基于QoS优化的面向服务流程分解方法

面向服务的业务流程分解是构建面向服务系统的前提。文章分析了复杂业务过程的QoS因素及其计算,提出一种基于QoS的服务流程分解方法。该方法首先应用OWL-S(Ontology Web Language for Services)进行流程建模,再对OWL-S模块进行归并、组合,将复杂业务流程转化成由几种典型结构构成的服务组合形式,通过服务组合和流程QoS约束的计算,实现流程分解的优化。最后通过一个汽车贷款审批的实例验证了分解方法的有效性。     

移动IPv6中QoS的实现

现有的网络服务质量(QoS)有两大模型:集成服务(Intserv)和区分服务(D iffserv)。这两种服务都是针对静态环境(固定主机和固定路由)设计的,对于移动通信网络都不能完全适用。本文结合集成服务和区分服务的优点,提出了一种新的双平面的三重QoS体系,并描述了这一体系对端到端QoS的实现。最后通过实例概述了QoS体系的整体流程,扩展了移动IPv6(M IPv6)信令中的绑定升级(BU)、绑定请求(BR)、绑定确认(BA)三个选项。     

WLAN的QoS分析与研究

随着WLAN的应用越来越广泛,其QoS问题也越来越受到广泛的重视和研究,传统的IEEE802.11协议无法为蓬勃发展的多媒体业务提供有效的QoS支持,使得在WLAN上应用多媒体业务带来了困难,虽然引入了优先级区分的IEEE802.11e具有较好的QoS支持,但是随着多媒体业务对实时性的要求越来越高,并且随着业务站点的增加,IEEE802.11e仍有其不足的地方,就WLAN的QoS问题进行了一些分析和研究,对影响WLAN的因素进行了探讨。     

浅析基于策略的网络管理相关技术分析

目前基于策略的网络管理技术发展迅速,引起越来越多关注。本文基于这样技术和应用背景,展开相应基于策略网络管理理论及相关关键技术分析。提出基于策略的网络管理思想模型。     

IPTV马赛克故障处理一例及故障处理思路总结

运营商的IPTV业务,在运营过程中存在马赛克、图像静止、频道切换等待时间长等问题,导致用户主观感知较差,严重影响了IPTV业务的发展,针对此问题通过有效的方法对网络进行了全方面的诊断和处理,解决了马赛克和图像静止和频道切换等问题,有力支撑了运营商IPTV业务的大发展。     

TD-SCDMA系统中呼叫接入控制算法研究

呼叫接入控制(CAC)是无线通信网络资源管理中一个重要的组成部分,CAC策略依据一定的准则决定呼叫到达请求的允许接入或拒绝接入,其中策略设计的好坏直接影响着网络的性能和资源利用率。目前,码分多址系统中的基于门限比较的接入控制算法是在理想条件下研究的,由于判定不能灵活控制管理,使得系统掉话率较高。对理想状态下的判定进行改进,提出了随着系统业务负荷变化的自适应调节算法。仿真结果显示,改进后的方案比以前有较好的性能,具有时延小、精度高、性能好、容易实现等特点。     

线性多用户检测器的软件无线电实现

无线多媒体通信的实现要求对不同种类业务提供不同的服务质量（ＱｏＳ）,文章将软件无线电技术应用于无线通信系统中,通过现场可编程门阵列（ＦＰＧＡ）和数字信号处理器（ＤＳＰ）的配合实现ＤＳ－ＣＤＭＡ系统的线性多用户检测。可以根据业务要求与信道状况调整线性滤波器抽头值,从而动态选择检测器类型,在算法复杂度和性能上求得平衡。仿真结果给出了４种线性多用户检测器对用户数及信噪比变化的性能比较。     

第三方物流业务流程中基于SLA的监测机制研究

物流服务需求方和物流服务提供方之间的信息不对称可能导致LSP提供较差的服务或较高服务价格,甚至可能会泄露商业机密,导致LSR遭受巨大损失。而仅凭签订的合同难以实时监测其实施情况。针对这一问题,在阐述面向领域的物流SLA基础上提出了一种基于SLA的监测机制。在服务的部署过程中,由第四方物流完成服务资源的重新配置,使得LSP能够根据用户需求提供一定等级的服务。最后还给出了一个具体的实例,进一步分析说明物流SLA的监控机制。     

A method towards Web service combination for cross-organisational business process using QoS and cluster

How to quickly combine various Web services to support cross-organisational business processes is the key technical problem in service computing. Because of the changeability of QoS of Web services, the traditional methods are unadaptable to the new environments. In this paper, a new service composition method, called Improved Self-organising neural network Method for Web Service Composition, is proposed to achieve QoS-aware Web service combination, according to using the clustering technology. First, fuzzy mathematics is used to express each QoS attribute and the improved self-organising neural network is used to cluster services to reduce the number of candidate services. Secondly, all the centre of each cluster is selected and formed a composite service by using an exhaustive algorithm. Thirdly, the service cluster that is represented by the concrete services. Finally, the optimal service combination can be selected using integer programming or genetic algorithm. The experimental result shows the efficiency of Web service composition and demonstrates the applicability.     

QaaS (quality as a service) model for web services using big data technologies

Quality of service (QoS) determines the service usability and utility and both of which influence the service selection process. The QoS varies from one service provider to other. Each web service has its own methodology for evaluating QoS. The lack of transparent QoS evaluation model makes the service selection challenging. Moreover, most QoS evaluation processes do not consider their historical data which not only helps in getting more accurate QoS but also helps for future prediction, recommendation and knowledge discovery. QoS driven service selection demands a model where QoS can be provided as a service to end users. This paper proposes a layered QaaS (quality as a service) model in the same line as PaaS and software as a service, where users can provide QoS attributes as inputs and the model returns services satisfying the user’s QoS expectation. This paper covers all the key aspects in this context, like selection of data sources, its transformation, evaluation, classification and storage of QoS. The paper uses server log as the source for evaluating QoS values, common methodology for its evaluation and big data technologies for its transformation and analysis. This paper also establishes the fact that Spark outperforms the Pig with respect to evaluation of QoS from logs.