Fitting multidimensional data using gradient penalties and the sparse grid combination technique

Sparse grids, combined with gradient penalties provide an attractive tool for regularised least squares fitting. It has earlier been found that the combination technique, which builds a sparse grid function using a linear combination of approximations on partial grids, is here not as effective as it is in the case of elliptic partial differential equations. We argue that this is due to the irregular and random data distribution, as well as the proportion of the number of data to the grid resolution. These effects are investigated both in theory and experiments. As part of this investigation we also show how overfitting arises when the mesh size goes to zero. We conclude with a study of modified “optimal” combination coefficients who prevent the amplification of the sampling noise present while using the original combination coefficients.     

动态负载均衡算法在校园网格中的应用

校园网格能有效消除信息孤岛,实现我国高校的计算资源和信息资源的有效共享。一个亟待解决的问题是在校园网格环境下,服务器节点响应能力低下。目前已提出多种技术与方案以解决并提高校园网格的服务器节点的响应能力,负载均衡技术就是一种全新的技术。本文根据校园网格的特点和影响负载均衡的因素,对基于校园网格的负载均衡技术进行了分析和探讨,并提出一种动态负载均衡算法。     

Dynamic grid load sharing with adaptive dissemination protocols

Scheduling in large scale dynamic grids comprising eclectic collections of resources is increasingly difficult. Autonomous resource neighborhoods may wish to determine the level of grid offered load that they can or will accept; different sites may wish to attract different amounts of load, to satisfy some desired property within a grid economy. This changes the traditional notion of load sharing, which generally assumes that the desired equilibrium should be an equal distribution of load across all participating machines, because they are under the jurisdiction of a single site, and therefore more likely to implement one common policy. In large-scale grids, nodes and neighborhoods should instead get a portion of the load that best matches their local policies for supporting and admitting grid jobs. This article describes information dissemination protocols that can distribute load in this way, without using load rebalancing through job migration, which is more difficult and costly in large-scale heterogeneous grids. Essentially, nodes adjust their advertising rates and aggressiveness to influence where jobs get scheduled. We report experimental results with example resource configurations in which each resource neighborhood determines its ideal grid load and disseminates accordingly. In turn, each neighborhood attracts the requisite amount of resource requests from the grid. Moreover, performance does not degrade: overall query satisfaction rates are within 9% of both adaptive dissemination protocols that use static adaptation policies, and static dissemination protocols that may be custom-tailored to specific resource and load distributions.     

基于网格计算的混合负载均衡策略

根据分布式系统的静态和动态负载均衡策略的优缺点,提出了在网格计算环境下的混合负载均衡策略.为了让网络中节点在网格计算环境中有效地执行需要大量计算的复杂任务,提出了用来评估节点效率的函数,并结合模拟实验证实了在此函数下算法的优越性.     

网格环境下负载平衡研究

随着Internet上网络应用和网格技术的飞速发展,负载平衡的研究和发展面临着新的机遇和挑战。这些新的技术、概念和方法提供了更新的环境来研究和发展负载平衡系统;结合网格和负载平衡两种技术,依据开放网格服务体系、网格数据服务接口模型和网格服务资源框架,研究了在网格环境下的负载平衡实施,提出了一个负载平衡系统的体系结构模型。针对负载平衡中的两个关键问题——信息分发收集过程和有效的负载估计算法做了详细的论述。     

山区季节性负荷用户接入新体系研究

遵循"安全、可靠、经济、合理"的原则,建立福建山区用户接入的一般体系。通过分析福建山区中低压配电网特点和福建山区负荷特性,结合用户接入的一般体系,运用负荷距理论,提出适用于福建山区季节性负荷的用户接入体系,以缓解季节性负荷用户带来的"低电压"问题。     

When smart grid meets PHEVs: a smart load distribution mechanism in smart grid

Along with the increasing popularity of electric vehicles caused by economic and environmental incentives, the penetration of plug-in hybrid electric vehicles (PHEVs) poses a great threat to the power grid, especially to the aggregated load in the power system. Motivated by this observation, in this paper, we analyze the impact of large-scale usage of PHEVs and address the load distribution problem by solving a decentralized optimization problem and smoothening the peak load with pricing strategies in the power grid. We also investigate the influence of charging time and charging mode on load distribution, as the charging price varies with the changes of these two factors. Our simulation study on PJM’s data warehouse shows that the proposed strategies can well smooth the peak load by pricing on the charging time and mode. The results also indicate that our strategies always distribute the load in a smoother manner at a smaller load fluctuation compared with other schemes (e.g., First Come First Service and PMCS) and thus improving the stability and reliability of the power grid.     

A hybrid load balancing policy underlying grid computing environment

In recent years, network bandwidth and quality has been drastically improved, even much faster than the enhancement of computer performance. The various communication and computing tasks in the fields such as telecommunication, multimedia, information technology, and construction simulation, can be integrated and applied in a distributed computing environment nowadays. However, as the demands of many researches for computing resources gradually grow, Grid Computing integrated with a distributed computing environment and the Internet (network) has gained more attention. The so-called Grid Computing is to utilize the idle computing resources (nodes) on the network to facilitate the execution of complicated tasks that require large-scale computing. In other words, the composition of Grid resources is dynamic and varies with time. Thus, when selecting nodes for executing a task, the dynamic of the nodes in the Grid must be considered, and to exploit the effectiveness of the resources, they have to be properly selected according to the properties of the task. This study proposed a hybrid load balancing policy which integrated static and dynamic load balancing technologies to assist in the selection for effective nodes. In addition, if any selected node can no longer provide resources, it can be promptly identified and replaced with a substitutive node to maintain the execution performance and the load balancing of the system.     

Coordinated load management in Peer-to-Peer coupled federated grid systems

This paper proposes a coordinated load management protocol for Peer-to-Peer?(P2P) coupled federated Grid systems. The participants in the system, such as the resource providers and the consumers who belong to multiple control domains, work together to enable a coordinated federation. The coordinated load management protocol embeds a logical spatial index over a Distributed Hash Table?(DHT) space for efficient management of the coordination objects; the DHT-based space serves as a kind of decentralized blackboard system. We show that our coordination protocol has a message complexity that is logarithmic to the number of nodes in the system, which is significantly better than existing broadcast based coordination protocols. The proposed load management protocol can be applied for efficiently coordinating resource brokering services of distributed computing systems such as grids and PlanetLab. Resource brokering services are the main components that control the way applications are scheduled, managed and allocated in a distributed, heterogeneous, and dynamic Grid computing environments. Existing Grid resource brokers, e-Science application work-flow schedulers, operate in tandem but still lack a coordination mechanism that can lead to efficient application schedules across distributed resources. Further, lack of coordination exacerbates the utilization of various resources (such as computing cycles and network bandwidth). The feasibility of the proposed coordinated load management protocol is studied through extensive simulations.     

A bipartite model for load balancing in grid computing environments

In this paper, a bipartite model for load balancing (LB) in grid computing environments, called Transverse viewpoint-based Bi-Tier model (TBT), is proposed. TBT can efficiently eliminate topology mismatching between overlay- and physical-networks during the load transfer process. As an implementation of TBT, a novel LB policy called M²ON (Min-cost and Max-flow Channel based Overlay Network) is presented. In M²ON, the communication capability is denoted as M²C (Min-cost and Max-flow Channel) which is obtained using a Labeled Tree Probing (LTP) method. The computing capacity is denoted as the Idle Factor (IF) which is obtained from the semantic overlay. The higher- and lower-level characteristics are combined into an Integrated Impacting Factor (IIF) using a Double Linear Inserting (DLI) function. Based on IIF, optimal topology matching can be achieved in the LB process. Extensive experiments and simulations have been performed and will be discussed. The results show that M²ON achieves more accurate topology matching with a minimum increment in the overall locating time yet achieving higher system performance as a whole.     

Towards a hybrid load balancing policy in grid computing system

Grid computing has become conventional in distributed systems due to technological advancements and network popularity. Grid computing facilitates distributed applications by integrating available idle network computing resources into formidable computing power. As a result, by using efficient integration and sharing of resources, this enables abundant computing resources to solve complicated problems that a single machine cannot manage. However, grid computing mines resources from accessible idle nodes and node accessibility varies with time. A node that is currently idle, may become occupied within a second of time and then be unavailable to provide resources. Accordingly, node selection must provide effective and sufficient resources over a long period to allow load assignment. This study proposes a hybrid load balancing policy to integrate static and dynamic load balancing technologies. Essentially, a static load balancing policy is applied to select effective and suitable node sets. This will lower the unbalanced load probability caused by assigning tasks to ineffective nodes. When a node reveals the possible inability to continue providing resources, the dynamic load balancing policy will determine whether the node in question is ineffective to provide load assignment. The system will then obtain a new replacement node within a short time, to maintain system execution performance.     

计算网格中动态负载平衡的分布调度模式

网格计算下对资源进行有效的管理和调度可以提高系统的利用率.在对现有若干调度方法的研究和分析基础上,针对计算网格中的负载平衡问题,提出了一种分布式网格作业调度模型,并给出相关算法.算法通过建立主从模式的负载信息收集机制,提供给节点全局负载信息,加速重负载节点的负载转移速度.通过有效的负载平衡模式,解决资源调度中负载平衡及其可靠性问题.     

Predict task running time in grid environments based on CPU load predictions

A good running time prediction of tasks is very helpful and important for job scheduling and resource management in grid systems. In this paper, we present a running time prediction method for grid tasks based on our previous work, which is a novel CPU load prediction method. In order to eliminate the interference of other factors, such as memory accessing, network performance, and fluctuation of competing CPU load and so on, we produce a simulation to test and evaluate our prediction method. In this simulation we use more than 10,000 randomized test cases run on load traces sampled from 39 different machines. The simulation results are excellent and demonstrate that our running time prediction of grid tasks outperforms significantly that of a widely existing prediction method.     

配电网感性负荷自动补偿装置的网格化研究

提高自动补偿装置效率,处理好谐波增大等问题,可以提高配电网的稳定性,为此,设计了一种新型自动补偿装置.该装置由两部分组成,首先通过并联电抗器补偿线路中的电容性电流,维持感性无功功率和容性无功功率的平衡关系,然后由网格化自动补偿器对配电网的输入电流进行频谱生成并对频谱进行分析计算,根据不同的故障类型选择不同的处理方式,以...     

A hybrid policy for fault tolerant load balancing in grid computing environments

Due to the emergence of grid computing over the Internet, there is a need for a hybrid load balancing algorithm which takes into account the various characteristics of the grid computing environment. Hence, this research proposes a fault tolerant hybrid load balancing strategy namely AlgHybrid_LB, which takes into account grid architecture, computer heterogeneity, communication delay, network bandwidth, resource availability, resource unpredictability and job characteristics. AlgHybrid_LB juxtaposes the strong points of neighbor-based and cluster based load balancing algorithms. Our main objective is to arrive at job assignments that could achieve minimum response time and optimal computing node utilization. Major achievements include low complexity of proposed approach and drastic reduction of number of additional communications induced due to load balancing. A simulation of the proposed approach using Grid Simulation Toolkit (GridSim) is conducted. Experimental results show that the proposed algorithm performs very well in a large grid environment.     

Ergonomic effects of load carriage on energy cost of gradient walking

We examined the effects of load on the energy cost of walking (C(w)), being defined as the ratio of the 2-min steady-state oxygen consumption to the speed, and economical speed (ES) during level and gradient walking. Ten men walked on a treadmill at various speeds with and without a load on their back at 0% and +/-5% gradients. Significantly lower C(w) values were observed only when the load was carried on the back during level walking at slower speeds. The ES was significantly decreased by less than 5% when the load was carried on the back. Significant gradient differences were also observed in the ES in the load and no load conditions. These results would be applicable to a wider range of occupational and leisure tasks.     

考虑负荷类型的配电网改进牛顿潮流算法

针对传统牛顿法存在计算量大、效率低,且当负荷类型不再是恒功率时其迭代次数与时间会明显增加等问题,提出了一种改进的牛顿潮流法。该算法考虑了负荷类型,将恒功率、恒电流和恒阻抗结合起来组成ZIP负荷模型,采用矩阵分裂以及矩阵求逆运算的松弛方法,使求解过程简单、快捷,有效地提高了算法效率,削弱了负荷类型变化对迭代次数以及迭代时间的影响。采用33节点系统测试比较了算法的迭代次数和迭代时间,证实了算法的有效性;并通过潮流计算结果分析了负荷类型对系统电压的影响,结果表明,恒阻抗负荷比例的增加有利于提高系统节点电压。     

Equivalent input disturbance-based load frequency control for smart grid with air conditioning loads

Integrating intermittent wind power into power systems results in low or zero inertia,threat-ening their frequency stability.To accommodate intermittent generat...