无线传感器网络能耗均衡路由模型及算法

在综合考虑传感器网络中节点链路接入、数据包传输能耗及节点剩余能量的基础上,提出了一种自适应能耗均衡路由策略,并给出了相应的数学最优化模型及求解算法.优化的目标是均衡网络能耗,进而最大化网络寿命.首先采用跨层分析的方法设计了符合传感器节点计算能力的分布式动态路由树生成算法及各节点的路由选择策略函数;然后通过构造一个双层规划模型使传感器网络的整体能耗趋向均衡,尽可能地延长网络寿命.一个数值例子说明,提出的路由选择策略、双层规划模型及求解算法是可行且有效的.     

基于微分博弈的移动目标防御最优策略

目前,针对移动目标防御最优策略研究大多采用经典单/多阶段博弈和Markov博弈模型,无法在连续实时网络攻防对抗中进行灵活决策.为实现实时选取最优移动目标防御策略,在研究节点级传染病模型与微分博弈理论的基础上,提出了一种移动目标防御微分博弈模型,对网络空间重要节点构造安全状态演化方程与攻防收益目标函数,并设计开环纳什均衡求解算法以得出最优防御策略.仿真结果表明,该方法可有效对网络攻击进行实时防御,并且可针对网络关键节点制定相应移动目标防御策略.     

改进GA的边缘计算任务卸载与资源分配策略

针对现有边缘计算计算卸载算法存在的延迟较大且负载不均衡的问题,提出一种移动边缘计算中基于改进遗传算法的计算卸载与资源分配算法.基于提出的移动边缘计算网络构建系统模型,其中包括能耗、平均服务延迟、执行时间以及负载均衡模型.以能耗、延迟、负载均衡最小化为优化目标,利用改进的遗传算法进行求解,其中采用染色体一维表现形式、交叉和变异算子提高算法的性能.利用iFogSim和Google集群对所提算法进行模拟仿真实验,结果表明,算法种群数量和最大迭代次数的合理值分别是60和25,所提算法得到的计算卸载和资源分配策略在能耗、负载均衡、延迟和网络使用率方面的表现均优于其它算法.     

基于PSO优化博弈的区块链共识算法

针对现有的区块链共识算法存在决策不均衡、适用性过小和产生共识困难等问题,根据纳什均衡理论,将区块链节点视为博弈的参与者,在共识过程中将节点策略选择的纳什均衡作为共识目标,提出基于纳什均衡的共识算法.在纳什均衡求解中利用聚类算法对同类型节点聚类,用基于拥挤距离和引力搜索算法改进的粒子群优化算法求解以类为基本种群的纳什均衡近似解,将均衡解下所对应的结果作为主节点.设计面向组合投资区块链系统求解共识机制的实验,分别从算法的安全性和扩展性验证该算法的有效性.     

基于博弈分析的车辆感知网络节点轨迹隐私保护机制

利用车辆移动"众包模式"为驾驶员提供实时路况信息和探索新的商业服务模式,是车载感知网络的新型应用之一.然而,车辆移动轨迹中的敏感信息易与用户身份相关联,存在隐私泄露问题.提出了一种车载感知网络节点轨迹隐私保护算法,克服了匿名和隐藏技术缺乏数据真实性权衡的缺点,并考虑到多种攻击策略的影响.对于给定的一系列轨迹集,首先确定边信息概率分布,建立攻击者和防御者模型,通过求解攻防博弈中的纳什均衡选择最优的防御策略,并证明其有效性.在此基础上,折中轨迹数据真实性和隐私性,以最大化防御者效用为目标,提出轨迹隐私保护算法.实验结果表明,防御策略在不同的攻击策略下展现出不同的性能,算法所选择的防御策略优于其他的策略.     

基于蚁群算法的飞机定检人员均衡配置

将蚁群算法(ACO)应用于飞机定检人员均衡配置中.首先,根据均方差指标建立人员均衡配置模型;其次,运用3种精英策略并引入信息素限制和自适应机制对基本蚁群算法进行改进,同时提出一种新变异算子以进一步提高算法的性能;最后,运用改进蚁群算法求解模型.实例仿真表明,改进蚁群算法克服了基本蚁群算法搜索时间长、容易早熟的不足,均衡...     

基于博弈论的Multi-homing负载均衡

针对移动网络的多主接入中的负载均衡问题,提出一种基于博弈论的解决方案。通过建立效用函数,量化用户对带宽的需求,根据用户对网络带宽的需求建立Bertrand博弈模型,求解出用户需求带宽的Nash均衡价格,并利用Nash均衡价格调整带宽资源的分配,从而最大化网络自身收益。仿真结果证明算法是有效的,该方案能够合理有效地利用带宽资源,实现了负载均衡。     

内容传递网络处理能力受限代理放置贪婪算法

提出了旨在提高内容传递网络服务性能的代理放置策略CCSP(capacity-constrained surrogate placement).CCSP在保证最大化系统吞吐量的条件下,以最小化系统通信开销为目标,求解最优的代理放置方式.与通信网络中的资源分配问题现有求解策略不同,CCSP通过模拟内容传递网络的请求路由机制,考虑了代理服务器的负载分布及处理能力约束,从而保证系统具有最低的资源消耗、最大的吞吐能力和良好的负载均衡.提出了高效的贪婪算法用以求解树型网络条件下的CCSP问题,并通过仿真实验系统地分析了算法的有效性.     

基于蚁群算法的动态用户均衡配流

在路网中,为了使用户的出行时间降到最低,提出一个适用于多OD对的路网的动态用户均衡离散模型,并应用蚁群算法求解动态用户均衡问题.通过设计一个算例,利用仿真得出路网中的流量分配数据,并和二次规划Frank-Wolfe算法求解的流量分配数据进行比较,最后得出蚁群算法在求解动态交通用户均衡问题时具有一定的优势.     

802.11网络中基于博弈理论的可变带宽信道分配研究

802.11网络中节点的理性和自私性导致可变带宽信道分配的低公平性、低负载均衡性及低社会效率问题.基于非合作博弈理论将可变带宽信道分配问题建模成策略型博弈模型.首先,给出问题的纳什均衡分配策略,证明了纳什均衡点的存在;然后,针对纳什均衡策略社会效率低的问题,提出一种基于支付的激励机制,使可变带宽信道分配过程收敛到占优决策均衡状态,从而系统整体吞吐量性能达到全局最优;并分析了上述两种策略的公平性和负载均衡问题;最后,给出达到纳什均衡和全局最优状态的可变带宽信道分配算法.仿真结果表明,纳什均衡策略能够获得好的公平性,而全局最优策略的负载均衡和社会效率性能要优于纳什均衡策略.     

Fast prediction of the quasi phase equilibrium in phase field model for multicomponent alloys based on machine learning method

The phase field model for multicomponent alloys are usually coupled with the thermodynamic database. But it will take much time to solve the quasi phase equilibrium equations. In order to reduce such time and keep the enough accuracy, we develop a new model to predict the quasi phase equilibrium based on the machine learning method. As an example, the quasi phase equilibrium during the isothermal solidification of Al-Cu-Mg alloy is studied in detail. A neural network model with 3 inputs, 4 outputs and a hidden layer of 150 nodes is constructed. The “training data” are prepared by solving the quasi phase equilibrium equations with least square method. The neural network model is trained by different amount of data set, which can fully cover the ranges of all the variables. The accuracy and performance of the neural network model are discussed in detail. Its high accuracy and fast speed demonstrated that this will be a convenient method to acquire the quasi phase equilibrium data in phase field model for multicomponent alloys.     

基于演化博弈论的无线传感网监测节点分群算法

针对大规模无线传感器网络多辐射源定位中,辐射源公共覆盖范围内监测节点能耗过高造成网络寿命降低的问题,提出一种基于演化博弈理论（EGT）的传感网监测节点分群算法。通过将最优节点集的搜索空间映射到博弈的策略组合空间,以博弈的效用函数为目标函数构建了非合作博弈模型;利用纳什均衡分析及均衡的扰动恢复过程实现目标优化;设计了分群算法以优化节点集组成相应的群参与最终的定位。以接收信号强度指示（RSSI）/信号到达时间差（TDOA）两轮定位为例,将该算法与典型的最近邻算法、基于离散粒子群优化（DPSO）的分群算法在定位精度和网络寿命方面作对比。仿真结果表明,该分群算法避免了多辐射源公共覆盖区域内节点能耗较高的问题,延长了网络寿命,同时保证了对辐射源的定位。     

Supply chain network equilibrium with revenue sharing contract under demand disruptions

Contract is a common and effective mechanism for supply chain coordination, which has been studied extensively in recent years. For a supply chain network model, contracts can be used to coordinate it because it is too ideal to obtain the network equilibrium state in practical market competition. In order to achieve equilibrium, we introduce revenue sharing contract into a supply chain network equilibrium model with random demand in this paper. Then, we investigate the influence on this network equilibrium state from demand disruptions caused by unexpected emergencies. When demand disruptions happen, the supply chain network equilibrium state will be broken and change to a new one, so the decision makers need to adjust the contract parameters to achieve the new coordinated state through bargaining. Finally, a numerical example with a sudden demand increase as a result of emergent event is provided for illustrative purposes.     

Optimal location policy for three competitive facilities

Competitive facility location problems have been investigated in many papers. In most, authors have applied location models with two competitors. In this paper three companies, which are mutually competitive, intend to locate their facilities in a linear market. It is well-known that Nash equilibrium solution for location problem does not include three competitive facilities. In this paper we present the optimal location strategies for three facilities. In our model we assume that the demands are continuously distributed in a linear market and the facilities are locating according to a specific order of sequence, A, B and C. We apply the Stackelberg equilibrium solutions for competitive location problems with three facilities. In our model, we consider the decision problems in three stages. In the first stage, we decide the optimal location of facility A, which is located optimally in respect to the remaining two facilities B and C. In the second stage, we determine the optimal location of facility B which is optimally located in respect to facility C, by utilizing the information on the location of facility A. Finally in the third stage problem we decide the location of facility C, optimally located by utilizing the information on the location of A and B. In the first stage, we need the optimal solutions of the second and third stages. In the second stage we need the optimal solution of the third stage problem. Therefore, first we solve the third stage problem which is the simplest. After that, we solve the second stage problem utilizing the optimal solution strategy of the third stage problem. In this paper we present the optimal location strategies for three facilities.     

Supply chain network design under oligopolistic price and service level competition with foresight

In this paper a new bi-level model for designing the network structure of a competitive supply chain (SC) is presented with anticipating variable prices and service levels competition in markets under stochastic price and service level dependent elastic demands with the presence of existing, external rivals. The network structure of the new entrant SC would be designed under the limited production capacity of its producers in a way to maximize its future capturable profit in the competitive markets. The network of the new SC is assumed to be set “once and for all” but further price and service level adjustments are possible. Outer part of this bi-level model deals with strategic decisions of SC network design. Given the SC network structure assigned by the outer model in each iteration, the inner equilibrium model determines the equilibrium retail prices and service levels. Finally, we illustrate the model through several numerical examples.     

中断情境下可靠性应急设施选址-分配多目标优化模型

应急设施选址是长期战略性决策布局问题,选址-分配网络面临潜在的中断风险.在中断情境下构建以成本经济性、覆盖质量均衡性及公平性为核心的多目标体系.以最小化系统成本为目标反映经济性,以覆盖服务质量最大化为目标反映均衡性,以最大化最小需求覆盖水平为目标反映公平性,建立中断情境下服务能力有限的可靠性应急设施选址-分配多目标优化模型.采用带精英策略的快速非支配排序遗传算法(NSGA-II)对模型予以求解,获得经济成本、覆盖服务质量均衡性与公平性之间的Pareto解集,给出Pareto最优解集在三维空间的分布及应急设施选址布局网络的拓扑结构.研究成果将为决策者在中断环境下设计可靠的选址-分配网络提供决策支持.     

具有模糊需求的多商品流供应链网络均衡研究

研究由多个相互竞争的制造商与多个相互竞争的零售商组成,且零售商处面临模糊市场需求、存在差异性的多商品供应链网络均衡问题.运用logit模型刻画消费者的随机选择行为,利用模糊事件的可信性测度推导零售商的模糊期望利润,借助有限维变分不等式理论构建具有模糊需求的多商品流供应链网络均衡状态满足的变分不等式,并分析了供应链网络均衡解的存在性和唯一性.最后,结合算例讨论了需求的模糊性对供应链网络均衡的影响.     

Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes

This paper focuses on modelling the network flow equilibrium problem on a multimodal transport network with bus-based park-and-ride (P&R) system and congestion pricing charges. The multimodal network has three travel modes: auto mode, transit mode and P&R mode. A continuously distributed value-of-time is assumed to convert toll charges and transit fares to time unit, and the users’ route choice behaviour is assumed to follow the probit-based stochastic user equilibrium principle with elastic demand. These two assumptions have caused randomness to the users’ generalised travel times on the multimodal network. A comprehensive network framework is first defined for the flow equilibrium problem with consideration of interactions between auto flows and transit (bus) flows. Then, a fixed-point model with unique solution is proposed for the equilibrium flows, which can be solved by a convergent cost averaging method. Finally, the proposed methodology is tested by a network example.     

时间演化图的机会传感网络连通均衡性模型

网络连通是网络正常通信的保证,网络连通均衡性是反映网络连通情况的一项重要指标.机会传感网络的拓扑随时间动态变化,使得传统的图模型不再适用于机会传感网络,如何准确刻画机会传感网络的连通均衡程度是研究的目的.定义移动节点的贡献度、聚集系数和连通均衡度,采用连通均衡度表征整个网络的连通均衡情况,基于时间演化图对机会传感网络连通均衡性进行建模.仿真实验结果表明,连通均衡性模型可以反映出整个网络的连通均衡情况,为机会传感网络的演化研究及维护提供支撑.     

液体空气汽液平衡计算模型

汽液平衡计算是精馏塔模拟计算中重要的组成部分。以液体空气汽液平衡计算为研究对象,利用神经网络技术,建立了总压（P）和各组分液相组成（X1、X2、X3）为输入节点,3种不同参数作为输出节点。（1）平衡温度（T）、各组分汽相组成（Y1、Y2、Y3）;(2)平衡温度（T）、各组分平衡常数（K1、K2、K3);（3）平衡温度（T）、汽相氮组成（Y1）及氩、氧平衡常数（K2、3））的BP神经网络模型。通过计算比较,第三种参数作为输出节点的液体空气汽液平衡计算模型,不仅具有良好的学习能力,而且预测结果也比较满意。对进一步研究并应用于空分塔模拟计算具有一定的指导意义。