Adaptive Executions of Multi-Physics Coupled Applications on Batch Grids

Long running multi-physics coupled parallel applications have gained prominence in recent years. The high computational requirements and long durations of simulations of these applications necessitate the use of multiple systems of a Grid for execution. In this paper, we have built an adaptive middleware framework for execution of long running multi-physics coupled applications across multiple batch systems of a Grid. Our framework, apart from coordinating the executions of the component jobs of an application on different batch systems, also automatically resubmits the jobs multiple times to the batch queues to continue and sustain long running executions. As the set of active batch systems available for execution changes, our framework performs migration and rescheduling of components using a robust rescheduling decision algorithm. We have used our framework for improving the application throughput of a foremost long running multi-component application for climate modeling, the Community Climate System Model (CCSM). Our real multi-site experiments with CCSM indicate that Grid executions can lead to improved application throughput for climate models.

Resource Usage Monitoring in Clouds

Monitoring of infrastructural resources in clouds plays a crucial role in providing application guarantees like performance, availability, and security. Monitoring is crucial from two perspectives - the cloud-user and the service provider. The cloud user’s interest is in doing an analysis to arrive at appropriate Service-level agreement (SLA) demands and the cloud provider’s interest is to assess if the demand can be met. To support this, a monitoring framework is necessary particularly since cloud hosts are subject to varying load conditions. To illustrate the importance of such a framework, we choose the example of performance being the Quality of Service (QoS) requirement and show how inappropriate provisioning of resources may lead to unexpected performance bottlenecks. We evaluate existing monitoring frameworks to bring out the motivation for building much more powerful monitoring frameworks. We then propose a distributed monitoring framework, which enables fine grained monitoring for applications and demonstrate with a prototype system implementation for typical use cases.

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application's throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based lookahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from Amazon AWS IaaS public cloud. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

Thermal building simulation using the UKCP09 probabilistic climate projections

This article investigates how to use UK probabilistic climate-change projections (UKCP09) in rigorous building energy analysis. Two office buildings (deep plan and shallow plan) are used as case studies to demonstrate the application of UKCP09. Three different methods for reducing the computational demands are explored: statistical reduction (Finkelstein-Schafer [F-S] statistics), simplification using degree-day theory and the use of metamodels. The first method, which is based on an established technique, can be used as reference because it provides the most accurate information. However, it is necessary to automatically choose weather files based on F-S statistic by using computer programming language because thousands of weather files created from UKCP09 weather generator need to be processed. A combination of the second (degree-day theory) and third method (metamodels) requires only a relatively small number of simulation runs, but still provides valuable information to further implement the uncertainty and sensitivity analyses. The article also demonstrates how grid computing can be used to speed up the calculation for many independent EnergyPlus models by harnessing the processing power of idle desktop computers. © 2011 International Building Performance Simulation Association (IBPSA).

一种网格环境下的密码计算模型

由于密码学和信息安全领域的许多问题最终都被转化为一个耗时的计算,其中许多计算需要利用多台异构的和地理分布的计算机协同,才能有效完成.密码算法的设计、分析和应用对于计算环境敏感,且依赖性较强,不同类型的算法和算法的不同实现模式对计算环境要求差异很大,而且到目前为止还不存在一种通用的分布式密码计算模型.为此,本文根据密码计算本身的需求,首先分别分析了密码算法设计、分析和应用的目标和特征,提出了相应的计算模式,给出了一种网格环境下的通用密码计算模型.进而讨论了密码计算任务分割策略,资源分配和负载平衡问题.最后给出了网格环境Globus Toolkit下的模型构架、实现与实验结果.

基于网格技术的密码学计算平台的设计

结合现有的网格技术、思想和密码计算的特点,分析了利用网格技术实现密码学计算的可行性,并结合J2EE开发方式的优势实现系统支持,最后提出了一种有效的、可行的密码计算网格平台构架.

关于网格计算授权机制的研究

分析了目前网格计算中最流行的安全机制GSI(Grid Security Infrastructure,网格安全基础设施)和基于GSI的CAS(Community Authorization Service,组织授权服务),提出了一种基于本地角色授权的、能够解决大规模VO(Virtual Organization,虚拟组织)的授权问题的方案.同GSI和CAS不同的是,本方案中的用户只需要进行本地认证就能够根据其在本地组织的角色来访问VO.

一种面向网格计算的分布式匿名协作算法

基于TCG提出的可信计算技术为网格协作安全性提出一种匿名分组身份验证算法,该算法可以非常可靠地解决网格计算平台之间的身份匿名验证问题.算法使用一个硬件模块TPM解决远程的身份验证,并通过TPM机制可以提供可靠的匿名验证和平台认证功能.算法中所有涉及的验证过程都是基于匿名机制实现的,除了实现匿名验证机制以外,算法还提供一套完整标记恶意网络实体的方法.提出了网格计算中虚拟分组的匿名认证平台架构,并在此架构基础上分成5步实现匿名验证算法,然后说明了算法在一种对等计算平台的应用实例,与GT2,GT3,GT4以及信任管理进行安全性的比较,并设计一个实验评价其性能.

基于移动代理的网格计算系统体系结构研究

本文针对物理链路可靠性低、容错性要求高、实体异构程度高的基础设施网格化需求，在系统分析当前主流的网格体系结构的基础上，研究了移动代理（PVM）系统的特性，根据移动代理的特点，提出了基于移动代理的四层网格计算模型MAGC(Mobile Agent Based Grid Computing)，描述了MAGC模型的层次结构，给出了MAGC模型的一个设计方案，分析了MAGC模型的特点，最后介绍了在Aglet平台下实现的原型系统。本文取得的成果主要包括： 第二章提出了基于移动代理的四层网格计算模型(MAGC)，说明了模型中每个层次的功能和层次之间的依赖关系。MAGC模型基于代码迁移，可以解决网络环境恶劣的条件下，网格系统的运行与部署问题。设计了MAGC模型的两个重要基础结构：作业机制和消息机制。设计了移动代理平台抽象层，使网格系统独立于具体的移动代理平台，从而具有一定的可移植性。 第三章在MAGC模型的基础上，进一步给出了MAGC模型的一个实现方案，阐述了MAGC模型中四个子层的功能和组件划分，对每层所包含的组件和组件实现的功能进行了描述，说明了系统的启动方式。 第四章基于MAGC模型构建了一个原型系统，原型系统以IBM开发的Aglets移动代理软件包为基础，实现了作业机制、消息机制和MAGC模型中的移动代理平台抽象层、系统服务层、API层、应用作业层四个子层。

一种非线性的分布式网格资源调价算法

针对网格环境下分布式异步动态调价算法存在均衡价格收敛过程缓慢、调价效率较低的缺点,提出了一种基于市场机制的非线性调价算法。该算法结合了当前超额需求和过去超额需求对资源价格变化的影响,较真实地刻画了需求变化后资源价格的波动过程。实验证明,非线性的调价算法明显地提高了价格收敛速度,降低了调价次数。

NETEMBED: A Network Resource Mapping Service for Distributed Applications

Emerging configurable infrastructures such as large-scale overlays and grids, distributed testbeds, and sensor networks comprise diverse sets of available computing resources (e.g., CPU and OS capabilities and memory constraints) and network conditions (e.g., link delay, bandwidth, loss rate, and jitter) whose characteristics are both complex and time-varying. At the same time, distributed applications to be deployed on these infrastructures exhibit increasingly complex constraints and requirements on resources they wish to utilize. Examples include selecting nodes and links to schedule an overlay multicast file transfer across the Grid, or embedding a network experiment with specific resource constraints in a distributed testbed such as PlanetLab. Thus, a common problem facing the efficient deployment of distributed applications on these infrastructures is that of "mapping" application-level requirements onto the network in such a manner that the requirements of the application are realized, assuming that the underlying characteristics of the network are known. We refer to this problem as the network embedding problem. In this paper, we propose a new approach to tackle this combinatorially-hard problem. Thanks to a number of heuristics, our approach greatly improves performance and scalability over previously existing techniques. It does so by pruning large portions of the search space without overlooking any valid embedding. We present a construction that allows a compact representation of candidate embeddings, which is maintained by carefully controlling the order via which candidate mappings are inserted and invalid mappings are removed. We present an implementation of our proposed technique, which we call NETEMBED – a service that identify feasible mappings of a virtual network configuration (the query network) to an existing real infrastructure or testbed (the hosting network). We present results of extensive performance evaluation experiments of NETEMBED using several combinations of real and synthetic network topologies. Our results show that our NETEMBED service is quite effective in identifying one (or all) possible embeddings for quite sizable queries and hosting networks – much larger than what any of the existing techniques or services are able to handle.

Load sharing in cluster service provision

The factors that are driving the development and use of grids and grid computing, such as size, dynamic features, distribution and heterogeneity, are also pushing to the forefront service quality issues. These include performance, reliability and security. Although grid middleware can address some of these issues on a wider scale, it has also become imperative to ensure adequate service provision at local level. Load sharing in clusters can contribute to the provision of a high quality service, by exploiting both static and dynamic information. This paper is concerned with the presentation of a load sharing scheme, that can satisfy grid computing requirements. It follows a proactive, non preemptive and distributed approach. Load information is gathered continuously before it is needed, and a task is allocated to the most appropriate node for execution. Performance and reliability are enhanced by the decentralised nature of the scheme and the symmetric roles of the nodes. In addition, the scheme exhibits transparency characteristics that facilitate integration with the grid.

GeneGrid: Architecture, Implementation and Application

The emergence of Grid computing technology has opened up an unprecedented opportunity for biologists to share and access data, resources and tools in an integrated environment leading to a greater chance of knowledge discovery. GeneGrid is a Grid computing framework that seamlessly integrates a myriad of heterogeneous resources spanning multiple administrative domains and locations. It provides scientists an integrated environment for the streamlined access of a number of bioinformatics programs and databases through a simple and intuitive interface. It acts as a virtual bioinformatics laboratory by allowing scientists to create, execute and manage workflows that represent bioinformatics experiments. A number of cooperating Grid services interact in an orchestrated manner to provide this functionality. This paper gives insight into the details of the architecture, components and implementation of GeneGrid.

Analysing orchestrations with risk profiles and angel-daemon games

In this paper game theory is used to analyse the effect of a number of service failures during the execution of a grid orchestration. A service failure may be catastrophic in that it causes an entire orchestration to fail. Alternatively, a grid manager may utilise alternative services in the case of failure, allowing an orchestration to recover, A risk profile provides a means of modelling situations in a way that is neither overly optimistic nor overly pessimistic. Risk profiles are analysed using angel and daemon games. A risk profile can be assigned a valuation through an analysis of the structure of its associated Nash equilibria. Some structural properties of valuation functions, that show their validity as a measure for risk, are given. Two main cases are considered, the assessment of Orc expressions and the arrangement of a meeting using reputations.