基于隧道模式的校园网多出口解决方案

随着我国教育信息化的大力发展,对网络的应用和要求越来越高,原先的网络无论在速度上,还是服务质量上都已经无法满足广大师生的要求了。对于高校校园网的改造已经迫在眉睫。以实际项目为背景,简述两种校园网多出口解决方案。提出了一种新的模型,即在现有校园网的基础上,通过使用GRE隧道技术,实现校园网的多出口、多服务的要求。用户既可采用原有方式通过教育网接入Internet,也可采用电信等其他网络,高速接入Intemet。文中方案采用在客户端路由的方式,可以根据用户要求,灵活选择教育网出口或者其他ISP提供的网络,并实现灵活计费,满足不同用户的要求。目前此方案已经在某高校进行试验,结果证明了它能有效地提高网速。此方案不仅可用于校园网,也可用于企业或者小区的改造。     

无线传感器网络路由协议及安全问题研究

无线传感器网络在军事和民用领域得到广泛的应用。由于传感器节点的资源有限以及通信的开放性使得其安全性显得尤为重要。出于对能量消耗的考虑,目前的路由协议设计得比较简单,作者对路由的安全性能以及可能受到的攻击进行分析,并给出相应的防范对策。     

Efficient realization of frequently used bijections on cube-connected cycles

CCC has lower hardware complexity than hypercube and is suited for current VLSI technology.LC-permutations are a large set of important permutations frequently used in various parallel computations.Existing routing algorithms for CCC cannot realize LC-permutations without network conflict.We present an algorithm to realize LC-permutations on CCC.The algorithm consists of two periods of inter-cycle transmissions and one period of inner-cycle transmissions.In the inter-cycle transmissions the dimensional links of CCC are used in a “pipeline” manner and in the inner-cycle transmissions the data packets are sorted by a part of its destination address.The algorithm is fast (O(log2N)) and no conflict will occur.     

Multi-objective routing algorithms for low-earth orbit satellite network

The low-earth orbit (LEO) satellite network, composed of a large number of satellite nodes, is a hot research topic at present. Due to the characteristics of the large-scale LEO satellite network, such as many satellite nodes, short orbit period, large dynamic change of topology, and unstable link-state, its communication quality of service (QoS) requirements are difficult to meet. Aiming at this problem, various factors that may affect data transmission are first analyzed. The network link selection problem is modeled as a multi-constraint optimization decision problem, a routing mathematical model based on linear programming (LP) is designed, and its solution is solved. Aiming at the problem of limited onboard computing resources, a multi-object optimization Dijkstra algorithm (MOODA) is designed. The MOODA finds the optimal path according to the comprehensive performance of the link. It solves the problems of poor comprehensive QoS performance and the low degree of load balancing of the paths found by the Dijkstra algorithm. The simulation results show that the paths found by the two algorithms have good QoS, robustness, and load balancing performance.     

Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

In today's Internet routing infrastructure, designers have addressed scaling concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain. In tactical Mobile Ad-hoc Network (MANET), hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out, self-mending and self-administration. Clustering in the routing process is one of the key aspects to increase MANET performance by coordinating the pathways using multiple criteria and analytics. We present a Group Adaptive Hybrid Routing Algorithm (GAHRA) for gathering portability, which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile situations. Based on this aspect, the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach, with the objectives of enhancing the output of MANET routing computation in each hub. Simulation analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.     

Integrated mathematical optimisation approach for the tower crane hook routing problem to satisfy material demand requests on-site

Optimising decisions around the location and operation of tower cranes can improve the workflow in construction projects. Traditionally, the location and allocation problems involved in tower crane operations in the literature have been solved separately from the assignment of material supply points to demand points and the scheduling of the crane’s activity sequence across supply and demand points on a construction site. To address the gap, this paper proposes a binary integer programming problem, where location of the tower crane, allocation of supply points to material-demanding regions, and routing of hook of the crane based on activity sequencing of the hook across supply and material-demanding regions on site are optimised. The novelty in this work is in the way the crane’s activity scheduling is modelled via mathematical programming, based on routing the hook movement to meet material demand, through minimising tower crane operating costs. A realistic case study is solved to assess the validity of the model. The model is contrasted with results obtained from other solving algorithms commonly adopted in the literature, along with a solution proposed by an experienced practitioner. Results indicate that all instances can be solved when compared to other meta-heuristics that fail to achieve an optimum solution. Compared to the solution proposed by the practitioner, the results of the proposed model achieve a 46% improvement in objective function value. Planners should optimise decisions related to the location of the crane, the crane’s hook movement to meet service requests, and supply points’ locations and assignment to material-demanding regions simultaneously for effective crane operations.     

一维水沙耦合模型参数敏感性分析——以2020年黄河下游洪水演进为例北大核心CSCD

一维水沙输移及河床冲淤模型中有较多理论上尚未解决的参数,而这些参数对一维模型精度的影响缺少定量分析。本文首先介绍了一维水沙耦合动力学模型,并将其应用于2020年汛期黄河下游的水沙过程模拟。计算结果表明:该模型能准确模拟水位和流量的变化,纳什效率系数基本大于0.85,均方根误差比相应的实测特征值小一个量级;计算沙峰虽然偏大,但计算的含沙量过程与实测过程整体符合,且模型计算的分河段冲淤量与断面地形法实测值较为接近。为分析模型中经验参数对模型计算结果的影响,以水文断面特征水沙参数的纳什效率系数作为目标函数,采用Sobol全局敏感性分析方法计算了各经验参数的敏感度指标。计算结果表明:糙率的总敏感度指标较高,是模型的高敏感参数;目标函数的选取对参数敏感度分析有一定影响,以含沙量纳什效率系数为目标函数时,挟沙力公式的系数及淤积时恢复饱和系数公式中指数的一阶敏感度和总敏感度指标较高;各参数组合对不同目标函数的影响差别较大,但对于同一目标函数存在影响作用相似的参数组合。全局敏感性分析方法刻画了模型参数的敏感性特征,有助于优化水沙数学模型参数取值。     

多尺度混合注意力胶囊网络的海洋鱼类识别

针对胶囊网络(capsule network,CapsNet)特 征提取结构单一和数据处理中参数量过大的问题,提出 多尺度混合注意力胶囊网络 模型。首先,在网络初始端添加不同尺度的卷积核来多角度提取 特征,并引 入混合注意力机制,通过聚焦更具分辨性的特征区域来降低复杂背景干扰。其次,采用局部 剪枝算法优 化动态路由,减少参数量,缩短模型训练时间。最后,在海洋鱼类数据集F4K(Fish4Knowled ge)上验证, 结果表明,与传统残差网络(residual network50,ResNet-50)、双线性网络(bilinear convo l utional neural network,B-CNN)、分层精简双线性注意力网络(spatial transformation netw ork and hierarchical compact bilinear pooling,STN-H-CBP)以及CapsNet模型相比,该算法 识别精度为98.65%,比ResNet-50模型提升 了5.92%;训练时间为2.2 h,相比于CapsNet 缩短了近40 min,验证了该算法的可行性。     

针对复杂多环网络拓扑的路由改进算法

网络运营商为用户提供的光纤接入主干网大多以环型网络的方式提供服务,然而目前对于大规模、环数众多、连接方式多样化的复杂多环网络缺乏性能优良的路由算法。为解决传统环网结构网络延迟高和传输效率低的问题,提出一种针对复杂多环网络拓扑的路由改进算法,将多环网络中的复杂路由问题转化为单环网中的简单路由问题。在此基础上,通过设计源溯节点还原以及路径还原算法,将单一环网改进为增强环网网络结构,使同一环内通信节点间的路径还原为完整最短路径,并从理论上证明该算法得到的最优路径是无差错的。实验结果表明,相比于现有的优化Dijkstra算法,该算法的搜索空间比提升约13%,具有更好的改进效果,且算法运行时间缩短79%,更适合复杂多环网络的路由计算。     

A mathematical model for vehicle routing problem under endogenous uncertainty

In this study, a multistage stochastic programming (SP) model is presented for a variant of single-vehicle routing problem with stochastic demands from a dynamic viewpoint. It is assumed that the actual demand of a customer becomes known only when the customer is visited. This problem falls into the category of SP with endogenous uncertainty and hence, the scenario tree is decision-dependent. Therefore, nonanticipativity of decisions is ensured by conditional constraints making up a large portion of total constraints. Thus, a novel approach is proposed that considerably reduces the problem size without any effect on the solution space. Computational results on some test problems are reported.