基于逐跳方式的单链路故障保护算法

当网络中的某条链路出现故障时,互联网部署的域内路由协议需要重新收敛,在收敛过程中经过该链路的报文将会被丢弃。针对该问题,IETF(the Internet Engineering Task Force)提出了快速重路由保护框架,利用该框架可以有效地解决网络中单链路故障造成的报文丢失问题,然而该方案并不能完全保护网络中所有可能的单链路故障。基于该框架研究者提出了一种基于隧道的解决方案,该方案虽然可以提供100%的单链路故障保护,但是需要辅助机制的协助,开销较大,难以实际部署。因此,提出了一种基于逐跳方式的针对单链路故障的全保护方案,该方案可以解决网络中任意的单链路故障造成的报文丢失问题。     

基于业务类型的网络切片可靠性映射算法

网络切片是5G网络的基础架构技术,为在多个切片共享同一底层网络资源的同时保证切片的可靠性,提出一种区分业务类型的网络切片可靠性映射算法,解决底层网络链路故障、网络切片可靠性与资源利用率相互矛盾的问题。通过区分切片承载业务类型,对高可靠低时延切片请求的链路提前构建备份路径,并采用基于最大生成树链路的备份资源共享保护方法,对高带宽切片请求则采用基于链路可靠性的重映射算法恢复故障链路。仿真结果验证了该算法的有效性,与SVNE1+1和DPS-VNRA算法相比,其在切片成功运行率、长期收益开销比、物理链路利用率和故障恢复率方面均具有优势。     

基于多链路故障的网络切片生存性算法

为了保证当底层网络的多条物理链路发生故障时用户业务能够不间断,提出一种基于多链路故障的网络切片生存性算法。通过区分切片上承载的业务类型,当高可靠低延迟切片请求到达后,将物理节点按节点重要度排序后进行映射,再对故障链路采用多备份路径算法,选取带宽资源消耗最少的路径依次对故障链路进行重映射,当高带宽切片请求到达后,采用广度优先搜索的节点映射算法,再通过多备份路径对故障链路进行恢复。仿真结果表明,该算法能够提高切片平均映射成功率、长期平均收益开销比、物理链路利用率和故障恢复率,缩短平均故障恢复时延。     

软件定义卫星网络的链路故障检测和恢复方案

针对具有星间链路的卫星网络,提出了一种软件定义卫星网络架构下的链路故障检测和恢复方案。首先基于软件定义卫星网络架构设计了一种主动上报式故障检测机制,并设计了链路故障检测算法,实现对卫星网络中链路故障的快速发现和准确定位。在此基础上,提出了一种保护加恢复式故障恢复机制来快速恢复因故障导致的业务中断。最后在原型系统中对该方案进行了验证。实验结果表明,该方案可以在毫秒级的时间内快速检测并准确定位到链路故障,并可以在10±2ms的时间内对故障进行快速恢复。同时,该方案可适用于多种卫星网络拓扑。     

网络中多节点故障定位的探测路径选择算法

针对现有故障定位技术不能满足多节点故障定位的要求,尤其当网络中存在大量故障节点时,提出了一种基于主动探测的探测路径选择算法。该算法主要包括用于故障检测的贪婪路径选择算法和用于故障定位的禁忌链路搜索算法。在故障检测阶段,使用贪婪路径选择算法迭代地选择具有最小权重的探测路径覆盖网络中的节点。在故障定位阶段,使用禁忌链路搜索算法多次生成候选路径集以选择最合适的探测路径来解决多节点故障定位问题。在随机网络拓扑和真实网络拓扑上的仿真结果表明,与现有的节点故障定位算法相比,探测路径选择算法具有更高的成功定位率和更低的探测成本。     

基于弧不相交着色树的多链路故障恢复方法

为实现网络多链路故障快速恢复,提出一种基于弧不相交着色树重路由的恢复方法。通过改进着色树机制,建立弧不相交着色树生成模型,提出一种改进的布谷鸟算法,引入动态调整步长操作降低陷入局部极值的概率,优化着色树求解。仿真实验表明,该方法不仅能够实现网络多链路故障的完全覆盖,还可获得较短的恢复路径。     

WSN中基于被动端到端的故障链路集推断算法

为了节省故障定位所需的网络能耗,给出了基于被动端到端的启发式贪婪故障链路推断算法.该算法基于被动端到端的数据建立故障链路推理模型,推断网络中最可能故障的链路集.使用端到端的数据计算各条路径的丢包率,通过与阈值的比较对路由矩阵进行简化,目的是去掉根据端到端的数据可以判定为好的路径.由于该推理模型需要各条链路的故障概率,通过简化矩阵的方式优化算法LIPM(loss inference based on passive measurement),给出了推测效果更好的LISC(loss inference based on passive measurement and set-cover)算法.仿真结果显示,新算法具有更好的精确度和运行效率.最后,迭代计算各条链路的权值,通过每次选择最优权值的链路并删除包含此链路的路径,直到所有的故障被解释为止.通过仿真验证了新算法具有更好的故障覆盖率.     

面向软件定义车联网的链路故障快速恢复方法

针对软件定义车联网（SDIV）的车-路实时查询类通信场景中单链路故障的问题，提出一种面向SDIV的链路故障快速恢复方法，综合考虑了链路恢复过程时延和恢复后路径的传输时延。首先，对故障恢复时延建模，将最小化时延的优化目标转化为0-1整数线性规划问题。然后，分析该问题，力图最大化复用已有计算结果，并根据不同情况提出两种算法：在流表更新时延相对路径传输延迟不可被忽略的情况下，提出基于拓扑划分的路径恢复算法（PRA-TP）；在流表更新时延相对路径传输延迟较小可被忽略的情况下，提出基于单链路搜索的路径恢复算法（PRA-SLS）。实验结果表明，相较于Dijkstra算法，PRA-TP的计算时延和路径恢复时延分别降低25%和40%,PRA-SLS的计算时延降低60%，可实现快速的汽车端的信息传输单链路故障恢复。     

IP over WDM网络中可生存的路由选择策略

在IPoverWDM网络中,单链路故障可能会使虚拓扑变得不连通而导致IP网络无法恢复受损业务,在设计虚拓扑时必须避免这种情况。SVTMA算法采用负载均衡策略,在保证网络生存性的同时,严格遵守物理链路的容量限制。实验表明,使用SVTMA算法进行虚拓扑设计所需的波长数小于SMART算法所需的波长数,使得整个网络的负载分布更加均衡。     

一种基于流聚合与拥塞避免的SDN快速故障恢复方案

针对主动式故障恢复方案会忽略备份路径的TCAM存储资源消耗和故障恢复后的拥塞问题，提出一种基于流聚合与拥塞避免的SDN快速故障恢复方案FACAR。FACAR是一种具有拥塞感知、低存储开销的主动式快速故障恢复方案，将通过同一链路的流视作一个或几个聚合流，并为这些聚合流提前配置保护路径。将FACAR方案形式化表示为一个整数线性规划问题，然后提出一种基于贪心的启发式算法ILP-FACAR以求解最少配置备份转发规则的数量。实验结果表明，FACAR可以满足单链路故障后的快速恢复需求，而且相比于其他故障恢复方法，FACAR可以保证在故障恢复后的网络中无链路拥塞问题，且大大减少了备份流规则的TCAM资源消耗。     

Multiprocessor systems with preemptive priorities

A system with N processors and R job classes subject to a preemptive priority scheduling discipline is considered. Exact analysis is presented for the case R = 2, under Markovian assumptions. That analysis suggests a method for obtaining approximate solutions for arbitrary R. The implementation of the methods is discussed and numerical results for some special cases are given.     

Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities

Research concerning project planning under uncertainty has primarily focused on the stochastic resource-constrained project scheduling problem (stochastic RCPSP), an extension of the basic RCPSP, in which the assumption of deterministic activity durations is dropped. In this paper, we introduce a new variant of the RCPSP, for which the uncertainty is modeled by means of resource availabilities that are subject to unforeseen breakdowns. Our objective is to build a robust schedule that meets the project deadline and minimizes the schedule instability cost, defined as the expected weighted sum of the absolute deviations between the planned and the actually realized activity starting times during project execution. We describe how stochastic resource breakdowns can be modeled, which reaction is recommended, when a resource infeasibility occurs due to a breakdown, and how one can protect the initial schedule from the adverse effects of potential breakdowns. An extensive computational experiment is used to show the relative performance of the proposed proactive and reactive strategies. It is shown that protection of the baseline schedule, coupled with intelligent schedule recovery, yields significant performance gains over the use of deterministic scheduling approaches in a stochastic setting. This research has been supported by project OT/03/14 of the Research Fund of K.U.Leuven, project G.0109.04 of the Research Programme of the Fund for Scientific Research, Flanders (Belgium) (F.W.O.-Vlaanderen) and project NB/06/06 of the National Bank of Belgium.     

Influence of the Limited Service Capacity of the Inspection Station on the Control Policy of an Automatized Production System

The influence of the limited capacity of an inspection station on the control policy is studied for a job shop manufacturing process. The production system and the control station are described by queue models M/G/1 and G/G/1, respectively. The deterministic sampling rate is obtained which, in case of breakdown, minimizes the number of defective units.     

考虑设备随机故障的装备维修作业调度方法

装备维修过程中,维修设备随机故障这一不确定因素易对正常的维修计划造成影响。为了优化制定维修设备随机故障条件下的维修作业调度决策方案,依据维修设备的故障特点,提出一种基于组合调度策略的维修作业调度方法。调度方法兼顾完成时间与鲁棒性两方面目标,通过调度优化模型生成调度决策方案,并采用一种组合调度策略进行方案调整以改善决策方案的鲁棒性。通过随机故障事件模拟实验与分析,验证了调度方法能有效地减少设备随机故障造成的工序延误。     

Comparative study on the effects of groupware and conventional technologies on the efficiency of collaborative writing

In this paper the concept of efficiency in collaborative writing is considered in detail and a definition of efficiency is proposed. The definition of efficiency leads to the development of a research framework that delineates five operational measures of efficiency: (a) writing activities efficiency, (b) coordination efficiency, (c) quality of output, (d) absence of breakdowns, and (e) satisfaction with group performance. A comparative study is subsequently presented on the effects that groupware and conventional technologies have on the effciency of collaborative writing. The hypothesis is advanced that groupware can improve the efficiency of collaborative writing over conventional technologies. The results seem to support the hypothesis and indicate that (a) the groupware system examined in this study (MUCH system) offers efficiency benefits in terms of coordination, (b) MUCH users tend to face communication breakdowns while users of conventional technologies tend to face task-related breakdowns, (c) the documents produced with MUCH are of higher content quality, more coherent, and of higher rhetorical effectiveness than the documents produced with conventional technologies, and (d) the comparison of MUCH with conventional technologies shows no significant difference in terms of their effects on group performance satisfaction.     

Multi-agent approach and stochastic optimization: random events in manufacturing systems

We propose a method to solve industrial problems and to take into account random events. It is called the triple coupling. It is based on stochastic algorithms, a simulation model and the multi-agents model of artificial intelligence. The method we propose is easy to use and allows us to take into account most of the constraints found in manufacturing systems. Experts look for solutions to increasing the capacity of production. But the production can be disturbed by random events experienced by the system. Industrial experts need schedules which prevent the consequences of random events. Minimizing such consequences is very important to increasing system delivery. Capital investment is often very high in factories and the cost of the investment goes on regardless of whether the resources are running or not. The multi-agent approach is used to determine schedules for which the consequences of random events are low, and a stochastic algorithm is proposed which permits us to optimize a random variable. We prove that this algorithm finds, with probability one, the schedule of the production for which the consequences of random events are the lowest. We propose to measure the consequences of random events using an influence ratio. Our approach has been used to study the consequences of random events in Peugeot sand foundries of Sept-Fons (France). A benchmark test is presented to prove the efficiency of our solution. For the Peugeot sand foundry of Sept-Fond, random events increase the production time by about 20% compared with the production time without any random events occurring. We have determined schedules of production for which the consequences of random events are about 0.5%.     

Equilibrium customer strategies in Markovian queues with partial breakdowns

We consider equilibrium analysis of a single-server Markovian queueing system with working breakdowns. The system may become defective at any point of time when it is in operation. However, when the system is defective, instead of stopping service completely, the service continues at a slower rate. We assume that the arriving customers decide whether to join the system or balk based on a natural reward-cost structure. With considering waiting cost and reward, the balking behavior of customers is investigated and the corresponding Nash equilibrium strategies are derived. The effects of the information level on the equilibrium behavior are illustrated further via numerical experiments.     

Integrating simulation and genetic algorithm to schedule a dynamic flexible job shop

Much of the research on operations scheduling problems has ignored dynamic events in real-world environments where there are complex constraints and a variety of unexpected disruptions. Besides, while most scheduling problems which have been discussed in the literature assume that machines are incessantly available, in most real life industries a machine can be unavailable for many reasons, such as unanticipated breakdowns (stochastic unavailability), or due to a scheduled preventive maintenance where the periods of unavailability are determined in advance (deterministic unavailability). This paper describes how we can integrate simulation into genetic algorithm to the dynamic scheduling of a flexible job shop with machines that suffer stochastic breakdowns. The objectives are the minimization of two criteria, expected makespan and expected mean tardiness. An overview of the flexible job shops and scheduling under the stochastic unavailability of machines are presented. Subsequently, the details of integrating simulation into genetic algorithm are described and implemented. Consequently, problems of various sizes are used to test the performance of the proposed algorithm. The results obtained reveal that the relative performance of the algorithm for both abovementioned objectives can be affected by changing the levels of the breakdown parameters.     

Note on the article: Maximum entropy analysis of the M/M/1 queueing system with multiple vacations and server breakdowns

Wang et al. [Wang, K. H., Chan, M. C., & Ke, J. C. (2007). Maximum entropy analysis of the M^[x]/M/1 queueing system with multiple vacations and server breakdowns. Computers & Industrial Engineering, 52, 192–202] elaborate on an interesting approach to estimate the equilibrium distribution for the number of customers in the M^[x]/M/1 queueing model with multiple vacations and server breakdowns. Their approach consists of maximizing an entropy function subject to constraints, where the constraints are formed by some known exact results. By a comparison between the exact expression for the expected delay time and an approximate expected delay time based on the maximum entropy estimate, they argue that their maximum entropy estimate is sufficiently accurate for practical purposes. In this note, we show that their maximum entropy estimate is easily rejected by simulation. We propose a minor modification of their maximum entropy method that significantly improves the quality of the estimate.     

多阶段人机协同求解动态柔性作业车间调度问题

针对柔性作业车间生产环境中机器故障的动态调度问题, 以最小最大完工时间和最小偏差为目标, 结合车间调度人员的经验建立多阶段人机协同动态调度策略. 在不同阶段该策略的调度人员可参与优化过程, 提高方案的可行性和稳定性. 设计外部精英库中最优解的更新方法, 依据海明距离保留具有相同目标值的多种调度方案. 最后通过实例仿真验证了该模型和算法的有效性、可行性和稳定性, 更便于有效地指导生产实践.