Reputation-based dependable scheduling of workflow applications in Peer-to-Peer Grids

Grids facilitate creation of wide-area collaborative environment for sharing computing or storage resources and various applications. Inter-connecting distributed Grid sites through peer-to-peer routing and information dissemination structure (also known as Peer-to-Peer Grids) is essential to avoid the problems of scheduling efficiency bottleneck and single point of failure in the centralized or hierarchical scheduling approaches. On the other hand, uncertainty and unreliability are facts in distributed infrastructures such as Peer-to-Peer Grids, which are triggered by multiple factors including scale, dynamism, failures, and incomplete global knowledge.In this paper, a reputation-based Grid workflow scheduling technique is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Peer-to-Peer Grid environments. The proposed approach builds upon structured peer-to-peer indexing and networking techniques to create a scalable wide-area overlay of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers mediated via Grid resource brokers. The proposed algorithm dynamically adapts to changing resource conditions and offers significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. The results evaluated through an extensive trace driven simulation show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system.     

Decentralising a service-oriented architecture

Service-oriented computing is becoming an increasingly popular paradigm for modelling and building distributed systems in open and heterogeneous environments. However, proposed service-oriented architectures are typically based on centralised components, such as service registries or service brokers, that introduce reliability, management, and performance issues. This paper describes an approach to fully decentralise a service-oriented architecture using a self-organising peer-to-peer network maintained by service providers and consumers. The design is based on a gradient peer-to-peer topology, which allows the system to replicate a service registry using a limited number of the most stable and best performing peers. The paper evaluates the proposed approach through extensive simulation experiments and shows that the decentralised registry and the underlying peer-to-peer infrastructure scale to a large number of peers and can successfully manage high peer churn rates.     

An autonomic approach for P2P/cloud collaborative environments

The rise of Cloud Computing has progressively dimmed the interest in volunteer and peer-to-peer computing, in general. However, efficient and cost-effective large scale distributed collaborative environments cannot be achieved leveraging upon the Cloud alone. In this paper, we propose a novel hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. The proposed approach is based on the Networked Autonomic Machine (NAM) framework, which allows distributed system designers to include different kinds of cost and performance constraints. As an example, we show how the NAM-based approach can be used to design collaborative storage systems, enabling the definition of an autonomic policy to decide, according to cost minimization and data availability goals, how to part data chunks among peer nodes and Cloud, based on the local perception of the P2P network.     

A workload-driven approach to database query processing in the cloud

This paper is concerned with data provisioning services (information search, retrieval, storage, etc.) dealing with a large and heterogeneous information repository. Increasingly, this class of services is being hosted and delivered through Cloud infrastructures. Although such systems are becoming popular, existing resource management methods (e.g. load-balancing techniques) do not consider workload patterns nor do they perform well when subjected to non-uniformly distributed datasets. If these problems can be solved, this class of services can be made to operate in more a scalable, efficient, and reliable manner. The main contribution of this paper is a approach that combines proprietary cloud-based load balancing techniques and density-based partitioning for efficient range query processing across relational database-as-a-service in cloud computing environments. The study is conducted over a real-world data provisioning service that manages a large historical news database from Thomson Reuters. The proposed approach has been implemented and tested as a multi-tier web application suite consisting of load-balancing, application, and database layers. We have validated our approach by conducting a set of rigorous performance evaluation experiments using the Amazon EC2 infrastructure. The results prove that augmenting a cloud-based load-balancing service (e.g. Amazon Elastic Load Balancer) with workload characterization intelligence (density and distribution of data; composition of queries) offers significant benefits with regards to the overall system’s performance (i.e. query latency and database service throughput).     

基于OpenVZ的中小型企业私有云定制服务的设计与实现

云计算是当前计算机信息科技领域十分热门一项的技术。私有云凭借其整合管理企业IT资源的优越性能,迅速被大众企业认可。为了降低中小型企业的运营成本,该文提出基于OpenVZ框架及其核心组件搭建私有云平台的解决方案,通过LNMP实现框架,采用磁盘阵列(RAID10)、定时任务corn等备份技术保障企业数据安全。搭建Centos6、Debian、Ubuntu等系统镜像模板以及虚拟服务器,满足不同环境需求。测试表明,OpenVZ实现的云平台可充分解决中小型企业资源管理问题。     

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). SLAs define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.     

A secure information service for monitoring large scale grids

The Grid Information Service (GIS) is a core component in the Grid software infrastructure. It provides diverse information to users or other service components in Grid environments. In this paper, we propose a scalable GIS architecture for information management in a large scale Grid Virtual Organization (VO). This architecture consists of the VO layer, site layer and resource layer: at the resource layer, information agents and pluggable information sensors are deployed on each resource monitored. This information agent and sensor approach provides a flexible framework that enables specific information to be captured; at the site layer, a site information service component with caching capability aggregates and maintains up-to-date information of all the resources monitored within an administrative domain; at the VO layer, a peer-to-peer approach is used to build a virtual network of site information services for information discovery and query in a large scale Grid VO. This decentralized approach makes information management scalable and robust. Furthermore, we propose a security framework for the GIS, which provide security policies for authentication and authorization control of the GIS at both the site and the VO layers. Our GIS has been implemented based on the Globus Toolkit 4 as Web services compliant to Web Services Resource Framework (WSRF) specifications. The experimental results show that the GIS presents satisfactory scalability in handling information for large scale Grids.     

Network virtualization in energy-efficient office environments

The rising costs of energy and world-wide desire to reduce CO₂ emissions has led to an increased concern over the energy efficiency of information and communication technology. Whilst much of this concern has focused on data centres, office environments (and the computing equipment that they contain) have also been identified as a significant consumer of energy. Office environments offer great potential for energy savings, given that computing equipment often remains powered for 24 h per day, and for a large part of this period is underutilised or idle. This paper proposes an energy-efficient office management approach based on resource virtualization, power management, and resource sharing. Evaluations indicate that about 75% energy savings are achievable in office environments without a significant interruption of provided services. A core element of this office management is a peer-to-peer network that interconnects office hosts, achieves addressing and mediation, and manages energy efficiency within the office environment. Several peer-to-peer approaches are suggested and discussed in this paper. Two of the approaches are evaluated, based on a discrete-event simulation.     

Facilitating resource discovery in grid environments with peer-to-peer structured tuple spaces

The computational grid is rapidly evolving into a large-scale computing infrastructure that facilitates resource sharing and problem solving over the Internet. Information services play a crucial role in grid environments for discovery of resources. The dynamic nature and the large-scale of a grid pose many challenges to information services in terms of scalability and resilience. This paper presents RDSpace which can be used as a substrate for resource discovery in grid environments. RDSpace builds a shared tuple space on top of a structured peer-to-peer overlay to achieve high scalability in dealing with a large number of computing nodes and to support range queries in discovery of resources. Another novelty of RDSpace lies in its capability to handle churn situations where nodes may join or leave the space frequently. RDSpace is evaluated from the aspects of scalability and churn handling, and the evaluation results are also presented in this paper.     

Security and Control in the Cloud

ABSTRACT

Cloud computing is a new IT delivery paradigm that offers computing resources as on-demand services over the Internet. Like all forms of outsourcing, cloud computing raises serious concerns about the security of the data assets that are outsourced to providers of cloud services. To address these security concerns, we show how today's generation of information security management systems (ISMSs), as specified in the ISO/IEC 27001:2005, must be extended to address the transfer of security controls into cloud environments. The resulting virtual ISMS is a standards-compliant management approach for developing a sound control environment while supporting the various modalities of cloud computing.

This article addresses chief security and/or information officers of cloud client and cloud provider organizations. Cloud clients will benefit from our exposition of how to manage risk when corporate assets are outsourced to cloud providers. Providers of cloud services will learn what processes and controls they can offer in order to provide superior security that differentiates their offerings in the market.     

一种基于多Agent系统的云服务自组织管理方法

在开放动态的互联网环境下的云服务呈现出发散、动态演化、异构等特征,为了适应多样的应用需求以及持续变化的云环境,云需要以灵活、适应的方法来有效地管理和提供云服务.针对这一需求,提出了一种云服务自组织管理方法,该方法利用agent的环境感知和自主行为决策的能力,依据它的职责实现对云服务的自主管理,并通过agent间的交互以自组织的方式实现对服务资源的有效管理,进而适应云环境和应用需求的变化;提出了支持上述方法和机制的实现技术,包括云服务自组织管理的核心机制和实现框架、云服务汇聚和提供的运行机制及相关实现算法.利用支持语义Web服务发现匹配的公共测试数据设计并完成了两组验证实验,实验结果表明:所提出的方法可以在持续变化的云环境下有效地管理和提供云服务,进而满足动态多样化的应用需求.     

Context-based caching and routing for P2P web service discovery

In modern heterogeneous environments, such as mobile, pervasive and ad-hoc networks, architectures based on web services offer an attractive solution for effective communication and inter-operation. In such dynamic and rapidly evolving environments, efficient web service discovery is an important task. Usually this task is based on the input/output parameters or other functional attributes, however this does not guarantee the validity or successful utilization of retrieved web services. Instead, non-functional attributes, such as device power features, computational resources and connectivity status, that characterize the context of both service providers and consumers play an important role to the quality and usability of discovery results. In this paper we introduce context-awareness in web service discovery, enabling the provision of the most appropriate services at the right location and time. We focus on context-based caching and routing for improving web service discovery in a mobile peer-to-peer environment. We conducted a thorough experimental study, using our prototype implementation based on the JXTA framework, while simulations are employed for testing the scalability of the approach. We illustrate the advantages that this approach offers, both by evaluating the context-based cache performance and by comparing the efficiency of location-based routing to broadcast-based approaches. Recommended by: Zakaria Maamar     

基于凸函数证据理论的关联感知云服务信任模型

针对大规模分布式云计算系统中的服务可信度辨别问题,提出一种基于凸函数证据理论的关联感知云服务信任模型。对云计算系统中云服务提供商、服务和用户之间的信任关系进行形式化描述,充分挖掘了同一服务商中的不同云服务之间的关联性,利用凸函数证据理论对有序命题的处理能力,构建了云计算系统中的可信服务推荐方法,根据用户需求为其提供合理可靠的云服务。与经典证据理论方法的对比结果表明,基于凸函数证据理论的关联感知云服务信任模型在保证有效性和健壮性的同时,充分利用了云计算系统中云服务之间的关联信息,能够根据用户的请求提供合理的云服务。     

云应用部署配置模型

云计算已经成为广泛使用的计算范型,越来越多的大规模分布式系统已经或正在向云平台部署和迁移.用户在部署和管理维护应用系统时通常需要管理底层基础设施资源细节,或者使用平台提供方的应用部署和管理服务,前者使得应用部署和运行时管理易于出错且费时费力,而后者则降低了系统管理的灵活性,很难满足用户的个性化需求.针对这一问题,本文提出了一种高层抽象模型来描述云应用的部署配置和管理需求.需求模型采用声明式机制定义期望的系统状态,而无需描述实现目标状态所需的执行步骤和细节.本文基于开源云计算平台OpenStack和自动化配置管理工具Puppet进行了原型实现,通过一个应用案例验证模型的有效性.     

Evaluation framework for adaptive context-aware routing in large scale mobile peer-to-peer systems

The proliferation of novel wireless network technologies creates new opportunities for complex peer-to-peer information dissemination systems. A key challenge that remains in this area is how to select the best algorithms and protocols to communicate effectively on a large scale. In this paper, we focus in particular on large scale mobile networks where effectiveness depends on the requirements of the application at hand and on the context of the peers in the network. We propose a framework for context-aware adaptive information sharing that allows the evaluation of and comparison with alternative information routing protocols using network metrics to measure a variety of quality attributes of the information dissemination protocols. These metrics can then be used to verify which protocol is best suited for a particular application. We illustrate our evaluation framework with different information dissemination protocols in an inter-vehicle communication scenario.     

Toward Internet distributed computing

Emerging Internet uses-including peer-to-peer and grid computing-provide both a glimpse of and the impetus for evolving the Internet into a distributed computing, platform of unprecedented scale. Taking a longer view, the authors consider what would be needed to make the Internet an application-hosting platform: a networked, distributed counterpart of the hosting environment traditional operating systems provide to applications within a single node. The foundation of their proposed approach is to disaggregate and virtualize individual system resources as services that can be described, discovered, and dynamically configured at runtime to execute an application.     

基于多属性度量的数据分级访问模型研究

随着云计算的迅速发展,云存储已成为企业关键信息服务的重要途径。但是,受限于存储资源性能以及大数据等影响,用户往往需要忍受较长的访问延时。为了缓解这种情况,人们提出了智能数据管理技术,用于有效管理大量数据以及降低用户的访问延迟,提高云计算的服务质量。提出一种基于多属性分析的存储端数据分级访问模型。模型通过对被管理数据对象的动态、静态属性进行统计分析来提取属性中的关键信息,并依此进行数据管理决策,将冷/热数据迁移至对应层级,以便能够在合理规划存储资源的同时提高存储系统的访问性能。性能测试实验的结果表明,该模型具有较好的整体性能。     

A peer-to-peer file search and download protocol for wireless ad-hoc networks

Deployment of traditional peer-to-peer file sharing systems on a wireless ad-hoc network introduces several challenges. Information and workload distribution as well as routing are major problems for members of a wireless ad-hoc network, which are only aware of their immediate neighborhood. In this paper, we propose a file sharing system that is able to answer location queries, and also discover and maintain the routing information that is used to transfer files from a source peer to another peer. We present a cross-layer design, where the lookup and routing functionality are unified. The system works according to peer-to-peer principles, distributes the location information of the shared files among the members of the network. The paper includes a sample scenario to make the operations of the system clearer. The performance of the system is evaluated using simulation results and analysis is provided for comparing our approach with a flooding-based, unstructured approach.     

Sky Computing

Infrastructure-as-a-service (IaaS) cloud computing is revolutionizing how we approach computing. Compute resource consumers can eliminate the expense inherent in acquiring, managing, and operating IT infrastructure and instead lease resources on a pay-as-you-go basis. IT infrastructure providers can exploit economies of scale to mitigate the cost of buying and operating resources and avoid the complexity required to manage multiple customer-specific environments and applications. The authors describe the context in which cloud computing arose, discuss its current strengths and shortcomings, and point to an emerging computing pattern it enables that they call sky computing.     

基于云计算模式的ERP企业管理信息系统分析

对于现代企业来讲,为了实现对企业信息的有效管理,提高企业管理效率,已经开始致力于建立企业内部的ERP管理信息系统。目前国内的大中型企业,很多已经建立了完善的ERP企业管理信息系统。考虑到企业规模的扩大以及企业管理数据的成倍增加,现有的ERP管理信息系统已经显示出一定的局限性。随着计算机技术的飞速发展,云计算的概念逐步得到了推广和应用。基于云计算的特点,ERP企业管理信息系统开始有意识的与云计算概念相结合。本文主要介绍了云计算模式的ERP企业管理信息系统特点和优势,对其应用效果进行了深入的分析。