attributed to each edge in the network in proportion to the number of citations between two vertices (codes) allows deepening the analysis of the French legal system.     

两层与三层体系结构并存的应用系统设计

针对数据库应用系统中两层结构和三层结构的优势与不足,设计了两种体系结构并存的解决方案。利用DCOM实现隐藏逻辑代码和复杂的企业应用逻辑运算规则,部分客户用ADO直接与数据库服务器相连,以便处理大量信息时降低网络通信量,从而实现既有两层结构的数据处理快速的优势,又有三层分布式的不必维护大多数客户端的方便的应用模式。     

Tuple switching network—When slower may be better

This paper reports an application dependent network design for extreme scale high performance computing (HPC) applications. Traditional scalable network designs focus on fast point-to-point transmission of generic data packets. The proposed network focuses on the sustainability of high performance computing applications by statistical multiplexing of semantic data objects. For HPC applications using data-driven parallel processing, a tuple is a semantic object. We report the design and implementation of a tuple switching network for data parallel HPC applications in order to gain performance and reliability at the same time when adding computing and communication resources. We describe a sustainability model and a simple computational experiment to demonstrate extreme scale application’s sustainability with decreasing system mean time between failures (MTBF). Assuming three times slowdown of statistical multiplexing and 35% time loss per checkpoint, a two-tier tuple switching framework would produce sustained performance and energy savings for extreme scale HPC application using more than 1024 processors or less than 6 hour MTBF. Higher processor counts or higher checkpoint overheads accelerate the benefits.     

基于网络编码的传感网重编程协议能耗模型

在无线传感器网络中,当需要进行软件更新、修复软件Bug 时,重编程协议能够将新程序镜像分发到多跳网络中的全部节点.近来,基于网络编码的重编程协议被用于解决在高损环境下的有效代码分发问题,但对这些协议性能的分析仍有待深入.提出一种基于时间和网络拓扑的能耗分析模型,在模型中综合考虑了页面流水和节点通信距离对协议性能的影响.该模型分析结果与基于网络编码的重编程协议Rateless Deluge 的仿真结果达到了较好的一致性(平均单节点能耗相对误差在0.23%左右),验证了能耗分析模型的有效性.分析结果揭示了基于网络编码重编程过程的网络能耗与网络密度、网络大小和分发镜像页面大小的关系:网络能耗随着网络密度的减小呈上升趋势(能耗与网络密度经拟合呈二次函数关系);网络能耗与网络大小基本呈线性正相关关系(对于n×n 的网格型网络,n从3~10,随着n 的增大,网络能耗的平均增长率为50%),并且随着网络的增大,单节点能耗有所增加(平均增长率为6.9%);页面大小增加时,网络能耗呈下降趋势(平均下降率为11.2%).     

Event‐triggered dissipative synchronization for Markovian jump neural networks with general transition probabilities

In this paper, dissipative synchronization problem for the Markovian jump neural networks with time‐varying delay and general transition probabilities is investigated. An event‐triggered communication scheme is introduced to trigger the transmission only when the variation of the sampled vector exceeds a prescribed threshold condition. The transition probabilities of the Markovian jump delayed neural networks are allowed to be known, or uncertain, or unknown. By employing delay system approach, a new model of synchronization error system is proposed. Applying the Lyapunov‐Krasovskii functional and integral inequality combining with reciprocal convex technique, a delay‐dependent criterion is developed to guarantee the stochastic stability of the errors system and achieve strict (Q,S,R)?α dissipativity. The event‐triggered parameters can be derived by solving a set of linear matrix inequalities. A numerical example is presented to illustrate the effectiveness of the proposed design method.     

Efficient reliable communication over partially authenticated networks

Reliable communication between processors in a network is a basic requirement for executing any protocol. Dolev [7] and Dolev et al. [8] showed that reliable communication is possible if and only if the communication network is sufficiently connected. Beimel and Franklin [1] showed that the connectivity requirement can be relaxed if some pairs of processors share authentication keys. That is, costly communication channels can be replaced by authentication keys. In this work, we continue this line of research. We consider the scenario where there is a specific sender and a specific receiver in a synchronous network. In this case, the protocol of [1] has n^O(n) rounds even if there is a single Byzantine processor. We present a more efficient protocol with round complexity of (n/t)^O(t), where n is the number of processors in the network and t is an upper bound on the number of Byzantine processors in the network. Specifically, our protocol is polynomial when the number of Byzantine processors is O(1), and for every t its round complexity is bounded by 2^O(n). The same improvements hold for reliable and private communication. The improved protocol is obtained by analyzing the properties of a "communication and authentication graph" that characterizes reliable communication. Received: 13 January 2004, Accepted: 22 September 2004, Published online: 13 January 2005 A preliminary version of this paper appeared in [2].     

一种基于复数域网络编码的双层卫星通信系统

针对卫星通信网络吞吐量不足、可靠性不高的问题,提出一种基于复数域网络编码(Complex Field Network Coding,CFNC)的卫星通信方案。该方案在信号发送前对源信息作预编码处理,即在复数域上选取一个大小合适的参数化空时码与源信号相乘,编码后的信号与源信号在复数域上有着一一映射关系。对该方案的吞吐量和成对差错概率(Pairwise Error Probability,PEP)做了详尽的理论分析,结果表明,采用该编码方案的卫星通信系统在终端发射功率不变的情况下,吞吐量比路由模式提高了100%以上,比传统的CFNC方式至少可提高75%。该方案还可以扩展至更多的地面源节点,从而支持多用户网络通信。最后,仿真实验表明,在较高的信噪比下,PEP仿真值逼近于渐近值,验证了理论分析的正确性。     

Quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems

This paper presents a novel quadratic optimal neural fuzzy control for synchronization of uncertain chaotic systems via H^∞ approach. In the proposed algorithm, a self-constructing neural fuzzy network (SCNFN) is developed with both structure and parameter learning phases, so that the number of fuzzy rules and network parameters can be adaptively determined. Based on the SCNFN, an uncertainty observer is first introduced to watch compound system uncertainties. Subsequently, an optimal NFN-based controller is designed to overcome the effects of unstructured uncertainty and approximation error by integrating the NFN identifier, linear optimal control and H^∞ approach as a whole. The adaptive tuning laws of network parameters are derived in the sense of quadratic stability technique and Lyapunov synthesis approach to ensure the network convergence and H^∞ synchronization performance. The merits of the proposed control scheme are not only that the conservative estimation of NFN approximation error bound is avoided but also that a suitable-sized neural structure is found to sufficiently approximate the system uncertainties. Simulation results are provided to verify the effectiveness and robustness of the proposed control method.     

A two-tier control architecture for nonlinear process systems with continuous/asynchronous feedback

In this work, we introduce a two-tier control architecture for nonlinear process systems with both continuous and asynchronous sensing and actuation. This class of systems arises naturally in the context of process control systems based on hybrid communication networks (i.e. point-to-point wired links integrated with networked wired or wireless communication) and utilising multiple heterogeneous measurements (e.g. temperature and concentration). Assuming that there exists a lower-tier control system which relies on point-to-point communication and continuous measurements to stabilise the closed-loop system, we propose to use Lyapunov-based model predictive control to design an upper-tier networked control system to profit from both the continuous and the asynchronous measurements as well as from additional networked control actuators. The proposed two-tier control system architecture preserves the stability properties of the lower-tier controller while improving the closed-loop performance. The theoretical results are demonstrated using two different chemical process examples.     

Interactive Investigation of Traffic Congestion on Fat‐Tree Networks Using TreeScope

Parallel simulation codes often suffer from performance bottlenecks due to network congestion, leaving millions of dollars of investments underutilized. Given a network topology, it is critical to understand how different applications, job placements, routing schemes, etc., are affected by and contribute to network congestion, especially for large and complex networks. Understanding and optimizing communication on large‐scale networks is an active area of research. Domain experts often use exploratory tools to develop both intuitive and formal metrics for network health and performance. This paper presents Tree Scope , an interactive, web‐based visualization tool for exploring network traffic on large‐scale fat‐tree networks. Tree Scope encodes the network topology using a tailored matrix‐based representation and provides detailed visualization of all traffic in the network. We report on the design process of Tree Scope , which has been received positively by network researchers as well as system administrators. Through case studies of real and simulated data, we demonstrate how Tree Scope 's visual design and interactive support for complex queries on network traffic can provide experts with new insights into the occurrences and causes of congestion in the network.     

Adaptive recurrent neural network control using a structure adaptation algorithm

This paper proposes an adaptive recurrent neural network control (ARNNC) system with structure adaptation algorithm for the uncertain nonlinear systems. The developed ARNNC system is composed of a neural controller and a robust controller. The neural controller which uses a self-structuring recurrent neural network (SRNN) is the principal controller, and the robust controller is designed to achieve L ² tracking performance with desired attenuation level. The SRNN approximator is used to online estimate an ideal tracking controller with the online structuring and parameter learning algorithms. The structure learning possesses the ability of both adding and pruning hidden neurons, and the parameter learning adjusts the interconnection weights of neural network to achieve favorable approximation performance. And, by the L ² control design technique, the worst effect of approximation error on the tracking error can be attenuated to be less or equal to a specified level. Finally, the proposed ARNNC system with structure adaptation algorithm is applied to control two nonlinear dynamic systems. Simulation results prove that the proposed ARNNC system with structure adaptation algorithm can achieve favorable tracking performance even unknown the control system dynamics function.     

Robust distributed H∞ filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

In this paper, the problem of robust distributed H_∞ filtering is investigated for state‐delayed discrete‐time linear systems over a sensor network with multiple fading measurements, random time‐varying communication delays, and norm‐bounded uncertainties in all matrices of the system. The diagonal matrices, whose elements are individual independent random variables, are utilized to describe the multiple fading measurements. Furthermore, the Bernoulli‐distributed white sequences are introduced to model the random occurrence of time‐varying communication delays. In the proposed filtering approach, the stability of the estimation error system is first shown by the Lyapunov stability theory and the H_∞ performance is then achieved using a linear matrix inequality method. Finally, two numerical examples are given to show the effectiveness and performance of the proposed approach.