基于动态定价策略的数据中心能耗成本优化

当前,云数据中心的能耗问题已成为业界关注的热点.已有研究工作大多致力于从技术角度降低数据中心的能耗,或在能耗与性能之间寻求一种最佳的折衷.云计算作为一种商业计算模式,已有研究成果很少考虑到云定价策略对能耗管理机制的影响.文中提出了基于动态定价策略的数据中心能耗成本优化方案.建立起服务价格和能耗成本的统一模型,通过研究两者之间的关系.协同优化服务价格与能耗成本,使数据中心的收益达到最优.鉴于数据中心规模庞大、承载任务繁重等特点,论文采用基于重载近似的大规模排队系统来对数据中心建模,根据不同数据中心间的服务需求量和电价差别,设计了多数据中心间的负载路由机制,旨在削减数据中心的整体能耗成本.针对单个数据中心,定义了双阈值策略以动态调节服务器的各种状态(On/Off/Idle等),从而使数据中心能耗成本得到进一步优化.实验结果表明,论文提出的解决方案能够在满足用户QoS需求的前提下,较好地优化数据中心能耗成本,同时使数据中心的收益达到最优.     

电子商务网站中一个双目标的池尺寸分配机制

为了提高电子商务网站资源提供者和服务提供者效用,本文提出一种新的B-PSA(双目标的池尺寸分配)算法.该算法依照排队论,参数化系统,建立以接纳概率和池尺寸为未知量的双目标优化函数,并使用启发式算法求出解;通过预测,使得各服务类的池尺寸适应变化的访问速率.与现有的算法进行模拟比较,B-PSA能提高整体的满意度.     

面向性能增强的双惯量伺服系统状态反馈控制

为避免使用函数逼近器(神经网络或模糊系统),并提高双惯量伺服系统的瞬态响应和稳态性能,针对含外部扰动的双惯量伺服系统,提出一种基于预设性能函数(Prescribed performance function, PPF)的类比例状态反馈控制策略.首先,提出一种改进的带有最大超调、收敛速率以及稳态误差的预设性能函数,并将该函数融入控制器设计使二惯量伺服的跟踪误差保持在预定的边界之内.其次,基于预设性能函数设计了类比例状态反馈控制器实现跟踪控制.与传统基于函数逼近控制方法相比较,该方法可降低控制系统计算复杂度同时消除反演控制中存在的复杂度爆炸问题.最后,利用双惯量伺服系统实验平台开展了对比实验,验证了所提出方法的有效性.     

多模型预测控制在磨矿分级过程中的应用

磨矿分级过程的控制目标是将一、二级溢流浓度和细度稳定控制在质量指标区间内.磨矿分级过程是胖系统,完成动态优化目标后控制器仍有剩余自由度,因此需考虑局部稳态经济优化.针对这一目标,提出一种考虑局部稳态经济目标的多模型预测控制方案.首先,建立了基于现场数据库的球磨机和分级机传函矩阵模型;然后考虑局部经济性能,将稳态经济目标以罚函数形式嵌入动态优化目标函数;为消除球磨机换球引起的模型失配的影响,建立了一种基于换球规律的多模型切换策略.仿真结果表明了所提出控制方案的有效性.     

按单装配系统中组件生产和库存分配控制策略研究

针对由两种组件、三类顾客需求组成的按单装配系统, 本文研究了其中的组件生产控制与库存分配问题. 在各类顾客需 求是泊松到达过程, 各种组件加工时间服从指数分布的假设下, 我们运用马尔科夫决策理论建立了无限期折扣总成本模型, 根据Lippman转换得到了相应归一化后的离散最优方程, 在此基础之上分析了生产和库存分配联合最优控制策略的结构性质. 本文证明了最优策略是依赖于系统状态的动态策略. 组件的最优生产策略是动态基库存策略, 其中基库存水平是关于系统中其他组件库存水平的非减函数. 而最优的分配策略是动态的阈值策略, 对于只需一种组件构成的顾客需求, 组件的分配阈值是系统中另一组件库存水平的增函数; 而对于同时需要两种组件组成的顾客需求, 其各组件的分配阈值是另一组件库存水平的减函数. 最后通过数值试验给出了各个参数对联合最优控制策略的影响, 并得到了相应的管理启示.     

基于VoD系统批处理阈值的调度分析

本文运用排队论的方法对视频服务系统批处理情形下的部分指标进行了定性分析，分析了系统服务状态；以用户等待平均数和系统吞吐量为主要考察对象，给出了系统吞吐量 、用户等待平均数、批处理阈值、系统服务强度、用户耐心程度的关系；阐述了用户时延受阈值、服务强度及用户耐心程度的影响。仿真结果表明，这也是一种节省资源、提
提高视频服务水平的有效途径。     

可重入生产系统的QBD型模型

考虑可重入生产系统除第一个外均为有限缓冲区的情形,建立了两种两站四缓冲区的 拟生灭过程(QBD)型模型.系统在随机调度策略下状态集是不可约的,而在最后一个缓冲区先 加工(LBFS)的策略下状态集是可约的.将可约的状态集化成不可约的吸收集和可约状态集的 和.求出了系统状态的稳态分布,给出了系统稳定的充要条件.     

完全服务和非对称门限服务两级轮询系统特性分析

区分优先级的轮询服务一直是研究人员讨论并探索的热点,本文则是采用了对称性与非对称性相结合的区分优先级的两级轮询服务模型.系统依托并行方式的处理模式,既提高了轮询系统的利用率,也降低服务器在查询转换期间所耗费的时间.并且运用马尔科夫链和概率母函数的方法建立了轮询系统的数学模型,通过对数学模型的解析精确地给出了两级非对称服务系统平均排队队长及查询周期的表达式.同时,根据系统终端循环周期的二阶特性量近似相等的方法,针对两级非对称模型给出了一种平均等待时间的近似解析式.     

带启动时间和工作故障的M/M/1/N排队系统性能分析

在M/M/1/N可修排队系统中引入了工作故障和启动时间.服务台在忙期允许出现故障,且在故障期间不是完全停止服务而是以较低的服务速率为顾客服务.同时,从关闭期到正规忙期有服从指数分布的启动时间.通过分析此模型的二维连续时间Markov过程,求解出系统平稳方程,建立此系统的有限状态拟生灭过程(QBD).根据系统参数,求解出水平相依的子率阵,从而得到系统稳态概率向量的矩阵几何表示形式.在系统稳态概率向量的基础上,求解出系统吞吐率、系统稳态可用度、系统稳态队长及系统处于各个状态的概率等性能指标的解析表达式.文中的敏感性分析体现了这种方法的有效性和可用性,同时,对系统各性能受系统参数的影响进行了探索.实验表明,文中提出模型的稳定性较好,且更贴近实际服务过程,因此这种模型将被广泛应用于各种实际服务中.     

基于反馈优先服务策略的产品研发管理模型研究

为了研究产品开发排队系统的平稳分布和稳态性能,运用排队理论对产品开发过程进行建模和分析,在改进传统反馈服务笨略基础上,构建产品开发反馈优先排队模型;通过构建拟生灭过程求解反馈优先服务策略下排队系统稳态性能指标,并对传统反馈服务策略和反馈优先服务策略下的性能指标进行比较.结果表明,反馈优先的存在对产品开发任务的时延产生较大影响,通过算例对反馈优先服务策略下产品开发排队系统稳态性能指标进行验证,数值模拟表明产品开发排队系统中的反馈优先服务策略优于传统的反馈服务策略.     

Performance evaluation of two-worker operations in a worker-to-cell order assorting system

This paper studies an order assorting system (OAS) composed of multiple-parallel order assorting aisles (OAAs) in a retailer’s order fulfillment center. We evaluate two worker-assignment policies for a worker-to-part OAA: a dedicated-assignment policy and a shared-assignment policy. Our analytical models evaluate the mean value and variance of worker process time including assorting time, walk time, empty walk time, and blocking time when single-line products arrive randomly. From the worker process time, we identify the system flow time of product lines per each worker-assignment policy using G/G/1 and G/G/2 queuing models. We find that the shared-assignment policy performs better compared to the dedicated-assignment policy in spite of workers’ productivity losses incurred by blocking delays over high sort probability, slow walk speed, and high magnitude and variations of inter-arrival times. At the worker-centric break-even point of worker process time, where worker process time suggests selecting either policy, system flow time always suggests selecting the shared-assignment policy.     

M|M|N queueing system with controlled service mode and disaster

An M|M|N queueing system with identical servers and controlled mode, which is characterized by the parameter, “exponential distribution of service time,” is considered. The mode varies in accordance with a multithreshold strategy. The system is subjected to the action of catastrophic failures that induce the departure of all the customers from the system. An algorithm is developed for calculating the stationary state probability of the system and the performance characteristics with fixed control strategy. An optimal strategy is found numerically in a limited region of values of the threshold. Numerical examples are presented.     

Discrete-time queues with generally distributed service times and renewal-type server interruptions

In this contribution, we investigate a discrete-time single-server queue subjected to server interruptions. Server interruptions are modeled as an on/off process with geometrically distributed on-periods and generally distributed off-periods. As message lengths can exceed one time-slot, different operation modes are considered, depending on whether service of an interrupted message continues, partially restarts or completely restarts after an interruption. For all alternatives, we establish expressions for the steady-state probability generating functions (pgf) of the buffer contents at message departure times and random slot boundaries, of the unfinished work at random slot boundaries, the message delay, and the lengths of the idle and busy periods. From these results, closed-form expressions for various performance measures, such as mean and variance of the buffer occupancy and message delay, can be established. As an application, we show that this model is able to assess performance of a multi-class priority scheduling system. We then illustrate our approach with some numerical examples.     

The queueing equivalence to a manufacturing system with failures

The authors consider optimal production rate control in a failure prone manufacturing system. It is well known that the hedging point policy is the optimum controller for such a system. They show that under the hedging point policy the system can be treated as an M/M/1 queue. Therefore, existing results in queuing theory can be readily applied to obtaining the steady-state probability density function of the production surplus, based on which the optimal hedging point policy can be computed. To a large extent, the approach is based on sample path analysis. It not only provides an alternative way to solve the problem but also reveals some interesting insights     

Power and delay optimisation in multi-hop wireless networks

In this paper, we study the optimisation problem of transmission power and delay in a multi-hop wireless network consisting of multiple nodes. The goal is to determine the optimal policy of transmission rates at various buffer and channel states in order to minimise the power consumption and the queueing delay of the whole network. With the assumptions of interference-free links and independently and identically distributed (i.i.d.) channel states, we formulate this problem using a semi-open Jackson network model for data transmission and a Markov model for channel states transition. We derive a difference equation of the system performance under any two different policies. The necessary and sufficient condition of optimal policy is obtained. We also prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate and the optimal transmission rate can be either maximal or minimal. That is, the ‘bang-bang’ control is an optimal control. This optimality structure greatly reduces the problem complexity. Furthermore, we develop an iterative algorithm to find the optimal solution. Finally, we conduct the simulation experiments to demonstrate the effectiveness of our approach. We hope our work can shed some insights on solving this complicated optimisation problem.     

Production control of a manufacturing system with multiple machinestates

The production control of a single-product manufacturing system with arbitrary number of machine states (failure modes) is discussed. The objective is to find a production policy that would meet the demand for the product with minimum average inventory or backlog cost. The optimal production policy has a special structure and is called a hedging-point policy. If the hedging points are known, the optimal production rate is readily specified. Assuming a set of tentative hedging points, the simple structure of the optimal policy is utilized to find the steady-state probability distribution of the surplus (inventory or backlog). Once this function is determined, the average surplus cost is easily calculated in terms of the values of the hedging points. The average cost is then minimized to find the optimum hedging points     

线性时序逻辑引导的安全强化学习

针对动态不确定环境下机器人执行复杂任务的需求,提出一种线性时序逻辑(linear temporal logic, LTL)引导的无模型安全强化学习算法,能在最大化任务完成概率的同时保证学习过程的安全性.首先,综合考虑环境中的不确定因素,构建马尔可夫决策过程(Markov decision process, MDP),再用LTL刻画智能体的复杂任务,将其转化为有多接受集的基于转移的有限确定性广义布奇自动机(transition-based limit deterministic generalized Büchi automaton, t LDGBA),并通过接受边界函数构建可记录当前待访问接受集的约束型tLDGBA (constrained tLDGBA,ctLDGBA);其次,构建乘积MDP用于强化学习搜索最优策略;最后,基于LTL对安全性的描述和MDP的观测函数构建安全博弈,并根据安全博弈设计安全盾机制保证系统在学习过程中的安全性.严格的分析证明了所提出的算法能获得最大化LTL任务完成概率的最优策略.仿真结果验证了LTL引导的安全强化学习算法的有效性.     

Robust control of the output probability density functions formultivariable stochastic systems with guaranteed stability

Presents two robust solutions to the control of the output probability density function for general multi-input and multi-output stochastic systems. The control inputs of the system appear as a set of variables in the probability density functions of the system output, and the signal available to the controller is the measured probability density function of the system output. A type of dynamic probability density model is formulated by using a B-spline neural network with all its weights dynamically related to the control input. It has been shown that the so-formed robust control algorithms can control the shape of the output probability density function and can guaranteed the closed-loop stability when the system is subjected to a bounded unknown input. An illustrative example is included to demonstrate the use of the developed control algorithms, and desired results have been obtained     

产品随机缺陷生产系统有限时域最优生产控制

针对合格产品产量呈随机分布的单设备单产品类型不可靠生产系统,假设所生产合格产品的产量占所生产产品总量比例的概率分布已知,且产品质量检测消耗时间与生产控制时域相比较小.本文通过对目标函数的离散化,在离散空间上对生产控制策略进行寻优,得到基于当前状态下的最优生产控制策略,该策略可解析表示为合格产品产量分布、成本惩罚系数c~ (c~-)、当前状态及产品质量检测时间的函数.与同类文献所得结果相比较,该控制策略克服了文献[8]结论有可能导致系统状态发散的缺点,并且最优控制策略表达式更简洁,所得结论对实际工程应用而言有显著意义.     

Feedback regulators for jump parameter systems with state and control dependent transition rates

A class of linear, stochastic, jump parameter systems is studied in which the probability law of the parameter processes depends upon the control policy used. An optimal controller is given when the loss function is quadratic. Because of difficulties inherent in the design equations, a more easily evaluated, near optimal controller is provided for problems in which the parameter processes are weakly dependent on the control policy.