移动自组网络N次空间重用的离散时间马氏链模型

移动自组网络(简称MANET)目前已经成为4G中的重要研究课题.本文在一个典型的随选型路由协议即动态源路由(DSR)协议的基础上,通过对信号强度进行分级来描述节点之间的相对距离,同时利用定向天线技术,建立了移动自组网络有空间重用的离散时间马氏链模型.通过计算平稳分布,进一步分析了节点相邻的概率和节点的平均邻居数两个基本的网络参数.并以定向天线发送信号的特性为基础,给出了一个具体实例,分析相应的参数.这对路由协议的评价和性能分析具有理论上的指导意义.     

基于模糊信息的多QoS约束组播路由算法研究

首次将模糊集理论应用到组播路由算法中，定义了各个QoS参数的隶属度和理想点，建立了计算各个QoS参数到理想点距离的模型和方法，将多QoS约束简化为单距离约束，设计和实现了MQMRFI算法，分析了该算法的时间复杂度和空间复杂度，仿真结果证明在CPU执行时间上优于传统的QoS组播路由算法。     

移位交换网的最优路由算法

移位交换网是重要的互联网络之一 ,在并行计算中有着广泛应用 .然而 ,它缺少任意点对间的最短路由算法 .已有的路由算法都不能保证其任意节点对间都是最短路由 .文中给出了一个最短路由算法 ,也是最优路由算法 ,它使得从源节点到目的节点的任何信息都是沿最短路由传输 .同时 ,我们还得到了任意节点对间的距离公式     

求解通信网节点间全部路由的逻辑代数化算法

经典的D IJKSTRA和BELLM AN-F LOYD通信网络路由算法,只能根据特定网络参数得到最佳路由,却无法获得网络存在的全部可用路由,而通信网理论研究及网络管理等方面,往往需要获得节点之间的全部可用路由.研究出一种路由新算法,遵循逻辑代数运算规则、采用关联矩阵中行与行之间整合与删除方式计算,N个节点的网络只需N-1次整合及删除运算,就能得到源节点到任意节点两点之间全部路由结果.详细论证了算法的正确性与合理性,简介了算法的并行运算可行性及与经典路由算法的兼容性等问题.通过算例详细说明算法的计算过程,并验证其正确性.     

m-aryn-cube网络的最优路由

基于可选邻接点的概念,在m-ary n-cube网络中提出一种新的最优寻径算法.这种算法始终在当前结点的可选邻接点中选取最空闲邻接点作为下一个信息传输点.该算法使得从源结点到达目的结点路由是最短路由也是最快速路由,而且在多项式时间内可以完成.     

立方体网络路由选择算法

本文利用图论理论 ,基于路由选择能力的概念 ,建立了一个有效的路由选择算法 ,该算法可以在含有节点故障和边故障的容错超立方体上使用 ,且具有较强的容错性 .     

基于冰情检测环境的无线传感器网络路由协议研究

结合冰凌测报无线传感器网络中传感器节点能量受限、节点随着冰凌的产生与流动会出现在河道断面局部观测区域的冰凌测报无线传感器网络拓扑结构不断变化这一特性,提出了对贪婪周边无状态路由协议GPSR的改进策略GFSRI(GPSR-Improved),改进算法中采用图论模型,借助网络模拟器NS2(Network Simulator 2),对GPSR算法以及改进的路由策略GPSRI进行了模拟仿真实验,对路由算法中涉及到的关键参数的相关实验数据进行了处理分析.模拟仿真实验及评估结果表明,GPSRI在数据包转发的路由跳数、源和目的节点间端到端的传输时延方面与GPSR相比有较大的性能改进.     

一类网络速率控制和路由联合算法的稳定性

近年来,动态多路径路由下网络速率控制的研究受到广泛关注.本文提出了一个新的速率控制和多路径路由联合的算法,该算法的特点是具有唯一的平衡点.利用传统的Lyapunov方法,我们证明算法在没有传播时延情形下的全局稳定性.而且,更为重要的是,即使考虑传播时延,在一定的条件下,该算法是局部稳定的.在平衡点处,每条路由上的速率非零.这一事实不但去掉了Kelly F P,Voice T(2005)结果中内部平衡点的假设条件,而且也可以理解为一种探测机制.我们通过仿真证实了算法的正确性,同时仿真结果也表明局部稳定性的吸引域可以很大,甚至是全局稳定的.     

考虑传输容量的通信网端到端可靠性指标算法

归一化传输容量加权通信网端到端可靠性指标,非常适合评价现代高速宽带通信网络.然而计算全过程易于在计算机上编程实现的算法尚未见到.研究出一整套可靠性指标的计算方法.由于,从路由计算、不交化网络状态集及其对应容量的求取,到最后获得可靠性指标结果等各个环节,均实现了代数化或逻辑代数化运算,因此,整套算法易于编写计算机程序.详细介绍了算法各环节的计算规则与步骤,并对正确性与合理性进行了论证.通过举例详细说明算法的计算过程,并检验算法的正确性.     

随机结构系统基于可靠性的优化设计

提出了以梁板（薄板）为基体的随机结构系统（即结构元件的面积、长度、弹性模量和强度等均为随机变量）在随机载荷作用下,基于可靠性的优化设计方法．给出了随机结构系统安全余量和系统可靠性指标的敏度表达式;给出最佳矢量型算法．首先是用改进的一次二阶矩和随机有限元法求出安全余量的可靠性指标的表达式,然后用概率网络估算(PNET)法求出系统失效概率的公式,对该式两边求导得出了系统可靠性指标的敏度表达式,进而用最佳矢量型算法进行优化设计．在优化迭代过程中,采用梯度步和最佳矢量步相结合的方法进行计算．最后给出了一个算例,说明该方法计算效率高,收敛稳定,适合工程应用．     

ATM Routing Algorithms for Multimedia Traffic in Private ATM Networks

The goal of this paper is to recommend a good Private Network-to-Network Interface (PNNI) routing algorithm for private ATM networks. A good routing algorithm has to work well with multimedia traffic with several quality of service (QoS) requirements (such as cell loss ratio, cell delay and its variation etc.) in different networks under various traffic conditions. The multiplicity of QoS requirements makes the routing problem NP-complete, so our approach to the problem is based on large scale simulations involving several empirical algorithms (compliant with the PNNI routing specification) which have been tested for different network topologies and traffic scenarios. Based on analysis of tradeoffs involving performance metrics (such as blocking rate, complexity, load distribution) we recommend a consistently good routing algorithm for single domain ATM networks.     

满足路径约束的最优路算法

满足路径约束的最优路问题已被证明是NP-hard问题。本针对源点到宿点满足两个QoS(服务质量)度量的路由问题，给出一种保证时延的最小费用路由启发式算法。这个算法的优点是计算较简单、占用内存小、时间短。算法的复杂度是多项式的，表明算法是有效的。     

Detecting and Preventing Routing Problems in the Planning Process of CCSS #7 Networks

Common Channel Signalling System #7 (CCSS#7) has become nowadays widely used by most of the operators which are strongly dependant on its performance. This paper develops next issues. First, usual problems with routing in CCSS#7 networks that can not be solved by the protocol are described, and a checking algorithm based on modified dynamic programming techniques is proposed. And secondly, the problem of updating routing tables of nodes and several alternatives to solve it, are presented and compared. Two kind of solutions to solve this second problem are proposed and tested. Conclusions are presented.     

Autonomous localization based energy saving mechanism in indoor MANETs using ACO

The biggest challenge in MANETs is to find most efficient routing due to the changing topology and energy constrained battery operated computing devices. It has been found that Ant Colony Optimization (ACO) is a special kind of optimization technique having characterization of Swarm Intelligence (SI) which is highly suitable for finding the adaptive routing for such a type of volatile network. The proposed ACO routing algorithm uses position information and energy parameters as a routing metric to improve the performance and lifetime of network. Typical routing protocols have fixed transmission power irrespective of the distance between the nodes. Considering limiting factors, like small size, limited computational power and energy source, the proposed solution excludes use of GPS for identifying the distance between nodes for indoor MANETs. The distance between nodes can be determined by using Received Signal Strength Indicator (RSSI) measurements. Thus, an intelligent ACO routing algorithm with location information and energy metric is developed to adaptively adjust the transmission power and distribute the load to avoid critical nodes. Proposed Autonomous Localization based Eligible Energetic Path_with_Ant Colony Optimization (ALEEP_with_ACO) algorithm ensures that nodes in the network are not drained out of the energy beyond their threshold, as the load is shared with other nodes, when the energy of a node in the shortest path has reached its threshold. Hence, the total energy expenditure is reduced, thus prolonging the lifetime of network devices and the network. We simulated our proposal and compared it with the classical approach of AODV and other biological routing approaches. The results achieved show that ALEEP_with_ACO presents the best Packet Delivery Ratio (PDR), throughput and less packet drop specially under high mobility scenarios.     

Routing-efficient CDS construction in Disk-Containment Graphs

In wireless networks, Connected Dominating Sets (CDSs) are widely used as virtual backbones for communications. On one hand, reducing the backbone size will reduce the maintenance overhead. So how to minimize the CDS size is a critical issue. On the other hand, when evaluating the performance of a wireless network, the hop distance between two communication nodes, which reflect the energy consumption and response delay, is of great importance. Hence how to minimize the routing cost is also a key problem for constructing the network virtual backbone. In this paper, we study the problem of constructing applicable CDS in wireless networks in terms of size and routing cost. We formulate a wireless network as a Disk-Containment Graph (DCG), which is a generalization of the Unit-Disk Graph (UDG), and we develop an efficient algorithm to construct CDS in such kind of graphs. The algorithm contains two parts and is flexible to balance the performance between the two metrics. We also analyze the algorithm theoretically. It is shown that our algorithm has provable performance in minimizing the CDS size and reducing the communication distance for routing.     

Target aiming Pareto search and its application to the vehicle routing problem with route balancing

In this paper, we present a solution method for a bi-objective vehicle routing problem, called the vehicle routing problem with route balancing (VRPRB), in which the total length and balance of the route lengths are the objectives under consideration. The method, called Target Aiming Pareto Search, is defined to hybridize a multi-objective genetic algorithm for the VRPRB using local searches. The method is based on repeated local searches with their own appropriate goals. We also propose an implementation of the Target Aiming Pareto Search using tabu searches, which are efficient meta-heuristics for the vehicle routing problem. Assessments with standard metrics on classical benchmarks demonstrate the importance of hybridization as well as the efficiency of the Target Aiming Pareto Search.     

Sensible decisions based on QoS

Network Quality of Service (QoS) criteria of interest include conventional metrics such as throughput, delay, loss, and jitter, as well as new QoS criteria based on power utilization, reliability and security. Variable and adaptive routing have again become of interest in networking because of the increasing importance of mobile ad-hoc networks. In this paper we develop a probability model of adaptive routing algorithms which use the expected QoS to select paths in the network. Our objective is not to analyze QoS, but rather to design randomized routing policies which can improve QoS. We define QoS metrics as non-negative random variables associated with network paths which satisfy a sub-additivity condition along each path. We define the QoS of a path, under some routing policy, as the expected value of a non-decreasing measurable function of the QoS metric. We discuss sensitive and insensitive QoS metrics, the latter being dependent on the routing policy which is used. We describe routing policies simply as probabilistic choices among all possible paths from some source to some given destination. Incremental routing policies are defined as those which can be derived from independent decisions taken at certain points (or nodes) along paths. Sensible routing policies are then introduced: they take decisions based simply on the QoS of each available path. Sensible policies, which make decisions based on the QoS of the paths, are introduced. We prove that the routing probability of a sensible policy can always be uniquely obtained. A hierarchy of m-sensible probabilistic routing policies is then introduced. A 0-sensible policy is simply a random choice of routes with equal probability, while a 1-sensible policy selects a path with a probability which is inversely proportional to the (expected) QoS of the path. We prove that an m + 1-sensible policy provides better QoS on the average than an m-sensible policy, if the QoS metric is insensitive. We also show that under certain conditions, the same result also holds for sensitive QoS metrics.Accepted: May 2003, This work was supported by the U.S. Army and Navy under contracts N611339-00-K-0002, N61339-02-C0050, N61339-02-C0080, N61339-02-C0117, and by NSF grants EIA0086251, EIA0203446, ECS0216381.     

基于交通流的多模糊时间窗车辆路径优化

研究了基于交通流的多模糊时间窗车辆路径问题,考虑了实际中不断变化的交通流以及客户具有多个模糊时间窗的情况,以最小化配送总成本和最大化客户满意度为目标,构建基于交通流的多模糊时间窗车辆路径模型。根据伊藤算法的基本原理,设计了求解该模型的改进伊藤算法,结合仿真算例进行了模拟计算,并与蚁群算法的计算结果进行了对比分析,结果表明,利用改进伊藤算法求解基于交通流的多模糊时间窗车辆路径问题,迭代次数小,效率更高,能够在较短的时间内收敛到全局最优解,可以有效的求解多模糊时间窗车辆路径问题。     

Ad Hoc网络中基于时分的分布式QoS路由算法

捷径冲突是AdHvc网络中QoS路由特有的一种现象，它由WenjianShao在[2]中首次提出．本文进一步研究了捷径冲突现象，给出了一个更加准确的定义，且给出了一个基于时分的分布式QoS路由算法成功地避免了捷径冲突现象．本算法是基于TDMA的分布式算法，每个节点只需了解网络的局部信息即可．数据分析表明本算法预留的最大带宽比较接近AdHoc网络中所能用的最大带宽．     

On the Hardness of Equal Shortest Path Routing

In telecommunication networks packets are carried from a source s to a destination t on a path that is determined by the underlying routing protocol. Most routing protocols belong to the class of shortest path routing protocols. In such protocols, the network operator assigns a length to each link. A packet going from s to t follows a shortest path according to these lengths. For better protection and efficiency, one wishes to use multiple (shortest) paths between two nodes. Therefore the routing protocol must determine how the traffic from s to t is distributed among the shortest paths. In the protocol called OSPF-ECMP (for Open Shortest Path First-Equal Cost Multiple Path) the traffic incoming at every node is uniformly balanced on all outgoing links that are on shortest paths. In that context, the operator task is to determine the “best” link lengths, toward a goal such as maximizing the network throughput for given link capacities.In this work, we show that the problem of maximizing even a single commodity flow for the OSPF-ECMP protocol cannot be approximated within any constant factor ratio. Besides this main theorem, we derive some positive results which include polynomial-time approximations and an exponential-time exact algorithm. We also prove that despite their weakness, our approximation and exact algorithms are, in a sense, the best possible.