基于遗传算法的虚拟机在线迁移优化方法

虚拟机在线迁移是云计算研究热点。目前已有的研究工作未能考虑Web应用资源需求的变化规律,可能会存在因虚拟机循环迁移而导致的Web应用性能频繁违约现象。提出一种基于Web应用资源需求变化分析的虚拟机迁移优化方法,以虚拟机资源需求小于物理机资源供给为约束条件,将虚拟机和物理机空间布局的稳定性刻画成收益。每次执行虚拟机在线迁移操作时,都以收益最大化作为待迁移虚拟机和目标物理机的选择依据。实验结果表明,与已有方法相比,本方法能减少超过50%的性能违约次数。     

基于请求目标分类的Web QoS动态控制模型

针对目前通用的Web服务器上未实现有效的QoS控制的现状以及Web QoS控制灵活性不够、通用性不强、可扩展性不好等缺点,提出了一种基于请求目标分类的Web QoS动态控制模型,采用以控制响应时间为中心的动态控制策略,对HTTP请求进行基于目标分类的动态接纳控制以及动态的重配置处理。实验结果表明,该方法可以显著减少系统响应时间,并保证在高负载下的吞吐量的平稳性。     

云环境下Web应用带宽资源预测与管理

针对Web应用带宽资源管理问题,提出了一种基于网络仿真的Web应用带宽需求和服务质量（QoS）预测方法,该方法给出了适用于Web服务的建模框架与形式说明,采用简化的并行负载模型,并运用自动化数据挖掘方法从Web应用访问日志中提取模型参数,并使用网络仿真工具建立系统模型模拟复杂网络传输过程,能够预测不同负载强度下的带宽需求和QoS变化。通过TPC-W基准测试系统验证该方法预测结果的准确性,理论分析和仿真结果表明,与传统的线性回归预测相比,网络仿真可以稳定地模拟真实系统,其对总请求数和总字节数的预测平均相对误差分别为4.6%和3.3%。最后以TPC-W基准系统为例,对Web应用不同带宽伸缩方案进行仿真评估,评估结果可以为Web应用资源管理提供决策支持。     

基于混沌预测的IP QoS模型与机制

利用混沌相关理论对具有综合业务应用的IP网流量进行了混沌特性与预测分析，提出了基于混沌预测的IP QoS实现模型与算法。OPNET的网络仿真实验表明，与传统的静态QoS参数配置方法和基于测量的QoS设置方法比较，该模型及方法在网络重负载环境下使各业务的QoS性能指标得到有效改善。     

一种基于服务质量的语义Web服务发现框架

在Web服务发现过程中,不同的用户希望根据自己的情况或个性化的需求进行服务选择,如何提供满足用户服务质量（QoS）需求的服务是语义Web服务应用急需解决的问题。基于OWL规范定义了一个QoS元模型——OWL-QoS,并将其应用于Web服务描述当中。根据提出的QoS元模型给出了一个基于QoS的语义Web服务发现框架,并从基本描述、IOPE、QoS三个层次实现了服务匹配。实验结果表明,与传统语义Web服务发现方法相比,该方法能显著提高服务匹配精度和效率。     

基于树型二重结构编码遗传算法的服务选择

提出了Web服务语法业务流程树的概念,并结合基于QoS的Web服务全局选择的特点,研究了一种用于组合服务QoS优化的基于树型二重结构编码的遗传算法GATD。该方法建立在服务语法业务流程树先序遍历序列编码的基础上,采用二重编码方法处理用户的QoS约束条件,不仅能够有效地选择出满足用户QoS需求的服务资源,而且可以较好地支持服务运行时快速再规划。     

基于贝叶斯策略的网格资源分配方法

考虑网格应用QoS需求,以最大化网格系统的经济收益为目标,提出了一种基于贝叶斯策略的网格资源分配方法。该方法基于价格可代表资源QoS综合性能的思想,利用历史QoS匹配记录,运用朴素贝叶斯定理根据用户提交的价格参数来分配与其级别相对应的符合要价范围资源,并优先考虑QoS水平较高的任务,将当前时刻QoS水平较高的资源预留给下一时刻到达的QoS水平较高的任务,而忽略当前时刻QoS水平较低的任务。实验结果表明,该资源分配方法不仅能有效地保障用户QoS,而且能使网格系统获得较大的经济收益。     

物联网环境下基于情境的语义Web服务选择

当前Web服务海量增加，物联网应用技术快速发展、不断普及，而现有的Web服务选择算法低效、用户匹配度低。针对该问题提出一种物联网环境下基于情境的语义Web服务选择方法。该方法应用QoS参数的无量纲化与语义Web服务动态选择方式，将物联网环境下服务与语义Web服务相结合，并根据用户需求针对QoS选择最优的服务集。实验表明，该方法能有效地提高用户服务动态选择的成功率。     

一种基于服务质量的语义Web服务发现框架

在Weh服务发现过程中,不同的用户希望根据自己的情况或个性化的需求进行服务选择,如何提供满足用户服务质量(Qos)需求的服务是语义Web服务应用急需解决的问题.基于OWL规范定义了一个QoS元模型--OWL-QoS,并将其应用于Web服务描述当中.根据提出的Qos元模型给出了一个基于Qos的语义Web服务发现框架,并从基本描述、IOPE、QoS三个层次实现了服务匹配.实验结果表明,与传统语义Web服务发现方法相比,该方法能显著提高服务匹配精度和效率.     

一种智能电视终端在线自适应多资源调度方法

针对智能电视终端面临的运行时资源冲突和过载控制问题,提出一种在线自适应多资源调度方法(OARSA).该方法根据资源特点和应用优先级对独占型资源进行动态优先级抢占式调度,避免了资源冲突;采用反馈控制算法对共享型资源进行QoS调度,直到实现QoS比例公平性,并采用QoS比例压缩法消除资源过载.实验结果表明,OARSA具备过载控制能力,仅以系统总体QoS下降4.5％为代价,解决了资源冲突,并提高了系统重负载下的响应性能,且算法耗时比现有方法降低约30％,更加适用于智能电视终端的资源调度.     

A benefit-aware on-demand provisioning approach for multi-tier applications in cloud computing

Dynamic resource provisioning is a challenging technique to meet the service level agreement (SLA) requirements of multi-tier applications in virtualization-based cloud computing. Prior efforts have addressed this challenge based on either a cost-oblivious approach or a cost-aware approach. However, both approaches may suffer frequent SLA violations under flash crowd conditions. Because they ignore the benefit gained that a multi-tier application continuously guarantees the SLA in the new configuration. In this paper, we propose a benefit-aware approach with feedback control theory to solve this problem. Experimental results based on live workload traces show that our approach can reduce resource provisioning cost by as much as 30% compared with a costoblivious approach, and can effectively reduce SLA violations compared with a cost-aware approach.     

Quality-of-service adaptation in distributed multimedia applications

High-speed networks and powerful end-systems enable new types of applications, such as video-on-demand and teleconferencing. Such applications are very demanding on quality of service (QoS) because of the isochronous nature of the media they are using. To support these applications, QoS guarantees are required. However, even with service guarantees, violations may occur because of resources shortage, e.g., network congestion. In this paper we propose new adaptation approaches, which allow the system to recover automatically, if possible, from QoS violations (1) by identifying a new configuration of system components that might support the initially agreed QoS and by performing a user-transparent transition from the original configuration to the new one, (2) by redistributing the levels of QoS that should be supported, in the future, by the components, or (3) by redistributing the levels of QoS that should be supported immediately to meet end-to-end requirements based on the principle that (local) QoS violation at one component may be recovered immediately by the other components participating in the support of the requested service. The proposed approaches, together with suitable negotiation mechanisms, allow us (1) to reduce the probability of QoS violations which may be noticed by the user, and thus, to increase the user confidence in the service provider, and (2) to improve the utilization of the system resources, and thus to increase the system availability.     

Dynamic service selection with QoS constraints and inter-service correlations using cooperative coevolution

Building business processes by Web services in cloud computing has become the hotspot of service applications. Due to the complexity and uncertainty of business environment, QoS violations of service processes often take place at run-time. To rapidly recover from failures and minimize their impacts on the original execution plan of service processes, dynamic service selection is urgently needed once potential QoS violations are detected. However, existing research works do not fully investigate QoS constraints and inter-service correlations, as well as the breach penalty caused by service adjustment. In this paper, we present a new cooperative coevolutionary approach for dynamic service selection with QoS constraints and inter-service correlations. First, a novel formal model for the dynamic service selection problem with QoS constraints and inter-service correlations is presented. Second, a Double Information based Cooperative Coevolutionary algorithm (DICC) is proposed which uses Potter’s cooperative coevolutionary framework and provides both local and global knowledge for the dynamic service selection optimization. Finally, we develop a prototype system to apply our approach and adopt different test cases to show that our DICC approach performs more effectively and efficiently than existing algorithms.     

QoS需求驱动的服务配置框架

为支持服务质量敏感的基于组件的分布式应用的开发,中间件需要为组件提供并配置各种服务质量服务的非功能性属性.目前的组件架构提供的服务配置方式大多是静态的,且没有考虑不同客户的需求.在对EJB架构进行研究的基础上,提出一种服务质量需求驱动的服务配置框架.研究了根据客户的服务质量需求,在组件实例级别自动生成服务配置决策并实施,实现对不同客户服务差分处理.框架是一个基于服务配置的决策模型,通过多选择背包问题生成服务配置策略.最后通过一个应用实例对框架进行了验证.     

基于QoS的Web服务选择方法研究新进展*

随着服务计算、云计算技术的迅速发展,具有相同或相似功能但服务质量（QoS）不同的可用服务已大规模部署在互联网上。如何从这些海量Web服务中为服务组合选择令人满意的服务成了一个重要的研究问题,其选择方法是影响组合服务的QoS 和服务组合性能高低的关键因素。为了解决该问题,研究者们已开发了许多服务选择方法以帮助用户选择合适的服务。针对近五年基于QoS的Web服务选择方法的新进展进行了综述。归纳了包括运用Skyline计算、协同过滤、优化算法、多属性决策支持理论和混合方法等一些典型的服务选择方法,讨论了各方法的优势和局限性,并根据当前研究现状,探讨了该领域的发展趋势和未来研究方向和挑战。     

An efficient and lightweight method for Service Level Agreement assessment

Traditional approaches to on-line end-to-end Service Level Agreement (SLA) assessment have focused on the estimation of network QoS parameters. These approaches, however, face a trade-off between accuracy and the amount of resources needed to achieve such accuracy. This paper offers an alternative approach, where instead of estimating QoS parameters, we propose an effective and lightweight solution for directly detecting SLA violations. Our solution monitors the Inter-Packet Arrival Time (IPAT) at an end-point, wherein current IPAT distributions are periodically compared with a set of reference IPAT distributions as the main basis for detecting SLA violations. A mapping of the IPAT distribution with the current network conditions is derived, and a training algorithm that dynamically acquires the set of reference IPAT distributions is designed. For the comparison of the IPAT distributions, we propose a variant of the Hausdorff Distance algorithm. Our variant provides a better accuracy than the traditional Hausdorff Distance, while presenting linear complexity. Our proposal is validated in a real testbed, by comparing the SLA violations detected and the resources required in terms of bandwidth, with other existing alternatives as well as with perfect knowledge of current network QoS status.     

Two different approaches for providing QoS in the Internet backbone

This paper compares two different approaches for providing QoS in the Internet backbone. The first, denoted as simple approach, is a simple method of Admission Control performed by a weighted-fair-queuing scheduler. This approach guarantees QoS with a suitable overprovisioning of transmission resources. The second approach, denoted as basic statistical approach, is a full-featured statistical framework, based on the central limit approximation, for estimating the delay bound violation probability associated to each traffic class, given the offered traffic and the schedulers’ configuration. Both approaches adopt the dual-leaky-bucket (p, r, b) regulated traffic model in order to characterize the aggregate traffic flows. At first, we analyze the characteristics of both approaches in order to point out the respective pros and cons. Then, we propose an enhanced version of the basic statistical approach, the enhanced statistical approach. Our novel approach, as opposed to the basic statistical approach, performs a joint optimization of the regulator’s parameters and of the network capacity instead of a separate optimization. Our study shows that the enhanced statistical approach outperforms both the basic statistical approach and the simple approach and offers the highest potential for a better utilization of transmission resources. The basic and the enhanced statistical approaches assume that traffic is Gaussian. The simple approach has looser constraints on the statistical behavior of traffic, but it requires overprovisioning of transmission resources to guarantee the required QoS in terms of packet delay and loss.     

一种服务质量驱动的企业应用软件构件组装方法

针对现有面向全局构件组装方案选择技术的不足,提出了一种基于服务质量优化的构件组装方案选择方法.该方法主要是面向大型复杂企业应用软件系统的配置管理,其主要思想是将构件组装方案的选择问题转化为带约束的多目标优化问题.针对该问题,给出了一种基于向量编码的构件组装方案选择遗传算法,该编码方式可以非常方便地表示构件组装模型中构件接口之间的连接关系,从而克服了现有编码在描述构件组装模型中的局限性.最后通过实验分析了算法的可行性.     

An Algebraic QoS-Based Resource Allocation Model for Competitive Multimedia Applications

A new class of multimedia applications require new mechanisms to consider various Quality of Services with respect to resource constraints so that they could support reliable services and utilize available resources optimally. In this paper we present a new analytical and generic resource management model that is QoS-based. The approach for resource allocation and relevant algorithms is based on a mathematically proved model that manages resource and QoS allocation intelligently so that the total system utility of is maximized. We use the constructs of application benefit functions and resource demand functions to represent the system configuration and to solve the resource allocation problems. Extensive surveys on the related work including systematic and analytical approaches are also presented.