SaaS服务供应商在提供免费试用服务时的定价策略

基于SaaS服务相关的背景构建两周期博弈模型,研究SaaS服务供应商在提供免费试用服务时使用量、交易成本、更新水平、折现率、免费试用时间这5类因素如何影响SaaS服务供应商的计费方式和定价策略.研究发现:在用户感知达到SaaS服务的真实质量前,最优利润均随着免费试用时间增加而增加.不论采用何种价格歧视策略,当使用量较高且交易成本较高时,SaaS服务供应商采取按阶段收费的方式获利更高,当使用量和交易成本处于一种均衡状态时,SaaS服务供应商通过两种定价方式获利相仿;当使用量较低且交易成本也较低时,SaaS服务供应商采取按使用量收费的方式获利更高.采取按阶段收费方式,折现率较高时,基于行为的价格歧视策略最优;折现率较低时,跨期价格歧视更有利可图.采取按使用量收费方式时,跨期价格歧视最优.

面向在线率差异的SaaS订阅限额及资源配置组合优化

软件即服务(softuare as a service,SaaS)是一种让用户通过支付订阅费来获得软件访问权的云服务模式。由于其业务的多样性,用户对不同软件的在线访问率存在很大差异,所以不同软件所消耗的云计算资源也存在差异。为避免违反服务等级协议(service level agreement,SLA)而产生违约赔付的风险,SaaS运营商不仅要优化各种软件的计算资源配置,还要对各类软件的订阅量加以限额。在考虑SLA限制的基础上,构建了一个以收益最大化为目标的有资源约束的非线性整数规划模型。由于模型计算的复杂性,其无法在多项式时间内求解,所以设计了基于Q学习-粒子群(particle swarm optimizoction,PSO)的融合算法来求解该NP难题。该算法将Q-学习嵌入到PSO中,动态调整PSO参数,从而避免直接使用PSO时会面临的局部最优陷阱和计算效率低下的问题。仿真实验验证了在不同场景下模型及算法的有效性,结果表明该算法可在云计算资源有限的条件下,以较高的求解效率获得收益更高的订阅限额及资源配置方案。其中,当处于需求波动大的情境下时,运营商应尽可能地降低软件的资源争用比,通过配置足量的虚拟机资源并设定严格的订阅限额来保障软件的服务质量,减少违约赔付成本;相反,当处于需求波动小的情境下时,运营商可以提高软件的资源争用比,通过放宽订阅限额来抢占更大的市场,实现收益最大化。

Threshold-Based Software-Defined Networking(SDN)Solution for Healthcare Systems against Intrusion Attacks

The healthcare sector holds valuable and sensitive data.The amount of this data and the need to handle,exchange,and protect it,has been increasing at a fast pace.Due to their nature,software-defined networks(SDNs)are widely used in healthcare systems,as they ensure effective resource utilization,safety,great network management,and monitoring.In this sector,due to the value of thedata,SDNs faceamajor challengeposed byawide range of attacks,such as distributed denial of service(DDoS)and probe attacks.These attacks reduce network performance,causing the degradation of different key performance indicators(KPIs)or,in the worst cases,a network failure which can threaten human lives.This can be significant,especially with the current expansion of portable healthcare that supports mobile and wireless devices for what is called mobile health,or m-health.In this study,we examine the effectiveness of using SDNs for defense against DDoS,as well as their effects on different network KPIs under various scenarios.We propose a threshold-based DDoS classifier(TBDC)technique to classify DDoS attacks in healthcare SDNs,aiming to block traffic considered a hazard in the form of a DDoS attack.We then evaluate the accuracy and performance of the proposed TBDC approach.Our technique shows outstanding performance,increasing the mean throughput by 190.3%,reducing the mean delay by 95%,and reducing packet loss by 99.7%relative to normal,with DDoS attack traffic.

Hybrid Chameleon and Honey Badger Optimization Algorithm for QoS-Based Cloud Service Composition Problem

Cloud computing facilitates the great potentiality of storing and managing remote access to services in terms of software as a service(SaaS).Several organizations have moved towards outsourcing over the cloud to reduce the burden on local resources.In this context,the metaheuristic optimization method is determined to be highly suitable for selecting appropriate services that comply with the requirements of the client’s requests,as the services stored over the cloud are too complex and scalable.To achieve better service composition,the parameters of Quality of Service(QoS)related to each service considered to be the best resource need to be selected and optimized for attaining potential services over the cloud.Thus,the cloud service composition needs to concentrate on the selection and integration of services over the cloud to satisfy the client’s requests.In this paper,a Hybrid Chameleon and Honey Badger Optimization Algorithm(HCHBOA)-based cloud service composition scheme is presented for achieving efficient services with satisfying the requirements ofQoS over the cloud.This proposed HCHBOA integrated the merits of the Chameleon Search Algorithm(CSA)and Honey Badger Optimization Algorithm(HBOA)for balancing the tradeoff between the rate of exploration and exploitation.It specifically used HBOA for tuning the parameters of CSA automatically so that CSA could adapt its performance depending on its incorporated tuning factors.The experimental results of the proposed HCHBOA with experimental datasets exhibited its predominance by improving the response time by 21.38%,availability by 20.93%and reliability by 19.31%with a minimized execution time of 23.18%,compared to the baseline cloud service composition schemes used for investigation.

基于SAAS的LVC装备试验资源实时调度模型研究

真实虚拟构造仿真为装备体系试验提供了有效技术手段。针对试验中大量异构仿真资源对象间的交互难以满足试验任务实时性需求问题,开展仿真资源实时调度模型研究。分析模型的功能组成,将调度模型划分为远程方法通信实现、远程方法云服务、优化调度策略3个子模型,分析各子模型的功能及其之间的关系,给出模型运行的步骤以及实现原理,并构建标准实验环境,验证模型算法。实验表明,在模型时延要求小于1 ms的标准测试环境下,云服务环境最多可承载大约30个节点同时提出订阅需求,并且调度成功率均大于98.5%,丢包率为0,符合模型性能要求。

Business Intelligence as a Service——SaaS BI Introduction and Recommendations

Characterized as automated access,analysis,management,improvement,identification,and efficiency,SaaS BI has played a significant role recently. This essay presents information about SaaS BI,such as,the generic reason for prevalent,advantages and limitations of SaaS BI,current market overview,tendency of development of SaaS BI,and applications in business. This paper uses the literature study and descriptive study methods in order to analysis the influence and functions of SaaS BI to the businesses and coping strategies.

A Performance Fault Diagnosis Method for SaaS Software Based on GBDT Algorithm

SaaS software that provides services through cloud platform has been more widely used nowadays.However,when SaaS software is running,it will suffer from performance fault due to factors such as the software structural design or complex environments.It is a major challenge that how to diagnose software quickly and accurately when the performance fault occurs.For this challenge,we propose a novel performance fault diagnosis method for SaaS software based on GBDT(Gradient Boosting Decision Tree)algorithm.In particular,we leverage the monitoring mean to obtain the performance log and warning log when the SaaS software system runs,and establish the performance fault type set and determine performance log feature.We also perform performance fault type annotation for the performance log combined with the analysis result of the warning log.Moreover,we deal with the incomplete performance log and the type non-equalization problem by using the mean filling for the same type and combination of SMOTE(Synthetic Minority Oversampling Technique)and undersampling methods.Finally,we conduct an empirical study combined with the disaster reduction system deployed on the cloud platform,and it demonstrates that the proposed method has high efficiency and accuracy for the performance diagnosis when SaaS software system runs.

面向铁路行业的多租户SaaS云教育培训平台设计

面向铁路行业的云教育培训平台是数字经济时代支撑铁路行业企业教育培训高质量发展的重要基础。文章分析了铁路行业企业由内部管理需求主导的三种教育培训系统服务模式及其在响应行业企业教育培训信息化需求方面存在的不足,提出基于共享服务的铁路教育培训信息化服务模式,以及适应用户不同网络环境的多租户Saa S云教育培训平台架构模式、主要结构和基础业务功能,包括培训管理、在线学习、在线考试、线下办班、教育管理等,进而为提升铁路行业企业教育培训信息化水平提供支持。

Naive Echo-State-Network Based Services Awareness Algorithm of Software Defined Optical Networks

As internet services newly emerge with diversity and complexity, great challenges and demands are presented to the Open Flow controlled software defined optical networks(SDON) to achieve better match between services and SDON. With this aim, this paper proposes a naive Echo-State-Network(Naive-ESN) based services awareness algorithm of the software defined optical network, where the naive ESN model adopts the ring topology structure and generates the probability output result to determine the Qo S policy of SDON. Moreover, the Naive-ESN engine is also designed in controller node of SDON to perform services awareness by obtaining service traffic features from data plan, together with some necessary extension of the Open Flow protocol. Test results show that the proposed approach is able to improved services-oriented supporting ability of SDON.

基于SaaS的大坝安全在线监控系统研发与应用

通过分析当前大坝安全监测系统存在的问题,指出了基于SaaS(软件即服务)的大坝安全在线监控系统建设的必要性。在需求分析基础上进行了系统功能设计及研发,系统在多座水电站进行了推广应用,开创了基于工程安全大数据的服务新模式,提升了水库大坝安全管理水平。

Service Function Chain in Small Satellite-Based Software Defined Satellite Networks

Software Defined Satellite Networks(SDSN) are proposed to solve the problems in traditional satellite networks, such as time-consuming configuration and inflexible traffic scheduling. The emerging application of small satellite and research of SDSN make it possible for satellite networks to provide flexible network services. Service Function Chain(SFC) can satisfy this need. In this paper, we are motivated to investigate applying SFC in the small satellite-based SDSN for service delivery. We introduce the structure of the multi-layer constellation-based SDSN. Then, we describe two deployment patterns of SFC in SDSN, the Multi-Domain(MD) pattern and the Satellite Formation(SF) pattern. We propose two algorithms, SFP-MD, and SFP-SF, to calculate the Service Function Path(SFP). We implement the algorithms and conduct contrast experiments in our prototype. Finally, we summarize the applicable conditions of two deployment patterns according to the experimental results in terms of hops, delay, and packet loss rate.

A Software Service Framework Model Based on Agent

This paper presents an agent-based software service framework model called ASF, and defines the basic concepts and structure of ASF model. It also describes the management and process mechanisms in ASF model.

SaaS流程可配置模型的研究与实现

目前针对软件即服务SaaS(Software as a Service)的可配置策略还没有完全形成成熟的理论。借鉴已有技术,提出和描述基于组件组装定制服务的一种配置模型。该配置模型允许用户对服务进行建模,根据自己特定的业务流程,基于相同的服务组件,通过定义不同的数据关联和约束规则实现服务流程定制。最后通过两个业务需求不同的服务的配置实例,证明所描述方法的灵活性和可行性。

基于SaaS的CALIS共享服务实践

SaaS集硬件、软件和服务于一体,通过规模化建设降低用户成本,对我国图书馆全面实施现代化管理,加快信息资源共建共享,提高文献服务保障水平具有重要的现实意义。2009年,SaaS进入图书馆领域,并引起我国图书馆界对SaaS服务的强烈关注。2011年,CALIS构架了一个标准化、低成本、自适应、可扩展的、基于SaaS的共享服务平台。通过该平台,可以支撑数百以至上千的CALIS成员馆在同一个应用体系内实现业务操作。CALIS馆际互借与文献传递系统共享版作为CALIS共享服务平台的一个实际应用范例,由于其低建设投入、低维护成本、低应用门槛等优势,推出半年后就在全国400多家图书馆得到广泛应用。

基于SaaS的弹性云平台优化调度策略设计

云计算平台利用虚拟化技术使软件应用变得更有效率的同时,也给资源管理和服务调度带来了挑战。在研究了软件服务(SaaS)与基础设施服务(IaaS)调度的区别基础上,重点考虑SaaS层的资源调度,提出基于随机理论的调度模型,把该层调度描述成一种多目标的优化问题。除了服务质量的要求,还考虑了弹性这一云服务的重要特性,并提供了任务调度与弹性服务副本的匹配策略。实验表明本调度机制的设计优化了云平台的整体性能,达到了较好的负载均衡与资源利用率。

面向SaaS应用的业务逻辑定制框架的研究与实现

SaaS(software as a service,软件即服务)是一种全球兴起的创新的软件服务模式,它的出现对中小企业的信息化产生了深远影响。目前面向SaaS应用的业务逻辑在线定制方法存在着定制复杂性高、可定制内容有限等缺点。为了解决这些问题,采用了基于领域工程的业务规则模板的方法,提出了适合SaaS应用的业务逻辑定制框架,兼顾了应用的易用性及性能。案例表明了此框架的有效性。

支持多租约个性化业务定制的SaaS业务-租约模型

面对多租约日益增长的个性化业务需求,目前大多数业务模型存在不能够灵活、简单地满足租约的个性化定制的问题,因此,提出了基于ex-WSCL的SaaS业务-租约模型(exWSCL-SBTM)作为SaaS业务流程描述方法.利用该模型以交互及变迁组织业务流程的特点,以及将业务端与租约端相分离的方式,能够提高多租约个性化业务定制的方便性和灵活性.在此基础上,给出了个性化业务定制操作行为的定义,以及提出了基于SBTM的多租约个性化业务定制框架.

基于SaaS的软件开发模式在高校中的应用研究与实践

介绍了SaaS的概念.综述高校SaaS应用的进展与效果,分析了SaaS应用进展缓慢的原因.以北京大学自主研发的两个SaaS应用——网上支付接口服务系统以及通用注册系统为例,提出了在高校内部应用SaaS的一种新途径和解决方案,为高校信息化中如何应用SaaS提供成功范例.

基于混合遗传模拟退火算法的SaaS构件优化放置

目前,对于SaaS优化放置问题的研究都是假定云环境中的虚拟机的种类和数量都是确定的,即,在限定的资源范围内进行优化.然而,在公有云环境下,SaaS提供者所需要的云资源数量是不确定的,其需要根据Iaa S提供者所提供的虚拟机种类以及被部署的SaaS构件的资源需求来确定.为此,站在SaaS提供者角度,提出一种新的SaaS构件优化放置问题模型,并采用混合遗传模拟退火算法(hybrid genetic and simulated annealing algorithm,简称HGSA)对该问题进行求解.HGSA结合了遗传算法和模拟退火算法的优点,克服了遗传算法收敛速度慢和模拟退火算法容易陷入局部最优的缺点,与单独使用遗传算法和模拟退火算法相比,实验结果表明,HGSA在求解SaaS构件优化放置问题方面具有更高的求解质量.所提出的方法为SaaS服务模式的大规模应用提供了理论与方法的支撑.

开放SaaS产业服务平台模型与体系结构

为解决企业用户对信息系统服务化、可编程等多样化需求,将开放系统设计思想与SaaS(软件即服务)平台技术相结合,提出了开放SaaS产业服务平台(OSISP)的概念,设计了产业服务平台业务架构,并对平台角色、业务集成模型进行了抽象与形式化建模;在此基础上,按照分层体系结构的设计思想,设计了由基础层、平台层、系统层、用户层以及系统管理和标准体系构成的系统体系结构.通过系统设计,将产业服务平台模型与体系结构应用于汽车供应链协同平台,提高了系统的开放性、用户参与系统建设及使用的积极性.