基于变化的服务演化一致性判定

由于Web服务处在开放、动态、多变的网络环境下,为了有效响应用户需求、运行平台及外部环境的变化,服务必须具备演化的能力。演化后的服务应维持与原伙伴服务或服务用户之间的正常交互,这种性质称为演化一致性。由于Web环境的多样性,服务开发者对演化一致性的判定的标准并不统一。对于服务演化一致性判定问题,现有方法大多基于固定的判定标准,缺乏可调节、细粒度的定量分析且不能显式地反映服务版本之间的变化。针对上述不足,面向服务演化导致的变化,从服务的结构层和非功能层两个角度建立基于变化的服务描述模型,并在该模型的基础上引入演化一致度对演化一致性进行度量。基于所提出的方法,设计并实现了一个服务演化一致性判定工具,验证了所提出方法的可行性与有效性。     

基于可变性模型的可复用与可定制SaaS软件开发方法

云计算环境下,软件通过互联网向租户提供服务,这种基于互联网的软件交付模式称为SaaS（软件即服务）.与传统软件交付模式相比,SaaS软件通常运行于软件供应商的服务器端,同时为多个租户提供服务.由于需要支持不同租户的个性化需求,SaaS软件应具备足够的灵活性,以应对快速变化的租户需求;而且针对某一个租户的变更,不应影响其他租户.通过扩展课题组前期开发的基于可变性管理的适应性服务组装方法及其支持平台,提出了一种云计算环境下可复用、可定制的SaaS软件开发方法,开发了相应的支持平台,包括支持SaaS模式的服务组装引擎和远程定制工具.该方法针对不同租户的共性需求,提供一个抽象服务组装模型,支持平台在运行阶段解释执行抽象服务组装模型,根据租户的个性化需求派生不同的流程实例,这些运行时流程实例多态共存、互不影响.采用一个特定领域的SaaS软件实例来验证该方法的可行性,评估了支持平台的性能.实验结果表明,该方法及其支持平台可以支持多实例多租户的交付模式.     

SaaS多租户数据管理及实现策略

云计算是通过互联网以服务的形式为客户提供企业级计算资源的技术。最普遍使用的服务是软件即服务(SaaS)。许多SaaS提供者利用多租户模式来托管应用。多租户是一种架构方法,软件应用程序的单实例服务多个租户,因此多租户设计关键要解决的是租户数据的共享与隔离。文章论述了多租户架构中数据存储管理的三种方式,详细描述了共享表时多租户数据库的具体实现策略,指出了各种模式映射技术的优缺点,最后给出了将来的研究目标。     

基于DIFC的租户自主授权SaaS层数据隔离与共享模型*

SaaS服务提供者对租户间提供数据共享服务时,容易造成租户数据的泄露,并且在租户未经许可的情况下,可以非法获取租户的隐私数据。针对上述SaaS服务的缺陷,本文引入了分布式信息流控制(DIFC)安全防护机制,提出了基于DIFC的租户自主授权SaaS层数据隔离与共享模型。该模型强制SaaS服务提供者执行标签比对机制,各租户可以自主划分用户信息级别,定制全球唯一标记。并通过第三方可信标签管理授权服务(AS),细粒度地限制租户间的数据共享操作,并必须经用户授权标签才能访问相应数据。最终本文证明了此模型可以满足租户数据隔离与共享的安全。     

SaaS模式下支持多租户可定制的Portlet协作模型设计

SaaS已经成为云计算应用层的标准软件交付模型,该软件的核心技术特点是单实例多租户体系结构。这种多承租体系结构在降低服务运营商成本的同时,也要求软件在功能上具有更强的可订制性,以满足不同租户的特定需求。以SaaS的方式提供Portal服务,不仅可以减少运营商的成本,而且也大大降低了购买者的维护费用,这将使Portal产品更具有市场竞争力。但已有的Portlet规范并没有考虑SaaS模式和多承租需求,因此不能支持租户对Portlet协作进行订制。对JSR286规范进行扩展,提出一种支持多租户可订制的Portlet组件协作模型,使Portlet规范可以更好地满足SaaS应用的需求,并给出在Portal系统中该模型的设计和实现。     

构件系统演化一致性的判定方法

构件系统演化一致性是确保演化操作可靠的必要条件,若一致性得不到满足,则会致使演化后的系统达不到既定的功能目标。针对该问题,文中提出基于接口、流程结构、内部行为的构件系统演化一致性判断方法。首先,在演化后的系统中将每个构件视为判定执行者,使所有的构件协同参与一致性判定过程,从接口和流程结构出发,判断执行者和全局的一致性;其次,在满足接口、流程结构一致性的情况下,判断演化构件在演化前后的内部行为一致性;最后,通过对一个构件实例的完整分析,详细描述了该判定方法,并验证了其可行性。     

SaaS交付平台多租户数据管理模型研究

随着SaaS(Software as a Service,即SaaS)应用交付平台租户数目及信息数据量呈几何曲线性增长,平台数据管理正处于由单数据节点往云中多数据节点转变的必然阶段,本文以软件即服务应用交付平台中多租户云数据管理为目标,对SaaS平台数据模型、云中放置策略、租户索引等进行了深入研究,提出一种SaaS平台多租户虚拟化方式及高效映射转换的数据分层模型,通过租户无关的应用数据模型为开发商屏蔽多租户云数据管理技术细节,通过租户逻辑模型支持租户按需定制数据模式以及各业务系统数据之间的共享关系,通过逻辑存储模型为平台运营商屏蔽了云中数据节点伸缩技术,解决了SaaS应用生命周期云数据管理技术瓶颈问题.     

SaaS模式多租户数据存贮模型的研究与实现

SaaS模式引入了多租户环境特征,在新的环境下,数据库层存贮设计面临租户数据隔离问题和租户数据弹性扩展问题.主要研究了多租户环境下的数据存储模式,提出了“共享数据库共享Schema存贮数据、独立Schema访问”的多租户数据存贮与访问模型,该模型将SaaS应用的数据存贮和数据访问的Schema进行分离,有效解决了“租户数据隔离性低”的问题;同时,提出了一种以XML为基础的多租户数据扩展模型,该扩展模型很好地解决了“租户数据弹性扩展”的问题.在此基础上,详细描述了这两个模型在SQL Server数据库的实现方案,实例结果证明了所述方法的灵活性和可行性.     

SaaS模式下多租户层次定制模型研究

SaaS的典型特征是“单实例多租户”。为提高多个租户定制同一SaaS应用的效率,避免多个租户在对同一SaaS应用进行定制时对相同定制内容的重复定制,提出了层次定制模型。利用树形数据模型和交运算思想,最大限度地计算出多个租户共性的定制内容,将相同的定制内容只需一次定制供多个租户共享,层次定制模型在层次定制的基础上不仅满足了租户的个性化定制需求,而且提高了定制效率,降低了定制复杂度。仿真实验结果证实了该层次定制模型减少了租户的定制时间,节省了存储空间     

对SaaS模式软件服务链的分析

SaaS模式不同于ASP模式之处在于：首先,SaaS模式从用户的角度来看待软件,关注用户的真实需求——服务,而ASP模式关注的是软件托管：其次,SaaS模式在面向服务的软件架构思想上发展起来,它可以为多个用户提供多对一的多租户服务,有利于产生规模效应,随着租户数量的增加,每租户的服务成本反而下降,而ASP模式只能提供一对一的托管服务,无法产生规模效应,     

SaaS平台访问控制研究

Saas平台软件交付模式将应用软件以服务的形式提供给客户,可缩减硬件采购、系统管理上的开销。由于租户数据统一存储于服务提供商处,如何在维持较高资源利用率的同时保障租户的数据安全是一个挑战性问题。针对租户角色复杂、各租户数据共存而又独立访问的要求,结合基于角色的访问控制模型,构建了支持多租户、多角色、方便租户权限管理的SaaS平台的访问控制模型。和传统基于角色的访问控制模型相比,该模型增加了租户的概念,以租户为基本单元实施平台的访问控制,提高了SaaS平台访问控制的安全性和可管理性。分析了用户访问SaaS平台的具体流程,给出了模型的形式语言描述,实现了SaaS餐饮管理平台访问控制的数据库的物理模型,为SaaS平台开发提供参考。     

Customer on-boarding strategies for cloud computing services with dynamic service-level agreements

A multi-tenant software as a service (SaaS) provider has to meet the needs of several tenants which adopt its services with diverse business requirements. The tenant needs vary widely with time, and the provider has to account for such fluctuations by suitable provisioning at its end. Handling this elasticity arising out of the tenant base is one of the key challenges for the SaaS provider. In this paper, we study the problem specifically in the SaaS context with the idea built around license provisioning in a tenant–provider perspective. For a given set of tenants with diverse license requirements, it is important to analyze whether there is any way to on-board them such that all constraints laid out as part of the service-level agreement can be honored. The total number of licenses available with the provider plays a crucial role in answering this question. We propose an intuitive model of elasticity that can capture anticipated license need variations at the tenant end. We propose an ILP-based approach for solving this schedulability problem for a collection of tenants. We also propose a simple-minded greedy heuristic to solve the on-boarding problem with elasticity constraints. Results show that our approach gives acceptable performance.     

面向多租约SaaS应用的负载均衡机制研究与实现

随着云计算的普及,SaaS作为一种新的软件交付模式得到了越来越广泛地关注.为了支持高速业务发展带来的大量用户的访问请求,多租约SaaS应用需要负载均衡机制以支持可扩展性.本文从对多租约SanS应用用户需求的分析入手,提出了一种面向租约功能类型的服务器负载模型和面向租约用户非功能需求的执行请求按需分配算法,设计了一个面向多租约SanS 应用的负载均衡系统.实验表明本文提出的面向多租约SaaS应用的负载均衡机制能在满足不同租约用户需求的同时提高系统整体执行效率.     

The QoS-based MCDM system for SaaS ERP applications with Social Network

Cloud computing delivers almost all of its services including software, user’s data, system resources, processes and their computation over the Internet. Cloud computing consists of three main classes; Software as a Service, Infrastructure as a Service and Platform as a Service. Using Software as a Service (SaaS), users are able to rent application software and databases which they then install onto their computer in the traditional way. In the Enterprise Resource Planning (ERP) system, the system service environment changed so as to allow the application of the SaaS in the cloud computing environment. This change was implemented in order to provide the ERP system service to users in a cheaper, more convenient and efficient form through the Internet as opposed to having to set up their own computer. Recently many SaaS ERP packages are available on the Internet. For this reason, it is very difficult for users to find the SaaS ERP package that would best suit their requirements. The QoS (Quality of Service) model can provide a solution to this problem. However, according to recent research, not only quality attributes’ identification for SaaS ERP, but also a process for finding and recommending software in the cloud computing environment, has proved to be lacking. In this paper, we propose a QoS model for SaaS ERP. The proposed QoS model consists of 6 criteria; Functionality, Reliability, Usability, Efficiency, Maintainability and Business. Using this QoS model, we propose a Multi Criteria Decision Making (MCDM) system that finds the best fit for the SaaS ERP in the cloud computing environment and makes recommendations to users in priority order. In order to organize the quality clusters, we organized an expert group and got their opinion to organize the quality clusters using Social Network Group. Social Networks can be used efficiently to get opinion by various types of expert groups. In order to establish the priority, we used pairwise comparisons to calculate the priority weights of each quality attribute while accounting for their interrelation. Finally, using the quality network model and priority weights, this study evaluated three types of SaaS ERPs. Our results show how to find the most suitable SaaS ERPs according to their correlation with the criteria and to recommend a SaaS ERP package which best suits users’ needs.     

SaaS模式下的信息安全探讨

SaaS(软件即服务)是一种通过互联网提供应用服务的方式,客户可以根据自己实际需求,通过互联网向SaaS提供商定购所需的应用软件服务,并通过互联网获得SaaS提供商提供的服务。SaaS模式彻底颠覆了传统软件的运营和交付模式,免除了中小企业购买、构建和维护基础设施和应用程序的巨大投资成本。但它存在着较大的安全风险,如在可靠性、稳定性、安全性上,尤其是在财务数据和隐私方面。论文首先分析了SaaS的特点和不足,并提出了增强SaaS模式下信息安全的几种方法。     

Optimization-based resource allocation for software as a service application in cloud computing

Software as a service (SaaS) is a software that is developed and hosted by the SaaS vendor. SaaS cloud provides software as services to the users through the internet. To provide good quality of service for the user, the SaaS relies on the resources leased from infrastructure as a service cloud providers. As the SaaS services rapidly expand their application scopes, it is important to optimize resource allocation in SaaS cloud. The paper presents optimization-based resource allocation approach for software as a service application in cloud. The paper uses optimization decomposition approach to solve cloud resource allocation for satisfying the cloud user’s needs and the profits of the cloud providers. The paper also proposes a SaaS cloud resource allocation algorithm. The experiments are designed to compare the performance of the proposed algorithm with other two related algorithms.     

Scalable SaaS Indexing Algorithms with Automated Redundancy and Recovery Management

Software-as-a-Service (SaaS) is a new software delivery model with Multi-Tenancy Architecture (MTA). An SaaS system is often mission critical as it often supports a large number of tenants, and each tenant supports a large number of users. This paper proposes a scalable index management algorithm based on B+ tree but with automated redundancy and recovery management as the tree maintains two copies of data. The redundancy and recovery management is done at the SaaS level as data are duplicated with tenant information rather than at the PaaS level where data are duplicated in chunks. Using this approach, an SaaS system can scale out or in based on the dynamic workload. This paper also uses tenant similarity measures to cluster tenants in a multi-level scalability architecture where similar tenants can be grouped together for effcient processing. The scalability mechanism also includes an automated migration strategies to enhance the SaaS performance. The proposed scheme with automated recovery and scalability has been simulated, the results show that the proposed algorithm can scale well with increasing workloads.     

SDSN@RT: A middleware environment for single-instance multitenant cloud applications

With the single-instance multitenancy (SIMT) model for composite Software-as-a-Service (SaaS) applications, a single composite application instance can host multiple tenants, yielding the benefits of better service and resource utilization and reduced operational cost for the SaaS provider. An SIMT application needs to share services and their aggregation (the application) among its tenants while supporting variations in the functional and performance requirements of the tenants. The SaaS provider requires a middleware environment that can deploy, enact, and manage a designed SIMT application, to achieve the varied requirements of the different tenants in a controlled manner. This paper presents the SDSN@RT (software-defined service networks at runtime) middleware environment that can meet the aforementioned requirements. SDSN@RT represents an SIMT composite cloud application as a multitenant service network, where the same service network simultaneously hosts a set of virtual service networks, one for each tenant. A service network connects a set of services and coordinates the interactions between them. A virtual service network realizes the requirements for a specific tenant and can be deployed, configured, and logically isolated in the service network at runtime. SDSN@RT also supports the monitoring and runtime changes of the deployed multitenant service networks. We show the feasibility of SDSN@RT with a prototype implementation and demonstrate its capabilities to host SIMT applications and support their changes with a case study. The performance study of the prototype implementation shows that the runtime capabilities of our middleware incur little overhead.