Optimal time-varying load sharing for divisible loads

A load sharing problem involving the optimal load allocation of divisible loads in a distributed computing system consisting of N processors interconnected through a bus-oriented network is investigated. For a divisible lend, the workload is infinitely divisible so that each fraction of the workload can be distributed and independently computed on each processor. For the first time in divisible load theory, an analysis is provided in the case when the processor speed and the channel speed are time varying due to background jobs submitted to the distributed system with nonnegligible communication delays. A numerical method to calculate the average of the time-varying processor speed and the channel speed and an algorithm to find the optimal allocation of the workload to minimize the total processing finish time are proposed via a deterministic analysis. A stochastic analysis which makes use of Markovian queueing theory is introduced for the case when arrival and departure times of the background jobs are not known     

Equal allocation scheduling for data intensive applications

A new analytical model for equal allocation of divisible computation and communication load is developed. Equal allocation of load is attractive in multiple processor systems when real time information on processor and link capacity that is necessary for optimal scheduling is not available. The model includes a detailed accounting of solution reporting time. Equal allocation scheduling is compared with sequential scheduling and a new type of multi-installment scheduling. Aerospace applications include the processing of satellite imagery, radar, and sensor networks.     

控制器故障下的软件定义机载网络数据平面迁移策略

软件定义网络（SDN）为突破机载网络功能僵化所造成的瓶颈提供了新的契机。针对软件定义机载网络控制域内控制节点故障问题,提出一种基于时延和负载均衡的传输节点迁移策略,将故障控制节点所管控数据平面中的传输节点迁移至其他正常控制节点,恢复网络的正常管控。以迁移时延和负载均衡率为目标,建立迁移优化模型,提出基于时延和负载均衡的传输节点迁移算法,指导数据平面中的迁移动作,最终对两个性能目标进行综合权衡。实验结果表明,与距离就近迁移（DCM）策略和分布式逐跳（DHA）策略相比,所提策略在迁移时延和负载均衡率2个方面进行了合适的折中,避免出现迁移时延过大或控制节点负载失衡的情况,有效解决机载网络故障恢复问题。     

Optimal divisible job load sharing for bus networks

Optimal load allocation for load sharing a divisible job over N processors interconnected in bus-oriented network is considered. The processors are equipped with front-end processors. It is analytically proved, for the first time, that a minimal solution time is achieved when the computation by each processor finishes at the same time. Closed form solutions for the minimum finish time and the optimal data allocation for each processor are also obtained     

Wireless sensor networks: scheduling for measurement and data reporting

An optimal load allocation approach is presented for measurement and data reporting in wireless sensor networks with a single level tree network topology. The measurement problem investigated involves a measurement space, part of which can be sampled by each sensor. We seek to optimally assign sensors part of the measurement space to minimize reporting time and energy usage. Three representative measurement and reporting strategies are studied. This work is novel as it considers, for the first time, the measurement capacity of processors and assumes negligible computation time which is radically different from the traditional divisible load scheduling research to date. Aerospace applications include satellite remote sensing and monitoring and sensor networks deployed and monitored from the air.     

Distributed computation in linear networks: closed-form solutions

A linear network of communicating processors is analyzed. The processors in the network may or may not be equipped with front-end processors. The processing load originates either at the boundary or at the interior of the network. Closed-form solutions and computational techniques are presented for the above situations, to obtain time optimal distribution of processing loads on the processors. Some important results are proved analytically using the closed-form expressions     

Performance limits for processor networks with divisible jobs

Ultimate performance limits to the aggregate processing speed of networks of processors that are processing a divisible job are described. These take the form of either closed-form expressions or numerical procedures to calculate the equivalent processing speed of an infinite number of processors. These processors are interconnected in either a linear daisy chain with load origination from the network interior or a tree topology. The tree topology is particularly general as a natural way to perform load distribution in a professor network topology with cycles (e.g., hypercube, toroidal network) is to use an embedded spanning tree. Such limits on performance are important as they provide an ideal baseline against which to compare the performance of finite configurations of processors.     

基于多目标帝国竞争算法的进场排序与调度

为兼顾空管、机场、航司以及民众的不同诉求,提出了基于多目标帝国竞争算法的进场排序与调度方法,达到平衡交通需求与进场管理的目的。首先,借鉴机器调度领域研究成果,梳理与精简进场排序与调度的评价指标,并结合运行约束构建多目标进场排序与调度模型。接着,引入非支配排序,设计多目标帝国竞争算法,给出衡量帕累托解集优劣的评价指标。最后,采用通用数据集与长沙黄花机场实际运行数据实施案例进行仿真与验证。结果表明：提出的多目标帝国竞争算法,相对于带精英策略的非支配排序遗传算法以及多目标模拟退火算法而言,解集更占支配地位、分布更均匀、收敛性更好,求解的效率也更高;提出的算法能有效实现进场排序与调度,即便以标准间隔的1.8倍实施仿真,总延误时间、总飞行时间和最大飞行时间,相对于实际运行分别降低了41.2%、11.4%和8.6%。     

Signature search time evaluation in flat file databases

For the first time, divisible load scheduling theory is used to solve for the expected time for searching for both single and multiple signatures in certain multiple processor database architectures. The target architectures examined for illustrative purposes are linear daisy chains and single level tree networks with single and multiple installment load distribution. The use of divisible load modeling and analysis yields elegant expressions for expected search time.     

Extracting multiple frequencies from phase-only data

The problem of extracting multiple frequencies from phase-only data is addressed. Multiple frequency estimation is accomplished by reconstructing the Fourier transform of the complex-valued time signal and then finding peaks in the frequency domain. We present a set of conditions under which a discrete-time complex sequence can be completely specified by its phase-only information. Two candidate multiple frequency estimation schemes are introduced, one based on a closed-form least-squares inverse, the other an iterative reconstruction algorithm. The uniqueness of the closed-form solution and the convergence of the iterative scheme have been proven under certain conditions. Several examples are given, including the case where the phase is quantized as would happen in an analog-to-digital (A/D) converter. Extensions to the multidimensional case, and to the case of real-part only reconstruction are straightforward.     

人工智能在卫星任务规划中的应用

智能规划与调度是实现卫星自主规划其飞行任务的关键。将人工智能方法应用于卫星的任务规划,以执行对地观测任务为例,将任务规划问题归于组合优化问题,建立了相应的数学模型,并应用Hopfield神经网络算法进行求解,结果表明,该方法可用于单个仪器的任务规划。     

局内电梯调度问题与竞争算法

经典的优化理论大多是在已知条件不变的基础上给出最优方案 (即最优解 ) ,其最优性在条件发生变化时就会失去。局内问题与竞争算法则是针对特定的优化问题来研究这样的方法 ,它在变化因素的每一个特例中都能给出一个方案 ,使得这一方案所得到的解离最优方案给出的解总在一定的比例之内。本文首先提出了局内电梯调度问题 ,设计了解决该问题的两个不同的竞争算法 ,并证明了这两个竞争算法的竞争比分别为k+2 和n-k +1,其中k为电梯的个数 ,n为楼层数。     

片间综合化互连时间触发通信调度方法

未来先进的分布式综合化航空电子系统需要实现跨越计算体系结构的信息综合,对微小型智能器件间的综合化互连提出要求。通过构建一种具有开放式接口的芯片间综合化互连结构,提出一种相应的时间触发（TT）通信调度方法。首先建立片间综合化互连模型和时间触发流量传输模型,给出负载均衡的选径方法;随后依据传输路径中各级节点各流量的发送时间偏移量计算流量传输的等待时间可行值,利用遗传算法优化调整各芯片发送端口的调度表相位,更新各流量在发送端口的时间偏移量,缩短最坏情况下的最大等待时间,得到具有全局优化意义的时间触发调度表。与使用Yices等SMT形式化求解器的TT调度表生成方法相比,本方法不会出现长时间不停机而无法判定的问题,且不论对于对称或非对称结构,案例研究表明本方法的可调度规模至少增加30%。此外,以流量传输等待时间占周期的比例作为归一化的传输延迟度量,与既有的基于特征任务的调度方法相比,案例研究表明本方法得到的传输延迟最多仅为后者的2%。     

一种基于偏好MOEA的卫星地面站资源多目标优化算法

随着中国航天事业的发展,卫星地面站资源匮乏问题日益突出,需要对其进行统筹优化使用。因此,卫星地面站资源规划问题得到了广泛关注。在分析问题特点的基础上,对用户规划结果的偏好信息进行建模表达,建立了涵盖用户偏好的多目标数学规划模型,提出了基于偏好多目标进化算法的卫星地面站资源规划算法。为了进一步提升算法性能,设计了基于领域知识的启发式策略,包括：任务扩充策略、冲突消解策略以及任务缩减策略等。实验结果表明,与现有算法相比,用户偏好信息的引入能有效提升问题求解针对性,在IGD-CF （Inverted Generational Distance based on Composite Front）指标上取得了更好的效果。     

A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets

The problem of generating optimal paths for curvature-constrained unmanned aerial vehicles （UAVs） performing surveillance of multiple ground targets is addressed in this paper. UAVs are modeled as Dubins vehicles so that the constraints of UAVs＇ minimal turning radius can be taken into account. In view of the effective surveillance range of the sensors equipped on UAVs, the problem is formulated as a Dubins traveling salesman problem with neighborhood （DTSPN）. Considering its prohibitively high computational complexity, the Dubins paths in the sense of terminal heading relaxation are introduced to simplify the calculation of the Dubins distance, and a boundary-based encoding scheme is proposed to determine the visiting point of every target neighborhood. Then, an evolutionary algorithm is used to derive the optimal Dubins tour. To further enhance the quality of the solutions, a local search strategy based on approximate gradient is employed to improve the visiting points of target neighborhoods. Finally, by a minor modification to the individual encoding, the algorithm is easily extended to deal with other two more sophisticated DTSPN variants （multi-UAV scenario and multiple groups of targets scenario）. The performance of the algorithm is demonstrated through comparative experiments with other two state-of-the-art DTSPN algorithms identified in literature. Numerical simulations exhibit that the algorithm proposed in this paper can find high-quality solutions to the DTSPN with lower computational cost and produce significantly improved performance over the other algorithms.     

一类适用于多星测控调度问题的模型及求解算法

多星测控调度是一个复杂的NP—hard问题,其模型和算法的研究一直是求解的关键和难点。本文从组合优化角度对问题进行描述,建立了多星测控调度问题的数学模型,并利用启发式调度算法予以求解。最后,将算法应用于一个6站10星的调度问题,进行了数值仿真研究。仿真表明,算法能在较短时间内求得任务支持率高且资源使用相对均衡的解,具有较好的寻优能力。     

光纤通道交换网络WRR实时调度算法分析

 随着综合航电系统的发展,1553B总线已经不能满足发展的需要,光纤通道交换式网络作为新一代高性能网络通信协议被引入到航电系统中,其性能指标与整个航电系统的总体指标有着密切的关系.为了解决系统消息实时发送的问题,研究了光纤通道交换网络实时条件下加权轮询调度算法的通信性能,利用随机Petri网对光纤通道交换网络的调度过程进行了建模,通过对模型的仿真和分析,得到了数据传输量及传输时限变化时系统网络负载、延迟时间、超时消息所占比例等重要性能指标,并分析了调度算法的性能.仿真结果证明光纤通道交换式网络具有高速稳定性,加权轮询调度算法能够满足消息传输的实时性、公平性要求.     

基于混合蚁群算法的柔性模糊车间作业调度

采用蚁群算法作为全局搜索算法,提出一种混合搜索策略,用于求解柔性模糊Job Shop调度问题.根据模糊Job Shop调度问题解的特性,提出基于     

基于人工蜂群算法的航空电子系统负载均衡研究

针对航空电子系统中存在的任务请求多、资源利用率低、负载不均衡等问题,通过基于人工蜂群算法,设计并实现航空电子系统负载平衡机制.建立航空电子系统负载均衡数学模型,通过研究人工蜂群算法的四个阶段来求解航空电子系统的负载均衡,将待分配的计算任务指派给当前负载最轻的处理器.实验结果表明该算法负载均衡效果好.     

相控阵雷达长时跟踪波束调度与波形优化策略

针对相控阵雷达多目标跟踪波束调度和波形参数优化控制的问题，本文提出了一种基于马尔可夫决策过程（MDP）的相控阵雷达跟踪波束调度与波形参数优化策略，该方法以无迹卡尔曼滤波（UKF）算法为基础来估计目标的状态。首先将本文的序列决策问题建模为马尔可夫决策过程，定义了资源的效费比和长期回报率，然后与当前实际跟踪误差综合考虑作为MDP的回报函数，进而给出了调度的优化模型，最后将长时决策问题转化为动态规划算法结构进行求解，并且提出了一种并行混合遗传粒子群优化算法来求解各决策时刻的最优策略。仿真结果表明了长时策略的先进性以及寻优算法的优越性，与传统的短时策略相比，跟踪精度可提高11.17%。