H/sub /spl infin// mode reduction for two-dimensional discrete state-delayed systems

The problem of H_infin model reduction for two-dimensional (2-D) discrete systems with delay in state is considered. The mathematical model of 2-D systems is established on the basis of the well-known Fornasini-Marchesini local state-space. First, conditions are established to guarantee the asymptotic stability and a prescribed noise attenuation level in the H_infin sense for the underlying system. For a given stable system, attention is focused on the construction of a reduced-order model, which approximates the original system well in an H_infin norm sense. Sufficient conditions are proposed for the existence of admissible reduced-order solutions. Since these obtained conditions are not expressed as strict linear matrix inequalities (LMIs), the cone complementary linearisation method is exploited to cast them into sequential minimisation problems subject to LMI constraints, which can be readily solved using standard numerical software. These obtained results are further extended to more general cases whose system states contain multiple delays. Two numerical examples are provided to demonstrate the effectiveness of the proposed techniques     

Delay-Dependent H∞ Control and Filtering for Uncertain Markovian Jump Systems With Time-Varying Delays

This paper deals with the problems of delay-dependent robust H_infin control and filtering for Markovian jump linear systems with norm-bounded parameter uncertainties and time-varying delays. In terms of linear matrix inequalities, improved delay-dependent stochastic stability and bounded real lemma (BRL) for Markovian delay systems are obtained by introducing some slack matrix variables. The conservatism caused by either model transformation or bounding techniques is reduced. Based on the proposed BRL, sufficient conditions for the solvability of the robust H_infin control and H_infin filtering problems are proposed, respectively. Dynamic output feedback controllers and full-order filters, which guarantee the resulting closed-loop system and the error system, respectively, to be stochastically stable and satisfy a prescribed H_infin performance level for all delays no larger than a given upper bound, are constructed. Numerical examples are provided to demonstrate the reduced conservatism of the proposed results in this paper.     

Adaptive Synchronization of Complex Dynamical Networks with Time-Varying Delays

This paper addresses the problem of adaptive pinning synchronization of complex dynamical networks with nonlinear delayed intrinsic dynamics and time-varying delays. By introducing decentralized adaptive strategies to both the coupling strengths and the feedback gains, it is proved that the complex dynamical network can synchronize with the desired state for the bounded time-varying delays even when only one node is informed, without any global information of the underlying network. Finally, some numerical simulations are given to verify the main results and show the superiority of these self-designed adaptive strategies.     

Improved Delay-Dependent H∞ Filtering Design for Discrete-Time Polytopic Linear Delay Systems

This brief revisits the problem of delay-dependent robust H_infin filtering design for discrete-time polytopic linear systems with interval-like time-varying delay. Under the condition whether the unknown parameters can be measured online or not, a parameter-dependent or a parameter-independent filter is respectively developed which guarantees the asymptotic stability of the resulting filtering error system with robust H_infin performance gamma. It is shown that by using a new linearization technique incorporating a bounding technique, a unified framework can be developed such that the full-order and reduced-order, the parameter-dependent and parameter-independent filters can be obtained by solving a set of linear matrix inequalities. Finally, a numerical example is provided to illustrate the effectiveness and merits of the proposed approach.     

Local stability of REM algorithm with time-varying delays

We investigate the local stability in equilibrium for an Internet congestion control algorithm proposed by Low (see IEEE/ACM Transactions on Networking, vol.7, p.861-875,1999). The network consists of multisource and one-bottleneck link with heterogenous time-varying propagation delays. Linear matrix inequality (LMI) stability criteria is presented for discrete congestion control algorithm of TCP/REM dual model, which can be efficiently and easily solved by the LMI toolbox provided by Matlab software. An important feature is to acquire the maximum network delays to guarantee the stability of congestion control algorithm, i.e., the scale stability domain of REM algorithm.     

Dynamic power allocation and routing for time-varying wireless networks

We consider dynamic routing and power allocation for a wireless network with time-varying channels. The network consists of power constrained nodes that transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices (/spl lambda//sub ij/) that the system can stably support-where /spl lambda//sub ij/ represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed that stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an ad hoc wireless network, where channel variations are due to user mobility. Centralized and decentralized implementations are compared, and the stability region of the decentralized algorithm is shown to contain that of the mobile relay strategy developed by Grossglauser and Tse (2002).     

Variable Bit Rate Flow Routing in Wireless Sensor Networks

Since energy constraint is a fundamental issue for wireless sensor networks, network lifetime performance has become a key performance metric for such networks. In this paper, we consider a two-tier wireless sensor network and focus on the flow routing problem for the upper tier aggregation and forwarding nodes (AFNs). Specifically, we are interested in how to perform flow routing among the nodes when the bit rate from each source node is time-varying. We present an algorithm that can be used to construct a flow routing solution with the following properties: (1) If the average rate from each source node is known a priori, then flow routing solution obtained via such algorithm is optimal and offers provably maximum network lifetime performance; (2) If the average rate of each source node is unknown but is within a fraction (epsiv) of an estimated rate value, then network lifetime by the proposed flow routing solution is within 2epsiv/1-epsiv from the optimum. These results fill in an important gap in theoretical foundation for flow routing in energy-constrained sensor networks.     

一种基于TMN的集中式信令路由管理新方法

本文提出了一种基于ＴＭＮ的集中式路由管理新方法Ｃ－ＭＲＶＴ,并运用排队理论对Ｃ－ＭＲＶＴ和传统ＭＲＶＴ方法进行了性能分析比较,最后给出了该方法的实现方案和模拟结果。理论分析和模拟结果表明,Ｃ－ＭＲＶＴ是一种有前景的、技术可靠的信令网络由管理方法。     

考虑排队时延的系统保护通信网络路由选择算法

目前满足系统保护通信网络的路由算法是在综合时延和可靠性的要求下,计算一条快速且可靠传输的路径,而没有考虑到当电网发生故障或网络中通信量过大时,通信网络中许多节点的排队时延会极大地增加,忽略排队时延对路径传输总时延的影响会导致路径的错误选择,从而影响系统保护的实时性。针对此问题,提出了一种考虑排队时延的路由选择算法,用于计算信息传输总时延最小的最优路径,以提高系统保护通信的实时性。实验结果表明,通过本文提出的路由选择算法计算得到的路径在满足系统保护可靠性要求的基础上信息传输总时延最小。     

Multipath routing in mobile ad hoc network with probabilistic splitting of traffic

Multipath routing is a burning issue in mobile ad hoc network due to its various advantages over single path routing. Some of these advantages are load balancing, bandwidth aggregation, and fault tolerance. Multipath routing means multiple paths exist between source and destination pair. Many works discussed in section 2 addressed queuing delays, but none of them suggested queuing delay for multiple path deliveries of data in mobile ad hoc network context. In this paper, we have designed a mathematical model to compute delay and throughput for multipath. Our model follow the network of M/M/1 queues, and we have applied Burke’s theorem to calculate the queuing delay of the packet in mobile network scenario. This model can be used to estimate delay and throughput of an individual path. Further, through the analysis the best path for data delivery out of available multiple paths as well as the multipath path can be used simultaneously for data delivery to the destination. Simulation result shows that splitted traffic multiple paths outperform splitted traffic. Therefore, our model is useful for design and analysis of ad hoc network. The simulation work has been carried out in Qualnet simulator.     

Centralized and decentralized stochastic routing models in telecommunication networks

With the advent of non-hierarchical routing in circuit-switched telecommunication networks, on-line routing policies have been developed with the objective of optimizing some measure of gain or performance. These policies are decentralized. However, traditional planning models are centralized models. We present a decentralized routing model to be used in network planning. We compare it theoretically and empirically with a centralized multicommodity flow model previously presented. The two models are solved by the same type of algorithm, a convex simplex implementation, adapted differently according to the model. Comparative results between planning models reproducing the two policies are discussed.     

QoS aware traffic grooming and integrated routing on IP over WDM networks

In this article, we consider traffic grooming and integrated routing in IP over WDM networks. The challenges of this problem come from jointly considering traffic grooming, IP routing, and lightpath routing and wavelength assignment (RWA). Due to the high bandwidth of optical fiber, there exists a mismatch between the capacity needed by an IP flow and that provided by a single lightpath. Traffic grooming is therefore used to increase the network utilization by aggregating multiple IP flows in a single lightpath. However, traffic grooming incurs additional delays that might violate Quality-of-Service (QoS) requirements of IP users. In this work, the tradeoff between traffic grooming and IP QoS routing is well-formulated as a mixed integer and linear optimization problem, in which the revenue from successfully provisioning IP paths is to be maximized. Problem constraints include IP QoS, routing, optical RWA, and the WDM network capacity. We propose a novel Lagrangean relaxation (LGR) algorithm to perform constraint relaxation and derive a set of subproblems. The Lagrangean multipliers are used in the proposed algorithm to obtain a solution in consideration of grooming advantage and resource constraints simultaneously. Through numerical experiments and comparisons between the proposed algorithm and a two-phase approach, LGR outperforms the two-phase approach under all experimental cases. In particular, the improvement ratio becomes even more significant when the ratio of IP flow to the wavelength capacity is smaller.     

Dual H∞ Algorithms for Signal Processing— Application to Speech Enhancement

This paper deals with the joint signal and parameter estimation for linear state-space models. An efficient solution to this problem can be obtained by using a recursive instrumental variable technique based on two dual Kalman filters. In that case, the driving process and the observation noise in the state-space representation for each filter must be white with known variances. These conditions, however, are too strong to be always satisfied in real cases. To relax them, we propose a new approach based on two dual H_infin filters. Once a new observation of the disturbed signal is available, the first H_infin algorithm uses the latest estimated parameters to estimate the signal, while the second H_infin algorithm uses the estimated signal to update the parameters. In addition, as the H_infin filter behavior depends on the choice of various weights, we present a way to recursively tune them. This approach is then studied in the following cases: (1) consistent estimation of the AR parameters from noisy observations and (2) speech enhancement, where no a priori model of the additive noise is required for the proposed approach. In each case, a comparative study with existing methods is carried out to analyze the relevance of our solution.     

Distributed Simulation of Differential Algebraic Systems Using Optimal Sliding-Mode Control

In this paper, the optimal solution of differential algebraic equation (DAE) systems over a network of processors is investigated. A sliding-mode control (SMC) approach is used to enforce the algebraic constraints of the DAEs. Time delays associated with network communication give rise to a sliding-control problem with sensor time delays. A new approach is presented that decouples this problem into two independent problems. Using this property, a mixed H_infin optimization approach is applied to minimize errors. The results are applied to solve the problem of the optimal bandwidth allocation between the processors under the constraint of limited communication bandwidth. Experimental results for a distributed simulation application on a TDMA network demonstrate the validity of the approach     

一种基于多主体模糊知识交换的动态网络路由方法

路由是通信网络中重要的研究课题,但对于高度动态网络环境,现有的许多路由方法仍存在一些局限性。本文将多Agent(主体)迁移合作系统应用于解决动态网络路由问题,提出了基于模糊知识的多Agent合作模型和用于计算路由的基础合作算法,并讨论了影响系统的几个关键因素。通过对动态网络仿真的试验研究,分析了系统的性能开销特性和合作策略。研究结果表明,所提出理论模型和算法适合于解决动态网络的路由问题,并且能提高路由系统的响应性能。     

Multihop Virtual Topology Design in WDM Optical Networks for Self-Similar Traffic

In this paper, we consider the problem of designing virtual topologies for multihop optical WDM networks when the traffic is self-similar in nature. Studies over the last few years suggest that the network traffic is bursty and can be much better modeled using self similar process instead of Poisson process. We examine buffer sizes of a network and observe that, even with reasonably low buffer overflow probability, the maximum buffer size requirement for self-similar traffic can be very large. Therefore, a self-similar traffic model has an impact on the queuing delay which is usually much higher than that obtained with the Poisson model. We investigate the problem of constructing the virtual topology with these two types of traffic and solve it with two algorithmic approaches: Greedy (Heuristic) algorithm and Evolutionary algorithm. While the greedy algorithm performs a least-cost search on the total delay along paths for routing traffic in a multihop fashion, the evolutionary algorithm uses genetic methods to optimize the average delay in a network. We analyze and compare our proposed algorithms with an existing algorithm via different performance parameters. Interestingly, with both the proposed algorithms the difference in the queuing delays, caused by self-similar and Poisson traffic, results in different multihop virtual topologies.     

Network coding for multiple unicast sessions in multi-channel/interface wireless networks

Throughput limitation of wireless networks imposes many practical problems as a result of wireless media broadcast nature. The solutions of the problem are mainly categorized in two groups; the use of multiple orthogonal channels and network coding (NC). The networks with multiple orthogonal channels and possibly multiple interfaces can mitigate co-channel interference among nodes. However, efficient assignment of channels to the available network interfaces is a major problem for network designers. Existing heuristic and theoretical work unanimously focused on joint design of channel assignment with the conventional transport/IP/MAC architecture. Furthermore, NC has been a prominent approach to improve the throughput of unicast traffic in wireless multi-hop networks through opportunistic NC. In this paper we seek a collaboration scheme for NC in multi-channel/interface wireless networks, i.e., the integration of NC, routing and channel assignment problem. First, we extend the NC for multiple unicast sessions to involve both COPE-type and a new proposed scheme named as Star-NC. Then, we propose an analytical framework that jointly optimizes the problem of routing, channel assignment and NC. Our theoretical formulation via a linear programming provides a method for finding source–destination routes and utilizing the best choices of different NC schemes to maximize the aggregate throughput. Through this LP, we propose a novel channel assignment algorithm that is aware of both coding opportunities and co-channel interference. Finally, we evaluate our model for various networks, traffic models, routing and coding strategies over coding-oblivious routing.     

A Class of Decentralized Routing Algorithms Using Relaxation

An important problem in packet-switched communication networks is the optimal assignment of routes to the message packets. An optimal routing assignment is one which chooses network paths for the packets in a way that minimizes some cost function, typically average message delay. A class of optimal routing algorithms is described which utilize a type of iterative computation known as relaxation. Computation is decentralized in the sense that each node computes its routing strategy using only information supplied from adjacent nodes. Being iterative, the algorithms are inherently adaptive. The routing computation is based conceptually on an electrical network analog for the optimization problem. We show that a simple, convergent relaxation procedure can be used to "solve" the analog network, thereby yielding the optimal routing strategy. A simple example is presented to illustrate the method. In general, the computational load compares favorably with other (centralized) methods, although further work is needed to obtain quantitive comparisons in specific cases.     

Intersection-Based Routing Protocol for VANETs

Vehicular ad hoc network (VANET) is an emerging wireless communications technology that is capable of enhancing driving safety and velocity by exchanging real-time transportation information. In VANETs, the carry-and-forward strategy has been adopted to overcome uneven distribution of vehicles. If the next vehicle located is in transmission range, then the vehicle forwards the packets; if not, then it carries the packets until meeting. The carry mostly occurs on sparsely populated road segments, with long carry distances having long end-to-end packet delays. Similarly, the dense condition could have long delays, due to queuing delays. The proposed intersection-based routing protocol finds a minimum delay routing path in various vehicle densities. Moreover, vehicles reroute each packet according to real-time road conditions in each intersection, and the packet routing at the intersections is dependent on the moving direction of the next vehicle. Finally, the simulation results show that the proposed Intersection-Based Routing (IBR) protocol has less end-to-end delay compared to vehicle-assisted data delivery (VADD) and greedy traffic aware routing protocol (GyTAR) protcols.