一种不需记录后继的扩展SPT动态更新算法

动态SPT算法是在图的拓扑改变时,以原有SPT为基础作局部更新;SPT动态更新需要解决寻找因为该改变而需要修正最短路径的相关节点的问题。对于传统的SPT定义先扩展,使节点记录距离相等的一条或多条最短路径,称之为ESPT。提出了一种不需记录后继的ESPT动态更新算法并加以证明,通过证明还说明在ESPT定义下该算法找到的所有节点都是动态更新所必要且充分的。给出算例,列出操作过程,对不同复杂度的图进行计算实验,将其结果与经典静态算法进行了对比。     

一种高效的最短路径完全动态更新算法

在通信网络中,节点间最短路径的计算是链路状态路由协议计算路由的基础。通过对现有动态最短路径算法的深入研究,提出了一种处理网络拓扑变化的完全动态最短路径算法DSPT-ID。该算法利用已有SPT的信息,建立一个最短路径树的更新队列,当网络拓扑发生变化时,算法针对边的权值增大和减小,分别进行更新,并将更新节点局限在受拓扑变化影响的节点中,从而达到SPT的增量更新。算法复杂度分析和仿真结果显示,DSPT-ID算法具有更少的节点更新次数和更高的时间效率。     

适用于无向网络的动态Dijkstra算法优化

网络拓扑发生变化时,利用静态Dijkstra算法重新计算最短路径树(SPT)会造成冗余计算。动态Dijkstra算法解决了这个问题,但目前动态算法一般是基于有向网络模型进行的研究。在已有的动态Dijkstra算法基础上,提出适用于无向网络的动态Dijkstra算法。算法主要解决了在无向网络中如何确定待更新节点的问题,对网络中的一条边权值增大、减小的处理方法进行了详细描述,并对已有的算法的筛选机制进行了优化。为了验证算法的正确性,用仿真实验实现了该算法并与静态算法进行性能比较。实验结果表明,新算法更能提高节点更新的时间效率。     

一种支持过程动态更新的过程系统设计与实现

在当前开放、变化的Internet环境下,业务过程需要在运行时进行动态更新,同时将原过程下正在运行的实例迁移到更新后的过程模型下.设计了一种支持动态更新的过程系统.在模型层面上,使用AOP(Aspect Orient Programming,面向方面编织)的方法,实现流程运行时动态更新生成新的模型.在引擎层面上,修改原有引擎,使其能够暂停、恢复实例的运行,从而支持实例的动态迁移.在实例层面上,提出了一种实例迁移的算法,为模型提供动态更新的能力.最后,介绍一个应用案例以验证系统的正确性.     

工作流管理系统的流程柔性动态变更研究

为解决工作流管理系统中流程柔性演进变化问题,结合业务模型生命周期和业务流程模型变更管理的特点,提出了一个支持业务流程动态更新模型和业务流程实例动态迁移算法。在该算法中引入区域划分法,在迁移之前进行相关数据一致性检查和影响区域比较,通过该算法实现流程实例动态调整,以适应新的变种。最后基于该算法和一工作流管理系统平台,通过一个案例来演示业务流程动态更新的过程。     

一种高效的最短路径树动态更新算法

计算动态环境下最短路径树是一个典型的组合优化问题。Ba11-and-String模型是一种高效的动态更新算法,但仍存在不少冗余计算。针对Ba11-and-String算法中边的处理进行了优化,从而提高了动态更新的效率,同时实现了对节点的删除和增加,以适应最短路径树的拓扑变化。实验结果表明新算法效率更高。     

免疫agent概念与模型

阐述了免疫agent(ImA)这一新概念，分析了免疫agent求解实体的个性特点。构造出一种能对动态环境进行实时监控和故障预警的多免疫agent的形式化网络模型。并提出一种新颖的免疫agent算法，以此构建的系统具有更强的灵活性，鲁棒性和局部更新能力，是一个适用于动态环境的自组织系统。     

基于容差关系的多粒度粗糙集中近似集动态更新方法

针对不完备信息系统变化时缺失值获取具体属性值的特性，为解决多粒度粗糙集中更新近似集时间效率低的问题，提出了一种基于容差关系的近似集动态更新算法。首先，讨论了基于容差关系的近似集变化的性质，并根据相关性质得出乐观、悲观多粒度粗糙集的近似集的变化趋势；然后，针对更新容差类效率低的问题，提出了动态更新容差类的定理；最后，在此基础上，设计出基于容差关系的近似集动态更新算法。采用UCI数据库中4个数据集进行仿真实验，当数据集变大时，所提更新算法的计算时间远小于静态更新算法的计算时间，即所提动态更新算法的时间效率高于静态算法，验证了所提算法的正确性和高效性。     

基于连续动态运动基元的移动机器人路径规划

针对二维动态场景下的移动机器人路径规划问题，提出了一种新颖的路径规划方法——连续动态运动基元（continuous dynamic movement primitives， CDMPs）.该方法将传统的单一动态运动基元推广到连续动态运动基元，通过对演示运动轨迹的学习，获得各运动基元的权重序列，利用相位变量的更新，实现对未知动态目标的追踪.该方法克服了移动机器人对环境模型的依赖，解决了动态场景下追踪运动目标和躲避动态障碍物的路径规划问题.最后通过一系列仿真实验，验证了算法的可行性.仿真实验结果表明，对于动态场景下移动机器人路径规划问题， CDMPs算法比传统的DMPs方法在连续性能和规划效率上具有更好的表现.     

带标记的不完备双论域模糊概率粗糙集中近似集动态更新方法

当不完备双论域模糊概率粗糙集获取缺省值时,传统的静态算法更新近似集的时间效率较低,为了解决这个问题,对带标记不完备双论域模糊概率粗糙集的近似集动态更新方法进行了研究。首先,给出了带标记的不完备双论域信息系统的相关定义,运用矩阵提出了带标记的不完备双论域模糊概率粗糙集的模型,证明了其相关定理,给出了一种带标记的不完备双论域模糊概率粗糙集的近似集计算方法,并对其进行了讨论分析。其次,当不完备双论域模糊概率粗糙集获取缺省值时,给出了动态更新其近似集的相关定理,并进行了证明,进而设计了一种带标记的不完备双论域模糊概率粗糙集中近似集动态更新算法,并分析讨论了其算法复杂度。最后,在6个UCI数据集和3个人工数据集上进行仿真实验,实验结果表明,该动态更新算法提高了更新近似集的时间效率,并结合实例证明了该动态算法更新近似集时不影响结果的正确性,验证了该动态更新算法的有效性。     

多链路权值增大的动态最短路径算法

动态网络最短路径是交通、通信等系统中的重要问题。在处理多链路权值变大时,多链路权值增大的动态最短路径算法可有效地减少单链路权值增大动态最短路径算法的冗余计算。目前,多链路权值增大的动态最短路径算法的研究较少,尚未存在有效的多链路变大的动态最短路径算法。通过对现有动态最短路径算法的深入研究,提出了一种多链路权值增大的动态最短路径算法(DSPT-MLI)。算法复杂度分析和仿真结果显示,DSPT-MLI算法具有更少的节点更新次数和更高的时间效率。     

Fuzzy-neural self-adapting background modeling with automatic motion analysis for dynamic object detection

In this paper we propose a system that involves a Background Subtraction, BS, model implemented in a neural Self Organized Map with a Fuzzy Automatic Threshold Update that is robust to illumination changes and slight shadow problems. The system incorporates a scene analysis scheme to automatically update the Learning Rates values of the BS model considering three possible scene situations. In order to improve the identification of dynamic objects, an Optical Flow algorithm analyzes the dynamic regions detected by the BS model, whose identification was not complete because of camouflage issues, and it defines the complete object based on similar velocities and direction probabilities. These regions are then used as the input needed by a Matte algorithm that will improve the definition of the dynamic object by minimizing a cost function. Among the original contributions of this work are; an adapting fuzzy-neural segmentation model whose thresholds and learning rates are adapted automatically according to the changes in the video sequence and the automatic improvement on the segmentation results based on the Matte algorithm and Optical flow analysis. Findings demonstrate that the proposed system produces a competitive performance compared with state-of-the-art reported models by using BMC and Li databases.     

基于路由最短路径树的动态多节点删除算法

提出一种基于路由最短路径树的多节点删除动态算法。算法建立一个最短路径树更新队列,将所有将被删除节点的子孙节点保存到该队列;从原最短路径树中删除需要被删除的节点和其所有子孙节点;从队列中选取与根节点距离最短的节点进行更新,已更新节点不再被插入队列,从而减少节点更新次数。实验结果表明,该算法能有效减少节点的更新冗余。     

Dynamic SPT update for multiple link state decrements in network routing

Previous approaches to the dynamic updating of Shortest Path Trees (SPTs) have in the main focused on just one link state change. Not much work has been done on the problem of deriving a new SPT from an existing SPT for multiple link state decrements in a network that applies link-state routing protocols such as OSPF and IS-IS. This problem is complex because in the process of updating an SPT there are, firstly, no simple forms of node set to presumable contain all nodes to be updated and, secondly, multiple decrements can be accumulated to make the updating much harder. If we adopt the updating mechanisms engaged in one link state change for the case of multiple link state decrements, the result is node update redundancy, as a node changes several times before it reaches its final state in the new SPT. This paper proposes two dynamic algorithms (MaxR, MinD) for obviating unnecessary node updates by having part nodes updated in a branch on the SPT only after selecting a particular node from a built node list. The algorithm complexity analysis and simulation results show that MaxR and MinD require fewer node updates during dynamic update procedures than do other algorithms for updating SPT of multiple link state decrements.

无线传感器网络数据融合路由算法的改进

无线传感器网络能量有限,数据融合能通过合并冗余数据减少传输数据量,但其本身的代价不可忽略。针对该问题,研究数据融合代价和数据传输代价对数据融合路由的影响,在基于决策数据融合技术AFST中,对直传数据采用动态最短路径(DSPT)算法,动态识别网络环境和数据特征变化,以最小的代价调整路由。实验与分析结果表明,当网络结构发生变化时,DSPT算法比SPT算法效率更高、更节能。     

Minimizing total completion time on a single machine with a flexible maintenance activity

A problem of jointly scheduling multiple jobs and a single maintenance activity on a single machine with the objective of minimizing total completion time is considered in this paper. It is assumed that the machine should be stopped for maintenance which takes a constant duration within a predefined period. The problem is generalized from the one with a fixed maintenance in that it relaxes the starting time of the maintenance from a fixed time point to a predefined period. Both resumable and nonresumable cases are studied. First, three properties of an optimal solution to each of the two cases are identified. Then it is shown that the proposed shortest processing time (SPT) algorithm is optimal for the resumable case. As for the nonresumable case, the conditions under which the SPT algorithm is optimal are also specified. Furthermore, it is shown that relaxing the starting time of the maintenance cannot improve the relative error bound of the SPT algorithm. The focus of the paper is presented afterwards, which is to develop a dynamic programming algorithm and a branch-and-bound algorithm to generate an optimal solution for this case. Experimental results show that these algorithms are effective and complementary in dealing with different instances of the problem.     

Protecting multicast services in optical internet backbones

Many applications in the future Internet will use the multicasting service mode. Since many of these applications will generate large amounts of traffic, and since users expect a high level of service availability, it is important to provision multicasting sessions in the future Internet while also providing protection for multicast sessions against network component failures. In this paper we address the multicast survivability problem of using minimum resources to provision a multicast session and its protection paths (trees) against any single-link failure. We propose a new, and a resource efficient, protection scheme, namely, Segment-based Protection Tree (SPT). In SPT scheme, a given multicast session is first provisioned as a primary multicast tree, and then each segment on the primary tree is protected by a multicast tree instead of a path, as in most existing approaches. We also analyze the recovery performance of SPT and design a reconfiguration calculation algorithm to compute the average number of reconfigurations upon any link failure. By extending SPT to address dynamic traffic scenarios, we also propose two heuristic algorithms, Cost-based SPT (CB_SPT) and Wavelength-based SPT (WB_SPT). We study the performance of the SPT scheme in different traffic scenarios. The numerical results show that SPT outperforms the best existing approaches, optimal path-pair-based shared disjoint paths (OPP_SDPs). SPT uses less than 10% extra resources to provision a survivable multicast session over the optimal solution and up to 4% lower than existing approaches under various traffic scenarios and has an average number of reconfigurations 10–86% less than the best cost efficient approach. Moreover, in dynamic traffic cases, both CB_SPT and WB_SPT achieves overall blocking probability with 20% lower than OPP_SDP in most network scenarios.