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.     

Designing a resource broker for heterogeneous grids

Grids provide uniform access to aggregations of heterogeneous resources and services such as computers, networks and storage owned by multiple organizations. However, such a dynamic environment poses many challenges for application composition and deployment. In this paper, we present the design of the Gridbus Grid resource broker that allows users to create applications and specify different objectives through different interfaces without having to deal with the complexity of Grid infrastructure. We present the unique requirements that motivated our design and discuss how these provide flexibility in extending the functionality of the broker to support different low‐level middlewares and user interfaces. We evaluate the broker with different job profiles and Grid middleware and conclude with the lessons learnt from our development experience. Copyright © 2007 John Wiley & Sons, Ltd.     

On the performance-driven load distribution for heterogeneous computational grids

Load balancing has been a key concern for traditional multiprocessor systems. The emergence of computational grids extends this challenge to deal with more serious problems, such as scalability, heterogeneity of computing resources and considerable transfer delay. In this paper, we present a dynamic and decentralized load balancing algorithm for computationally intensive jobs on a heterogeneous distributed computing platform. The time spent by a job in the system is considered as the main issue that needs to be minimized. Our main contributions are: (1) Our algorithm uses site desirability for processing power and transfer delay to guide load assignment and redistribution, (2) Our transfer and location policies are a combination of two specific strategies that are performance driven to minimize execution cost. These two policies are the Instantaneous Distribution Policy (IDP) and the Load Adjustment Policy (LAP), (3) The communication overhead involved in information collection is reduced using mutual information feedback. The simulation results show that our proposed algorithm outperforms conventional approaches over a wide range of system parameters.     

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.     

An algorithm for optimal decentralized regulation of linear quadratic interconnected systems

This paper provides a method for designing ‘optimal’ decentralized controls for linear time-invariant interconnected systems. The optimality is with respect to a quadratic cost criterion. An algorithm is proposed which uses the method of feasible directions and provides a local minimum while ensuring, at each iteration, the stability of the overall system.     

一种异构云环境下的负载均衡算法

针对动态负载均衡算法在异构云环境中的任务迁移次数过多的问题,提出了一种最小化任务迁移次数的动态负载均衡(MMLB)算法。MMLB算法通过自适应阈值对虚拟机进行分组、任务选择算法最小化任务迁移的次数、任务调度算法优化任务分配实现了任务的再分配。将MMLB与WRR、HBBLB、LBF算法进行实验对比分析,MMLB算法在Makespan、平均任务响应时间、负载不均衡度等评价指标上表现更优,并且有效降低了任务迁移的次数。实验结果验证了MMLB算法的可行性和有效性。     

Rule-driven service coordination middleware for scientific applications

With the proliferation of Web services, scientific applications are more and more designed as temporal compositions of services, commonly referred to as workflows. To address this paradigm shift, different workflow management systems have been proposed. While their efficiency has been established over centralized static systems, it is questionable over decentralized failure-prone platforms.Scientific applications recently started to be deployed over large distributed computing platforms, leading to new issues, like elasticity, i.e., the possibility to dynamically refine, at runtime, the amount of resources dedicated to an application. This raised again the demand for new programming models, able to express autonomic self-coordination of services in a dynamic platform.Nature-inspired, rule-based computing models recently gained a lot of attention in this context. They are able to naturally express parallelism, distribution, and autonomic adaptation. While their high expressiveness and adequacy for this context has been established, such models severely suffer from a lack of proof of concepts. In this paper, we concretely show how to leverage such models in this context. We focus on the design, the implementation and the experimental validation of a chemistry-inspired scientific workflow management system.     

异构Hadoop集群下的负载自适应反馈调度策略

随着基于Hadoop平台的大数据技术的不断发展和实践的深入,Hadoop YARN资源调度策略在异构集群中的不适用性越发明显。一方面,节点资源无法动态分配,导致优势节点的计算资源浪费、系统性能没有充分发挥;另一方面,现有的静态资源分配策略未考虑作业在不同执行阶段的差异,易产生大量资源碎片。基于以上问题,提出了一种负载自适应调度策略。监控集群执行节点和提交作业的性能信息,利用实时监控数据建模、量化节点的综合计算能力,结合节点和作业的性能信息在调度器上启动基于相似度评估的动态资源调度方案。优化后的系统能够有效识别集群节点的执行能力差异,并根据作业任务的实时需求进行细粒度的动态资源调度,在完善YARN现有调度语义的同时,可作为子级资源调度方案架构在上层调度器下。在Hadoop 2.0上实现并测试该策略,实验结果表明,作业的自适应资源调度策略显著提高了资源利用率,集群并发度提高了2到3倍,时间性能提升了近10%。     

Semi‐decentralized nonlinear cooperative control strategies for a network of heterogeneous autonomous underwater vehicles

In this paper, we develop nonlinear distributed or semi‐decentralized cooperative control schemes for a team of heterogeneous autonomous underwater vehicles (AUVs). The objective is to have the network of AUVs follow a desired trajectory, while the agents maintain a desired formation when there is a virtual leader whose position information is only available and known to a very small subset of the agents. The virtual leader does not receive any feedback and information from the other agents and the agents only communicate with their nearest neighboring agents. It is assumed that the model parameters associated with each vehicle/agent is different, although the order of the agents is the same. The developed and proposed nonlinear distributed cooperative control schemes are based on the dynamic surface control methodology for a network of heterogeneous autonomous vehicles with uncertainties. The development and investigation of the dynamic surface control methodology for a team of cooperative heterogenous multi‐agent nonlinear systems is accomplished for the first time in the literature. Simulation results corresponding to a team of six AUVs are provided to demonstrate and illustrate the advantages and superiority of our proposed cooperative control strategies as compared to the methods that are available in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

A novel decomposition and coordination algorithm for complex networks and its application to power grids

To analyze and control complex networks effectively, this paper puts forward a new kind of scheme, which takes control separately in each area and can achieve the network＇s coordinated optimality. The proposed algorithm is made up of two parts： the first part decomposes the network into several independent areas based on community structure and decouples the information flow and control power among areas; the second part selects the center nodes from each area with the help of the control centrality index. As long as the status of center nodes is kept on a satisfactory level in each area, the whole system is under effective control. Finally, the algorithm is applied to power grids, and the simulations prove its effectiveness.     

A process partitioning technique for constructing decentralized web service compositions

Web service compositions have been widely applied in different applications. A service composition is usually implemented in either a centralized or decentralized manner. Compared with the centralized service composition, the decentralized composition has no central control component, and components interact with each other directly, thereby achieving better performance. Process partitioning is a technique to divide a process into multiple parts and has been shown that it can be successfully applied to decentralizing process-driven service compositions. This paper proposes a new process partitioning technique for constructing decentralized service compositions. The proposed technique, which is based on typed digraphs and a graph transformation technique, is used for exploring available process partitioning solutions. For applications, this paper discusses the topology and interaction features about the partitioning solutions and summarizes a ranking method for them. Three experiments are conducted to evaluate the proposed methods in this paper. Experimental results show that the proposed methods can be applied in constructing decentralized service compositions effectively. In addition, the results also show that the decentralized compositions can have lower average response times and higher throughputs than the corresponding centralized compositions in the experiments.     

A distributed evolutionary approach for multisite mapping on grids

In this paper attention is concentrated on the mapping of computationally intensive multi‐task applications onto shared computational grids. This problem, already known to be as NP‐complete in parallel systems, becomes even more arduous in such environments. To find a near‐optimal mapping solution a parallel version of a Differential Evolution algorithm is presented and evaluated on different applications and operating conditions of the grid nodes. The purpose is to select for a given application the mapping solutions that minimize the greatest among the time intervals which each node dedicates to the execution of the tasks assigned to it. The experiments, effected with applications represented as task interaction graphs, demonstrate the ability of the evolutionary tool to perform multisite grid mapping, and show that the parallel approach is more effective than the sequential version both in enhancing the quality of the solution and in the time needed to get it. Copyright © 2011 John Wiley & Sons, Ltd.     

Brokering of risk‐aware service level agreements in grids

Service level agreements (SLAs) are facilitators for widening the commercial uptake of Grid technology. They provide explicit statements of expectation and obligation between service consumers and providers. However, without the ability to assess the probability that an SLA might fail, commercial uptake will be restricted, since neither party will be willing to agree. Therefore, risk assessment mechanisms are critical to increase confidence in Grid technology usage within the commercial sector. This paper presents an SLA brokering mechanism with risk assessment support, which evaluates the probability of SLA failure. WS‐Agreement and risk metrics are used to facilitate SLA creation between service consumers and providers within a typical Grid resource usage scenario. An evaluation is conducted to examine risk models, the performance of the broker's implementation as well as a comparison of its capabilities against similar SLA‐based solutions from the literature. Copyright © 2011 John Wiley & Sons, Ltd.     

A descent anderson-moore algorithm for optimal decentralized control

A convergent version of the Anderson-Moore algorithm for the optimal output feedback problem is applied to a class of optimal decentralized control problems. The algorithm is based on a positive definite approximation of the second-order Taylor-series expansion of the loss function. Numerical results show that the algorithm performs favourably when compared with the method of Geromel and Bernussou (1979) (Automatica, 15, 489) and with variable metric function minimization techniques.     

大规模CFD多区结构网格任务负载平衡算法

针对现有负载平衡算法的适应度低、可扩展性差、通信开销度量不准确的缺陷, 提出一种大规模CFD多区结构网格任务负载平衡算法。通过对网格块的分割、网格块之间的组合映射、进程上网格计算量的调整来实现并行CFD任务负载平衡。实验结果表明, 该算法既适应同构平台也适应异构平台, 既适应网格块数多于进程数的情况也适应网格块数少于进程数的情况, 该算法可使得整个计算空间分配到各进程上的计算量负载平衡, 同时使得各进程间的最大通信开销最小。     

异构信息系统下安全策略协同的设计与形式化语言描述

在异构的信息系统中,为了保障信息的安全,都会采用相应强度的访问控制技术和策略。为了在异构信息系统之间,能够有效地共享资源,就需要在异构系统间实现安全策略的协同。给出了一个基于票据的安全策略协同模型,用形式化的语言对其进行了描述,并完成了对票据权限的计算     

一种基于自动回归的改进网格主机负载预测模型

提出了一种基于自动回归（AR）改进的主机负载预测模型,它不仅具有AR模型本身的计算成本小、预测性能稳定的优点,还对AR模型只对未来某个固定时间段的负载预测进行了改进,使之能根据作业的预测执行时间进行主机负载动态预测,同时该模型还充分体现了主机负载变化的自相似性和长期依赖性。实验结果表明,该模型达到了预期的效果。     

一种面向随机性负载的计算网格资源预留定价策略

针对传统预留机制对本地任务服务质量造成的负面影响,提出了基于预留收益与损失均衡的资源预留机制。首先,基于本地任务相关统计特性利用概率论方法,给出并证明了一段时间内本地任务执行时间之和的概率分布函数。然后,在资源提供者的效用中考虑本地任务可能带来的损失,求解出了为保障本地任务服务质量的最低资源价格。实验结果表明,提出的预留机制能有效保障本地任务的服务质量,提高资源利用率、降低任务拒绝率。     

A refinement-tree based partitioning method for dynamic load balancing with adaptively refined grids

The partitioning of an adaptive grid for distribution over parallel processors is considered in the context of adaptive multilevel methods for solving partial differential equations. A partitioning method based on the refinement-tree is presented. This method applies to most types of grids in two and three dimensions. For triangular and tetrahedral grids, it is guaranteed to produce connected partitions; no other partitioning method makes this guarantee. The method is related to the OCTREE method and space filling curves. Numerical results comparing it with several popular partitioning methods show that it computes partitions in an amount of time similar to fast load balancing methods like recursive coordinate bisection, and with mesh quality similar to slower, more optimal methods like the multilevel diffusive method in ParMETIS.     

Price-driven coordination method for solving plant-wide MPC problems

In large-scale model predictive control (MPC) applications, such as plant-wide control, two possible approaches to MPC implementation are centralized and decentralized MPC schemes. These represent the two extremes in the “trade-off” among the desired characteristics of an industrial MPC system, namely accuracy, reliability and maintainability. To achieve optimal plant operations, coordination of decentralized MPC controllers has been identified as both an opportunity and a challenge. Typically, plant-wide MPC problem can be formulated as a large-scale quadratic program (QP) with linking equality constraints. Such problems can be decomposed and solved with the price-driven coordination method and on-line solutions of these structured large-scale optimization problems require an efficient price-adjustment strategy to find an “equilibrium price”. This work develops an efficient price-adjustment algorithm based on Newton’s method, in which sensitivity analysis and active set change identification techniques are employed. With the off-diagonal element abstraction technique and the enhanced priced driven coordination algorithm, a coordinated, decentralized MPC framework is proposed. Several case studies show that the proposed coordination-based decentralized MPC scheme is an effective approach to plant-wide MPC applications, which provides a high degree of reliability and accuracy at a reasonable computational load.