求解具有混合约束流水车间调度问题的迭代贪婪算法

流水车间调度问题是具有典型工程应用背景的组合优化问题,对该问题的研究具有重要的理论意义和应用价值。基于传统的流水车间调度问题,提出一种有限等待约束、阻塞约束以及无等待约束共存的混合约束流水车间调度问题。以问题的最小化最大完工时间为目标,提出一种利用迭代贪婪算法进行求解的方法,该方法利用改进的NEH算法计算初始解,通过迭代贪婪算法进行优化,并设计多点交叉策略和插入邻域搜索策略提高解的质量。通过经典实例测试,验证了所提算法的有效性。     

基于优化前向纠错和TCP友好阻塞控制的实时音频传输策略研究

结合优化前向纠错策略和TCP友好阻塞控制算法，提出了一个新的基于Internet的实时音频数据传输策略．该策略根据TCP友好阻塞控制算法计算实时音频数据流在网络上可以获得的TCP友好的传送速率，同时根据检测到的网络状态和计算的速率，利用优化前向纠错策略来计算在发送端的数据包中应该包括多少冗余信息、采用何种编码方法才能在接收端获得最好的服务质量．实际的Internet实验和在内部网络的模拟实验显示该策略工作良好。     

一种基于TCRA的低轨星座通信系统的强占预留信道策略

在基于时间信道预留算法的基础上,提出了一种改进的低轨星座通信系统信道分配策略——强占预留信道策略。讨论了策略的基本原理,并通过仿真,比较分析了该策略与 TCRA 和固定信道预留策略对系统新呼叫阻塞概率、切换失败概率和服务等级的影响。仿真结果表明,与 TCRA 策略相比,该策略有效降低了新呼叫阻塞,同时为网络提供更好的 QoS 保证。     

Hadoop集群环境下集成抢占式调度策略的本地性调度算法设计

在Hadoop集群环境下本地性调度算法是提高数据本地性的算法。本地性调度算法的调度策略的本质是提高数据本地性,减少网络传输开销,避免阻塞。但是由于Map任务的完成时间不同,Reduce任务存在的等待现象影响了作业的平均完成时间,使得作业的完成时间增加,进而引起系统的性能参数不佳。因此提出在保留原算法数据本地性要求的基础上集成可抢占式的调度方法。在Reduce任务等待时,挂起该任务并释放资源给其他Map任务,当Map任务完成到一定程度后,重新调度Reduce任务。基于上述调度策略设计了集成抢占式策略的本地性调度。为了对改进的算法进行验证,通过实验对本地性调度算法和集成抢占式本地性调度算法进行比较。实验结果表明,在相同数据上,集成抢占式本地性调度算法的平均完成时间有明显的降低。     

基于动态反馈多线程的大数据驱动缓存的设计与实现

对大数据驱动缓存设计原理进行了研究,针对常规数据传递策略时间性能和在性能稳定性上的不足,在大数据的驱动缓存设计上,提出了基于动态反馈的多线程主动等待策略。该策略首先采用主线程主动等待的方式实现了多线程数据处理方案,在此基础上引入动态反馈,通过平衡数据驱动和服务器、应用系统之间数据流与指令流的传递,以提供常规多线程传递策略无法实现的负载不确定性下的性能保证。     

嵌入式操作系统中非阻塞的同步机制

传统阻塞同步的缺点在于容易引起进程死锁和优先级的翻转，为了有效解决此类问题，出现了一种新的同步机制——非阻塞同步，该同步机制主要包括锁自由同步和等待自由同步。介绍了非阻塞同步在操作系统中的实现前提——同步原语和类型稳定的存储器管理以及它的实现技术，最后根据嵌入式系统的特点，提出了把非阻塞同步用于嵌入式操作系统的思想。     

基于Linux的进程迁移机制设计

进程迁移在集群和分布式系统中发挥着重要的作用。进程迁移算法直接影响着迁移时间，目前流行的几种进程迁移算法的共同问题是迁移时间比较长，文中提出了一种改进的进程迁移算法，该算法借鉴了目前几种算法的优点。在此算法的基础上，设计了一种基于Linux-2．4．0内核的进程迁移机制。实验结果表明：这种迁移机制有效的提高了进程迁移的速度。     

Windows Vista操作系统十大优化技巧

一、缩短关闭应用程序与进程前的等待时间 Windows Vista在强行关闭应用程序与进程前同样有一段等待该程序或进程自行关闭的时间，只有超过该时限后，Windows系统才会将其强行中止。因此．缩短默认关闭应用程序或进行等待时间，同样能够加快Windows Vista的关机速度。     

一种基于动态进化模型的事件探测和追踪算法

在大量分析网络新闻特点的基础上，借鉴Single-Pass聚类思想，并结合新闻要素给出了一种基于动态进化模型的事件探测和追踪算法．该动态模型是基于新闻事件的生存特点提出的，包括：基于时间距离的相似度计算模型、事件模板进化策略以及动态阈值设置思想．该算法可以自动对新闻资料进行组织生成新闻专题，进而为用户提供个性化服务．实验结果验证了算法的有效性．     

一类动态多尺度系统融合估计算法的分析

为了进一步认识基于状态空间投影的一类动态多尺度系统的融合估计算法本质,本文对该算法进行了分析．首先,将该融合估计算法和在最细尺度上直接进行卡尔曼滤波的算法性能进行了比较,并用仿真进行了验证．结果表明,在最细尺度上,融合估计效果比直接进行卡尔曼滤波的效果好．其次,从计算过程和计算量方面,与一般的时间配准方法进行了对比分析．结果表明,该融合估计算法用比较严谨的数学模型代替了时间配准,可以在每个尺度上获得基于全部观测信息的最优估计,但计算量比时间配准方法大．本文的研究为基于状态空间投影的一类动态多尺度系统的融合估计算法的实际应用奠定了基础．     

集群环境中的对周期性Barrier应用的调度策略

在工作站集群系统中调度周期性Barrier并行应用，若采用不加修改的本地调度器或只采用Spin-Block策略的调度器，则所获得的性能距离最佳性能都有着或多或少的差距，并且不能很好地扩展到多个应用同时运行的情况．本文提出了一种新的Preempt-Block策略以解决一致状态的获取问题，而利用Spin-Block策略维持一致状态．上述二者相结合的策略使得系统的CPU占用时间和应用的响应时间都接近最优化，并适用于多个Barrier应用同时执行的情况．     

Vector field editing and periodic orbit extraction using Morse decomposition

Design and control of vector fields is critical for many visualization and graphics tasks such as vector field visualization, fluid simulation, and texture synthesis. The fundamental qualitative structures associated with vector fields are fixed points, periodic orbits, and separatrices. In this paper, we provide a new technique that allows for the systematic creation and cancellation of fixed points and periodic orbits. This technique enables vector field design and editing on the plane and surfaces with desired qualitative properties. The technique is based on Conley theory, which provides a unified framework that supports the cancellation of fixed points and periodic orbits. We also introduce a novel periodic orbit extraction and visualization algorithm that detects, for the first time, periodic orbits on surfaces. Furthermore, we describe the application of our periodic orbit detection and vector field simplification algorithms to engine simulation data demonstrating the utility of the approach. We apply our design system to vector field visualization by creating data sets containing periodic orbits. This helps us understand the effectiveness of existing visualization techniques. Finally, we propose a new streamline-based technique that allows vector field topology to be easily identified.     

Optimal placement of barrier coverage in heterogeneous bistatic radar sensor networks

Barrier Coverage is an important sensor deployment issue in many industrial, consumer and military applications.The barrier coverage in bistatic radar sensor networks has attracted many researchers recently. The Bistatic Radars (BR) consist of radar signal transmitters and radar signal receivers. The effective detection area of bistatic radar is a Cassini oval area that determined by the distance between transmitter and receiver and the predefined detecting SNR threshold. Many existing works on bistatic radar barrier coverage mainly focus on homogeneous radar sensor networks. However, cooperation among different types or different physical parameters of sensors is necessary in many practical application scenarios. In this paper, we study the optimal deployment problem in heterogeneous bistatic radar networks.The object is how to maximize the detection ability of bistatic radar barrier with given numbers of radar sensors and barrier’s length. Firstly, we investigate the optimal placement strategy of single transmitter and multiple receivers, and propose the patterns of aggregate deployment. Then we study the optimal deployment of heterogeneous transmitters and receivers and introduce the optimal placement sequences of heterogeneous transmitters and receivers. Finally, we design an efficient greedy algorithm, which realize optimal barrier deployment of M heterogeneous transmitters and N receivers on a L length boundary, and maximizing the detection ability of the barrier. We theoretically proved that the placement sequence of the algorithm construction is optimal deployment solution in heterogeneous bistatic radar sensors barrier. And we validate the algorithm effectiveness through comprehensive simulation experiments.

     

Projection-based partial periodic pattern mining for event sequences

Partial periodic pattern mining is one of the important issues in the field of data mining due to its practical applications. A partial periodic pattern consists of some periodic and non-periodic events in a specific period length, and is repeated with high frequency in an event sequence. In the past, a max-subpattern hit set algorithm was developed to discover partial periodic patterns, but its drawback is spending a large amount of time in calculating frequency counts from the redundant candidate nodes. In this study, we thus adopt an efficient encoding strategy to speed up the efficiency of processing period segments in an event sequence, and combined with the projection method to quickly find the partial periodic patterns in the recursive process. Finally, the experimental results show the superior performance of the proposed approach.     

Quantum prisoners’ dilemma under enhanced interrogation

In the quantum version of prisoners’ dilemma, each prisoner is equipped with a single qubit that the interrogator can entangle. We enlarge the available Hilbert space by introducing a third qubit that the interrogator can entangle with the other two. We discuss an enhanced interrogation technique based on tripartite entanglement and analyze Nash equilibria. We show that for tripartite entanglement approaching a W-state, we calculate the Nash equilibria numerically and show that they coincide with the Pareto-optimal choice where both prisoners cooperate. Upon continuous variation between a W-state and a pure bipartite entangled state, the game is shown to have a surprisingly rich structure. The role of bipartite and tripartite entanglement is explored to explain that structure. As an application, we consider an evolutionary game based on our quantum game with a network of agents on a square lattice with periodic boundary conditions and show that the strategy corresponding to Nash equilibrium completely dominates without placing any restrictions on the initial set of strategies.     

准周期积分函数控制在双管正激变换器中应用的研究

本文介绍了一种新型的控制策略准周期积分函数控制.分析准周期积分函数控制的基本原理,总结了准周期积分函数的特点并对其存在的问题加以改进.通过前馈补偿抑制负载扰动对输出电压产生的波动.把带前馈补偿的准周期积分函数控制应用在双管正激变换器中,分析其工作原理.通过仿真验证了该控制策略的有效性和可行性.     

Optimal distributed real-time scheduling of flexible manufacturing networks modeled as hybrid dynamical systems

The paper considers a class of flexible manufacturing networks. We employ hybrid dynamical systems to model such networks. The main and new achievement of the paper is that we propose a distributed implementable in real time scheduling rule such that the corresponding closed-loop system is stable and optimal. In stable systems the processes converge to periodic ones. The paper gives computing relations for the determination of the parameters of the periodic processes. These are very much suitable for planning purposes. On this basis—and this, we consider, is also a new, significant result—optimal arrival (demand) rates determination method is proposed. Quality characteristics are outlined. Field of application of hybrid dynamical approach for FMS scheduling is analyzed. The results open perspectives for MRP level task planning. Example and simulation results are presented.     

Nearly optimal perfectly periodic schedules

We consider the problem of scheduling a set of pages on a single broadcast channel using time-multiplexing. In a perfectly periodic schedule, time is divided into equal size slots, and each page is transmitted in a time slot precisely every fixed interval of time (the period of the page). We study the case in which each page i has a given demand probability , and the goal is to design a perfectly periodic schedule that minimizes the average time a random client waits until its page is transmitted. We seek approximate polynomial solutions. Approximation bounds are obtained by comparing the costs of a solution provided by an algorithm and a solution to a relaxed (non-integral) version of the problem. A key quantity in our methodology is a fraction we denote by , that depends on the maximum demand probability: . The best known polynomial algorithm to date guarantees an approximation of . In this paper, we develop a tree-based methodology for perfectly periodic scheduling, and using new techniques, we derive algorithms with better bounds. For small values, our best algorithm guarantees approximation of . On the other hand, we show that the integrality gap between the cost of any perfectly periodic schedule and the cost of the fractional problem is at least . We also provide algorithms with good performance guarantees for large values of . Received: December 2001 / Accepted: September 2002     

Discovery of Periodic Patterns in Spatiotemporal Sequences

In many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. For example, people wake up at the same time and follow more or less the same route to their work everyday. The discovery of hidden periodic patterns in spatiotemporal data could unveil important information to the data analyst. Existing approaches for discovering periodic patterns focus on symbol sequences. However, these methods cannot directly be applied to a spatiotemporal sequence because of the fuzziness of spatial locations in the sequence. In this paper, we define the problem of mining periodic patterns in spatiotemporal data and propose an effective and efficient algorithm for retrieving maximal periodic patterns. In addition, we study two interesting variants of the problem. The first is the retrieval of periodic patterns that are frequent only during a continuous subinterval of the whole history. The second problem is the discovery of periodic patterns, whose instances may be shifted or distorted. We demonstrate how our mining technique can be adapted for these variants. Finally, we present a comprehensive experimental evaluation, where we show the effectiveness and efficiency of the proposed techniques     

A theory of ultimately periodic languages and automata with an application to time granularity

In this paper, we develop a theory of regular ω-languages that consist of ultimately periodic words only and we provide it with an automaton-based characterization. The resulting class of automata, called ultimately periodic automata (UPA), is a subclass of the class of Büchi automata and inherits some properties of automata over finite words (NFA). Taking advantage of the similarities among UPA, Büchi automata, and NFA, we devise efficient solutions to a number of basic problems for UPA, such as the inclusion, the equivalence, and the size optimization problems. The original motivation for developing a theory of ultimately periodic languages and automata was to represent and to reason about sets of time granularities in knowledge-based and database systems. In the last part of the paper, we show that UPA actually allow one to represent (possibly infinite) sets of granularities, instead of single ones, in a compact and suitable to algorithmic manipulation way. In particular, we describe an application of UPA to a concrete time granularity scenario taken from clinical medicine.