Impairment aware optimal diverse routing for survivable optical networks

In wavelength-routed optical networks, a lightpath connection can be provisioned only if a path, or a pair of paths in case of path protection is required, can be found which satisfies multiple constraints while simultaneously achieving optimal primary cost. The primary cost can be any metric set by network administrators, and the constraints concerned in optical networks include wavelength continuity constraint, accumulation effect of some transmission impairments in the optical domain, and SRLG-disjoint requirement in survivable networks. In this paper, the impact of these constraints on the optimal path calculation algorithms is studied. Three novel algorithms for solving this problem, which we call “Impairment Aware Optimal Path Pair” problem, are proposed, and their performance is evaluated through extensive simulations. This research has been supported by a National Natural Science Foundation of China (NSFC) grant (90604002, 60472008), and Program for New Century Excellent Talents in University grant (NCET-05-0807).     

WDM光网络中固定路由的优化算法

通过研究WDM光网络中固定路由策略的选取对网络性能的影响，提出了一种新的用于优化固定路由的算法-综合代价法。该算法综合考虑了链路负载和路由跳数这两个因素，以综合代价为策略进行路由优化。计算机仿真结果表明，针对不同的网络负载情况，综合代价法能够有效地降低网络的阻塞率，提高网络的性能。     

The use of artificial neural networks for optimal message routing

Artificial neural networks are being designed to exploit the unique computational power of the human brain. A brief review of neural networks and their applications in communications is presented. Following that, the neural network solutions to the routing problems are given. Simulation results and performance comparisons are discussed. A comparison between the neural approach and other popular routing algorithms such as Bellman-Ford's and Dijkstra's algorithms is then presented. The practical significance of this new routing algorithm is discussed and further research work is suggested     

数据分组网中自相似业务模型的研究进展

本文介绍了数据分组网络中业务模型的研究进展。数据分组网络中，传统的泊松或马尔科夫模型在描述网络业务的精确性方面有很大的不足，近年来发展的自相似（单元形）业务模型效果较好。最近，研究人员在实测网络业务数据的基础上提出的多分形模型，不但能很好地模拟网络业务的长相关性，还能表现其在小的时间尺度下的特性。本文简单介绍了单分形业务模型，然后对多分形业务模型进行了重点的阐述，对业务模型的研究进展做出了分析。     

Near optimal routing and capacity management for PWCE-based survivable WDM networks

Protected Working Capacity Envelope (PWCE) has been proposed to simplify resource management and traffic control for survivable WDM networks. In a PWCE-based network, part of the link capacity is reserved for accommodating working routes, and the remaining capacity is reserved for backup routes. The shortest path routing is applied in PWCE-based networks. An arrival call is accepted only when each link along the shortest path has a free working channel. Such a working path routing scheme greatly simplifies the call admission control process for dynamic traffic, and it is especially suitable for implementation in a distributed manner among network nodes. In this article, we investigate two protection strategies: Bundle Protection (BP) and Individual Protection (IDP). In BP, only one backup path can be used to protect a failure component, whereas multiple backup paths can be used in IDP. We formulate four mixed integer non-linear programming (MINLP) problems using BP and IDP strategies for single link and single node failure protection. Each model is designed to determine link metrics for shortest working path routing, working and backup channel assignments, and backup path planning. Our objective is to minimize call-blocking probability on the bottleneck link. Since these models are highly non-linear and non-convex, it is difficult to obtain exact global optimal solutions. We propose a Simulated Annealing-based Heuristic (SAH) algorithm to obtain near optimal solutions. This SAH adopts the concepts of simulated annealing as well as the bi-section technique to minimize call-blocking probabilities. To evaluate the performance, we made simulation comparisons between SAH and the unity link weight assignment scheme. The results indicate that SAH can greatly reduce call-blocking probabilities on benchmark and the randomly generated networks.     

Jointly optimal routing and scheduling in packet ratio networks

A multihop packet radio network is considered with a single traffic class and given end-to-end transmission requirements. A transmission schedule specifies at each time instant the set of links which are allowed to transmit. The purpose of a schedule is to prevent interference among transmissions from neighboring links. Given amounts of information are residing initially at a subset of the network nodes and must be delivered to a prespecified set of destination nodes. The transmission schedule that evacuates the network in minimum time is specified. The decomposition of the problem into a pure routing and a pure scheduling problem is crucial for the characterization of the optimal transmission schedule     

Near‐optimal online routing in opportunistic networks

In opportunistic networks, nodes communicate intermittently based on store‐carry‐forward paradigm while exploiting node mobility. The challenge is to determine the ideal nodes to deliver the messages since there is no end‐to‐end connectivity. The nodes might make this decision based on the data sensed from the network. This technique is not ideal in scenarios where the speed of changes in the network topology is greater than the speed at which the nodes can collect info on the network, which might, in turn, be restricted due to usage constraints and uncertainty of knowledge about future contacts. To tackle the problems raised by the non‐deterministic environments, in this paper, a stochastic optimization model and corresponding algorithm are developed to find the optimal routes by considering the short and long‐term impact of choices, ie, the next hop. Herein, we first propose a stochastic model to resolve the routing problem by identifying the shortest path. In the second step, we show that the optimal solution of the proposed model can be determined in polynomial time. An online algorithm is then proposed and analyzed. The algorithm is O( lognρ ) competitive considering the number of nodes and their associated energy. This model can take advantage of the unexpected meets to make the routing more elastic in a short time of contact and with less of a burden on the buffer. The simulation results, against the prominent algorithms, demonstrate significant improvement of the proposed approach in delivery and average delay ratio.     

A modified spectral conjugate gradient projection method for signal recovery

In this paper, signal recovery problems are first reformulated as a nonlinear monotone system of equations such that the modified spectral conjugate gradient projection method proposed by Wan et al. can be extended to solve the signal recovery problems. In view of the equations’ analytic properties, an improved projection-based derivative-free algorithm (IPBDF) is developed. Compared with the similar algorithms available in the literature, an advantage of IPBDF is that the search direction is always sufficiently descent as well as being close to the quasi-Newton direction, without requirement of computing the Jacobian matrix. Then, IPBDF is applied into solving a number of test problems for reconstruction of sparse signals and blurred images. Numerical results indicate that the proposed method either can recover signals in less CPU time or can reconstruct the images with higher quality than the other similar ones.     

Surviving double-link failures for near optimal heuristic routing in protected optical networks

The survivability for double-link failures in WDM optical network has been studied in recent years. In previous algorithm, to survive the double-link failures each connection request will be assigned to one primary path and two link-disjoint backup paths. However, the previous algorithm is the so-called simple algorithm which may lead to low resources utilization and high blocking probability. In this paper, we propose a new heuristic algorithm called routing with optimal solution (ROS) to protect the double-link failures. Differing from the previous algorithm, ROS can obtain near optimal solution by recomputing the primary path and two backup paths based on the rerouting policy for each connection request. Simulation results show that ROS can significantly outperform the previous algorithm.     

A location-based routing method for mobile ad hoc networks

Using location information to help routing is often proposed as a means to achieve scalability in large mobile ad hoc networks. However, location-based routing is difficult when there are holes in the network topology and nodes are mobile or frequently disconnected to save battery. Terminode routing, presented here, addresses these issues. It uses a combination of location-based routing (terminode remote routing, TRR), used when the destination is far, and link state-routing (terminode local routing, TLR), used when the destination is close. TRR uses anchored paths, a list of geographic points (not nodes) used as loose source routing information. Anchored paths are discovered and managed by sources, using one of two low overhead protocols: friend assisted path discovery and geographical map-based path discovery. Our simulation results show that terminode routing performs well in networks of various sizes. In smaller networks; the performance is comparable to MANET routing protocols. In larger networks that are not uniformly populated with nodes, terminode routing outperforms, existing location-based or MANET routing protocols.     

Network coding and competitive approach for gradient based routing in wireless sensor networks

Energy efficiency is a key design criterion for routing protocols in wireless sensor networks since sensor nodes are strongly constrained in terms of energy supply. Gradient-Based Routing (GBR) is a well known energy efficient routing protocol that is used in WSNs. However, there exist shortcomings in the GBR scheme such as: (1) sinks make use of flooding to broadcast interest messages which leads to a lot of duplication packets which are transmitted. This leads to the waste of a lot of energy in the network and (2) nodes deliver messages in a point to point manner. As a result, the potential of data retransmissions in the network is high due to the unstable network environment in WSNs. In this study, network coding and a competitive approach are proposed to solve the above two problems. Firstly, an energy efficient broadcast algorithm using network coding for GBR (GBR-NC) is proposed. This algorithm aims to reduce network traffic, and furthermore, reduce the energy consumption and prolong the lifetime of the network. Secondly, two competing algorithms (GBR-C and auto-adaptable GBR-C) are proposed for GBR. The basic idea of the proposed competing algorithms is to reduce the retransmission attempts and save the energy by considering two forward candidates. Simulation results show that the proposed schemes give better results when compared to the traditional GBR in terms of energy efficiency.     

Algorithm of conditional minimization of the goal function for optimal routing in information networks

Anew algorithm has been proposed for solving the optimal routing problem. This algorithm is based on applying the Kirchhoff laws to information networks and does not require the mandatory use of derivatives of the goal function making it quite convenient for distributed realizations. The algorithm convergence is substantiated by drawing an analogy between information and electric networks. On the basis of a case study of the network it was shown that its speed is tens of times as high as that of the flow deviation algorithm. It was shown that theoretical labor intensity of implementing this method is substantially less than that of the algorithms based on finding the shortest routes, since the cyclic part of this algorithm does not contain laborious logical operations.     

Energy and congestion aware routing based on hybrid gradient fields for wireless sensor networks

Wireless Networks - The principles of physics and system sciences are increasingly used in the field of network engineering to design network protocols. This work proposes an energy and congestion...     

An optimal design method for magnetic resonance imaging gradient waveforms

A method of using nonlinear constrained optimization to design gradient waveforms for magnetic resonance imaging is described. Formulation and solution of the waveform optimization problem are described and example waveforms are presented for a variety of design objectives and constraint sets. Most design objectives can be expressed as linear or quadratic functions of the discrete parameter set, and most constraint functions are linear. Thus, linear and quadratic programming techniques can be utilized to solve the optimization problem. Among the objectives considered are: minimize RMS current; minimize waveform slewing; minimize waveform moments to reduce motion induced dephasing; minimize echo time (TE) for given imaging and motion refocusing conditions; maximize the gradient amplitude during RF application and sampling and the area of the phase encoding waveform to maximize resolution; and minimize or maximize the gradient b factor or diffusion sensitivity. This optimal design procedure produces physically realizable waveforms which optimally achieve specific imaging and motion artifact reduction goals, and it is likely to reduce waveform design time by making it more scientifically (rather than heuristically) based.     

A simple method for optimal redundancy allocation for complex networks

In this paper a simple method for optimum redundancy allocation for complex networks is presented. A new heuristic criterion is introduced for solving the problem by decomposing the same in two phases. After finding all minimal path sets of the system in phase I, we choose a minimal path set having the highest value of the ‘sensitivity factor’. In phase II we add one component to the stage having the largest value of the selection factor amongst the stages of the selected minimal path set. This procedure is continued until no more redundant component can be added within the available resources. The proposed method is simple, easily computerizable, fast and capable of handling problems subject to any number of constraints. The method has been illustrated by examples and results are compared with the existing methods.     

双环网络并行最优寻径策略及宽直径的研究

将双环网络拓扑结构映射到平面直角坐标系,基于直角坐标系研究双环网络的并行最优寻径方法。首先研究坐标轴上节点及其等价节点的分布规律,建立等价节点分布模型,得出基于等价节点的并行最优寻径策略及双环网络宽直径求解方法。在双环网络最小路径图（MDD）的基础上拓展,提出并行路径图（PDD）的设计思路并予以仿真实现,基于PDD图,设计两点间2条内点不交的并行最短路径的快速求解方法。仿真实验表明,宽直径分布随步长的变化呈现一定波动性,相对于传统的寻径方式,并行最优寻径明显提高了网络传输效率。     

A solving method for singly routing traffic demand in telecommunication networks

The problem of assigning single paths to point to point demands in a network arises in the telecommunications industry. The well known atm technology involves such a problem when each demand must be assigned to a single virtual channel in an atm backbone network. This problem is referred to as the Bandwidth Packing Problem. For a given network and a set of point to point demands with related bandwidth requirement and profit, the problem consists in determining the most rewarding subset of demands for which all demands are single path routed according to the link capacity constraints. We propose a heuristic derived from an exact method to solve this problem. We use cutting planes to strengthen a path-based linear relaxation embedded in a Branch&Cut scheme. The results particularly depend on the ratio of the average edge capacity to the average bandwidth required by the demands. The method provides optimum or nearly optimum solutions for practical telecommunications problems within small computational time.     

A new fault-management method using congestion-avoidance routing for optical burst-switched networks

Optical burst switching (OBS) has been proposed as a promising technique to support high-bandwidth, bursty data traffic in the next-generation optical Internet. This study investigates a new fault-management framework for an OBS network. In an OBS network, burst-loss performance is a critical concern. In OBS, the data-burst transmission is delayed by an offset time (relative to its burst control packet (BCP), or header), and the burst follows its header without waiting for an acknowledgment for resource reservation. Thus, a burst may be lost at an intermediate node due to contention, which is generally resolved according to the local routing and bandwidth information. The routing table maintained in each OBS node is generally pre-computed and fixed to forward the data bursts. Such a static forwarding feature might have limited efficiency to resolve contentions. Moreover, a burst may be lost and the network may be congested when a network element (e.g., fiber link) fails. Therefore, for reliable burst transport, we develop dynamic routing approaches for preplanned congestion avoidance. Our goal is to proactively avoid congestion during the route-computation process, and our approach employs wavelength-channel utilization, traffic distribution, and link-distance information in the proposed objective functions for routing. Two update mechanisms for maintaining a dynamic routing table are presented to accommodate bursty data traffic. Based on our routing mechanisms, we also propose a new congestion-avoidance-and-protection (CAP) approach, which employs a primary route and a group of backup routes for each node pair against failures and congestion. The performance of the proposed protection strategy using congestion-avoidance routing is demonstrated to be promising through illustrative numerical examples.

Lattice networks: capacity limits, optimal routing, and queueing behavior

Lattice networks are widely used in regular settings like grid computing, distributed control, satellite constellations, and sensor networks. Thus, limits on capacity, optimal routing policies, and performance with finite buffers are key issues and are addressed in this paper. In particular, we study the routing algorithms that achieve the maximum rate per node for infinite and finite buffers in the nodes and different communication models, namely uniform communications, central data gathering and border data gathering. In the case of nodes with infinite buffers, we determine the capacity of the network and we characterize the set of optimal routing algorithms that achieve capacity. In the case of nodes with finite buffers, we approximate the queue network problem and obtain the distribution on the queue size at the nodes. This distribution allows us to study the effect of routing on the queue distribution and derive the algorithms that achieve the maximum rate.