无线传感器网络分簇算法研究综述

由于无线传感器网络存在能量约束问题,因此如何利用现有能量资源,延长网络的生命周期是无线传感器网络技术迫切需要解决的问题。分簇算法(Cluster Algorithm)是无线传感器网络在分层路由中的重要算法。本文在简单介绍当前几个典型分簇算法的基础上,重点分析了簇首的形成过程,最后给出了结论和展望。     

基于图的广度搜索的进度生成机制

启发式算法是解决资源受限的项目调度问题的经典方法之一，通常用来生成元启发算法初始解，传统的串行（SSGS）和并行（PSGS）是生成项目调度方案的经典机制，本文基于图的广度优先搜索算法，提出了一种考虑任务节点位置因素的广度生成机制（BSSGS），并验证了算法的效果。借鉴广度搜索算法定义进度生成机制中的当前任务集合C、候选任务集合D以及阶段变量g等，对各任务节点进行层次划分并定义任务调度秩序；结合优先规则选择候选任务j^*并进行资源R_k（t）调度更新，进而生成完整的调度方案；案例分析表明新机制在满足优先规则和资源约束的同时兼顾了任务节点在网络中位置因素，拥有对于局部复杂网络不回避，对关键节点及时调度等明显优势；选择PSPLIB中算例，在不同优先规则下对新机制进行了测试，测试结果表明新的进度生成机制在LPT、SPT、MTS和MIS等优先规则下，在平均最短工期、平均资源利用率及最优调度方案率等方面优于串行和并行进度生成机制，且算法时间复杂度与传统机制相比并未增加，仍为O（J²，K）。     

个体投资者情绪与股票价格行为的互动关系研究

本文运用情感分析技术，在情感倾向点互信息（SO-PMI）算法的基础上，引入"拉普拉斯修正"和"情绪分类阈值"，提出了一种改进的个体投资者情绪度量的SO-LNPMI算法；基于上证指数股吧的31万条论坛信息，运用格兰杰因果检验方法研究了个体投资者情绪与市场收益率和成交量的互动关系。研究表明：（1）与经典的SO-PMI算法相比，本文提出的SO-LNPMI算法的情感识别精度更高；（2）积极情绪是股票收益率的格兰杰原因，消极情绪对其影响不显著；（3）投资者情绪与成交量存在双向的格兰杰因果关系；（4）当投资者处于积极状态时，会热衷于使用表情符号表达情绪。本文的研究为投资者情绪度量提供了一种新的有效算法，有助于投资者更好的利用网络论坛信息进行投资决策。     

探讨路由器原理在网络管理系统中的重要作用

随着计算机网络技术和通信技术的快速发展,路由协议和路由策略的不断完善,路由器对提高网络性能,保证网络质量,为人们提供更加快捷、方便以及安全及时的网络具有重要的作用。本文首先进行介绍路由器技术的概念以及其工作原理,重点探讨其在互联网中的应用价值。     

分布式虚拟现实技术与实验教学结合的思考

一、什么是分布式虚拟现实技术 分布式虚拟环境是虚拟现实技术和网络技术发展和结合的产物。分布式虚拟环境的目标是利用计算机构造一个真实世界的模拟，地理上分布的多个用户可以通过网络共享该环境，选择一个虚拟化身代替自己与该环境和在相互之间进行交互。它提供给用户更具有沉浸感和交互性的人机界面和相互交流的方式，与现在所谓的WIMP（Windows、Icons、Menus、Pointer）二维界面相比，人们可以更加直观方便地操作日益复杂的信息。     

基于Floyd-Warshall算法的无线传感器网络路由选择

无线传感器网络以其特有的组织方式在各个行业得到了广泛的应用,在军事领域的应用更为广阔。作为传感器网络最基本的研究是路由协议的设计。将无线传感器网络最佳路由问题转化为图论最短路径问题,本文利用Floyd-Warshal算法有效解决不含负有向圈的有向图的最短路径求解,从而解决无线传感器网络的最佳路由与能耗问题。     

新能源风电技术人才成长最优路径研究

新能源风电的可持续发展需要可持续的人才支撑。而风电作为多学科交叉的新兴产业，其技术人才的培养和聚集周期长。因此，如何有效提升风电技术人才成长速度和质量至关重要。本文在对技术人才成长网络特征分析的基础上，利用成长代价函数量化标度不同成长状态关系，构建了风电技术人才加权小世界网络，并通过改进Floyd算法，优化风电技术人才成长路径选择。且通过仿真实验证明这种组合方法有效提高了计算速度和精度，降低了时间复杂度，为有效提升新能源风电技术人才成长速度与质量提供了量化方法支撑。     

较园网中三层交换和VLAN技木的应用

校园网设计使用虚拟局域网（VLAN）的功能,可以保证全网的良好性能及网络安全性。VLAN间的路由,用三层交换机来代替路由器,可以加快局域网内部的数据交换,做到一次路由,多次转发。使用虚拟局域网（VLAN）技术和三层交换技术能较好的满足校园网的需求。     

解读4：重装上阵：网络时代的角色重塑

以网络为代表的信息技术正在深刻地改变我们的生产方式与生活方式，同时也给政府的管理模式带来一场革命。决策支持系统（DSS）、电子会议系统（EMS）、远距离控制、分布式工作等信息技术充分运用到行政管理之中，打破了时空限制，改变了传统的科层组织结构，缩减了中间管理层，     

大数据下分位数回归通讯有效算法及其应用

考虑风险度量中常见的分位数回归模型，给出在超大容量数据且复杂数据类型下的几类快速分布式算法.虽然仅考虑分位数回归模型，但本文提供的算法大多数可以应用到其它更一般的模型中.由于分位数回归模型的目标函数为非光滑函数，通常的分块集成法和光滑函数高效通讯算法并不适用.本文首先针对完整观测数据，给出了分位数回归模型参数估计的等度连续法，光滑函数逼近法和改进的数萃(Meta)方法三种分布式通讯有效算法.进一步，考虑了非平衡半监督数据，分别针对无标签数据样本量较小和较大两种情形，提出了加权损失函数法和改进的数萃方法两种数据融合方法.所提出的方法可以把分散在不同机器上的半监督数据进行数据融合，从而实现不同数据类型和不同样本量情形下的高效通讯分布式计算，提高算法的精度和参数估计的效率.本文通过大量仿真模拟研究了所提出的算法在有限样本下的表现，并将其应用到了洛杉矶流浪人口数的实际数据分析中，发现其均具有较好的准确性.     

Scheduling Support Times for Satellites with Overlapping Visibilities

We consider the scheduling of ground station support times to low Earth orbit (LEO) satellites with overlapping visibilities. LEO satellites typically complete a revolution around the Earth in less than four hours at an altitude of a few hundred miles and are part of the critical infrastructure for natural resource management, crop yield estimation, meteorology, flood control, communication, and space research. Because these satellites are quite expensive to launch and operate, utilizing them in the best possible manner is of paramount importance for the agencies that own them. A ground station provides support time to a satellite to perform a variety of tasks when the satellite is visible to the station over a prespecified planning horizon; the payoff from providing such support is a function of the support time. When two or more satellites pass over the ground station, their visibility time windows may overlap. Thus, under overlapping visibilities, a relevant problem is that of scheduling ground station support time for each satellite with the objective of maximizing the total utility generated from supporting the satellites. We propose four basic scheduling models to address a variety of scenarios and investigate their computational complexities. For each model, we also identify special cases that are polynomially solvable.     

Dynamic Policies for Optimal LEO Satellite Launches

Low‐earth orbit satellite (LEO) systems continue to provide mobile communication services. The issue of cost containment in system maintenance is a critical factor for continued operation. Satellite finite life‐times follow a stochastic process, and since satellite replenishment cost is the most significant on‐going cost of operation, finding optimal launch policies is of paramount importance. This paper formulates the satellite launch problem as a Markovian decision model that can be solved using dynamic programming. The policy space of the system is enormous and traditional action space dominance rules do not apply. In order to solve the dynamic program for realistic problem sizes, a novel procedure for limiting the state space considered in the dynamic program is developed. The viability of the proposed solution procedure is demonstrated in example problems using realistic system data. The policies derived by the proposed solution procedure are superior to those currently considered by LEO system operators, and result in substantial annual cost savings.     

大规模客运专线网络运营优化模型与求解算法

本文在分析铁路运营优化模型的研究进展的基础上,提出了一个适合大规模客运专线网络运营的优化模型,并提出了求解此模型的列生成算法和启发式快速算法。目的是将客运专线网路的开行方案优化与动态收益优化问题结合起来,解决更大、更复杂的客运网络运营优化问题。模型以列车运营总收益最大化为目标。用随机生成数据进行的模型试验表明,模型及算法可以在较短的时间内求解较大规模的收益管理优化问题。     

Combinatorial analysis for route first-cluster second vehicle routing

Two Route first-cluster second vehicle routing algorithms are contrasted in the first section of the paper. Next, the ‘large’ number of feasible solutions to a multiple travelling salesman problem is established given that each salesman can visit any number of customers in a stated range. An approximate expression is given for the ‘small’ fraction of this solution space searched by a route first-cluster second vehicle routing heuristic. Nevertheless, this heuristic is seen to be a very efficient means of searching its solution space.     

Reliability evaluation of a multicast over coded packet networks

Network coding is a generalization of conventional routing methods that allows a network node to code information flows before forwarding them. While it has been theoretically proved that network coding can achieve maximum network throughput, theoretical results usually do not consider the stochastic nature in information processing and transmission, especially when the capacity of each arc becomes stochastic due to failure, attacks, or maintenance. Hence, the reliability measurement of network coding becomes an important issue to evaluate the performance of the network under various system settings. In this paper, we present analytical expressions to measure the reliability of multicast communications in coded networks, where network coding is most promising. We define the probability that a multicast rate can be transmitted through a coded packet network under a total transmission cost constraint as the reliability metric. To do this, we first introduce an exact mathematical formulation to construct multicast connections over coded packet networks under a limited transmission cost. We then propose an algorithm based on minimal paths to calculate the reliability measurement of multicast connections and analyze the complexity of the algorithm. Our results show that the reliability of multicast routing with network coding improved significantly compared to the case of multicast routing without network coding.     

Complexity analysis for maximum flow problems with arc reversals

We provide a comprehensive study on network flow problems with arc reversal capabilities. The problem is to identify the arcs to be reversed in order to achieve a maximum flow from source(s) to sink(s). The problem finds its applications in emergency transportation management, where the lanes of a road network could be reversed to enable flow in the opposite direction. We study several network flow problems with the arc reversal capability and discuss their complexity. More specifically, we discuss the polynomial time algorithms for the maximum dynamic flow problem with arc reversal capability having a single source and a single sink, and for the maximum (static) flow problem. The presented algorithms are based on graph transformations and reductions to polynomially solvable flow problems. In addition, we show that the quickest transshipment problem with arc reversal capability and the problem of minimizing the total cost resulting from arc switching costs are NP\mathcal{NP} -hard.     

On the construction of k-connected m-dominating sets in wireless networks

Connected dominating sets (CDS) that serve as a virtual backbone are now widely used to facilitate routing in wireless networks. A k-connected m-dominating set (kmCDS) is necessary for fault tolerance and routing flexibility. In order to construct a kmCDS with the minimum size, some approximation algorithms have been proposed in literature. However, the proposed algorithms either only consider some special cases where k=1, 2 or k≤m, or not easy to implement, or cannot provide performance ratio. In this paper, we propose a centralized heuristic algorithm, CSAA, which is easy to implement, and two distributed algorithms, DDA and DPA, which are deterministic and probabilistic methods respectively, to construct a kmCDS for general k and m. Theoretical analysis and simulation results indicate that our algorithms are efficient and effective.     

多油品供给受限下多油库被动配送车辆路径问题研究

成品油供给不足将导致加油站油品订单无法完全满足,如何安排有限油品的合理配送对保障能源供给安全至关重要。为此,本文考虑有限供给下不同客户配送的优先次序,开展配送计划、车辆调度和路径优化等油品配送网络规划活动,对多油品供给受限情况下多油库被动配送车辆路径问题（Multiple Depot Vehicle Routing Problem,MDVRP）进行深入研究。首先,文章构建了考虑需求优先等级和配送成本的多油品多油库车辆路径规划多目标优化模型。其次,采用多目标粒子群优化算法（Multi-Objective Particle Swarm Optimization,MOPSO）对模型进行求解,以实现车辆高效调度和油品配送路径优化。最后,基于CNPC在青岛市部分油库和加油站点的数据信息,构建油品配送网络进行实证检验。算例结果显示,配送车辆路径经过优化后,生成Pareto非劣解集,配送成本显著降低,配送满足率明显提高,这也进一步验证了该模型及相关算法的可行性和有效性。     

When Many Davids Collaborate with One Goliath: How Inter‐organizational Networks (Fail to) Manage Size Differentials

How do organizations of vastly different size collaborate in order to achieve a common goal? While this poses less of a problem when the network is orchestrated by a classic lead firm, in networks exhibiting a shared governance mode, where leadership responsibilities are more or less equally distributed, size differentials present a critical management challenge. In this paper, we contribute to the literature on coordination in and of inter‐organizational arrangements by emphasizing the so far largely neglected role of size for managing close collaborative relationships. We study the case of Apprenticeship Network, a network that originally consisted of seven small and medium‐sized enterprises, but which then accepted a very large multinational firm as a new member. By unpacking how the network coordinated its endeavour over time to achieve accountability, predictability and a common understanding as critical conditions for effective coordination, we explore how coordination effectiveness may deteriorate and result in the failure of the collaborative effort. We pay special attention to the role of size in these processes, and we theorize how the strategic front and back‐staging of agreed‐upon rules and norms facilitates the formation, maintenance and deletion of a tie, thus producing important network dynamics.     

Dispatching design for storage-centric wireless sensor networks

In a large-scale storage-centric wireless sensor network (SWSN) where data from different clusters are archived at distributed storage nodes, the dispatching design problem is to determine one or multiple storage nodes for each cluster. To achieve high data fidelity in SWSNs, the dispatching design should aim to reduce the data loss due to the network congestion and, at the same time, to prolong the network lifetime by avoiding sending excessive traffic to some particular storage nodes in order to achieve energy consumption balance among the relaying sensors around the storage node. In this paper, we propose an h-peak dispatching design for SWSN. Under such a design, regular traffic volume from each cluster will receive guaranteed data fidelity, and over-expectation traffic will receive best-effort data fidelity. We use an h-peak model to characterize the traffic deviation which assumes that at most h clusters may have over-expectation traffic simultaneously at a storage node. By incorporating h into the dispatching decision rather than assuming that all clusters may reach their traffic spikes simultaneously, the proposed h-peak dispatching design can achieve high data fidelity in SWSNs.