Web service based spatial forest information system using an open source software approach

For technical and other reasons there is a dilemma that data providers cannot find an appropriate way to redistribute spatial forest data and data users who need spatial data cannot access and integrate available forest resources information. To overcome this dilemma, this paper proposed a spatial forest information system based on Web service using an open source software approach. With Web service based architecture, the system can enable interoperability, integrate Web services from other application servers, reuse codes, and shorten the development time and cost. At the same time, it is possible to extend the local system to a regional or national spatial forest information system. The growth of Open Source Software （OSS） provides an alternative choice to proprietary software for operating systems, web servers, Web-based GIS applications and database management systems. Using open source software to develop spatial forest information systems can greatly reduce the cost while providing high performance and sharing spatial forest information. We chose open source software to build a prototype system for Xixia County, Henan Province, China. By integrating OSS packages Deegree and UMN MapServer which are compliant to the OGC open specifications, the prototype system enables users to access spatial forest information and travelling information of Xixia County which come from two different data servers via a standard Web browser and promotes spatial forest information sharing.

微服务架构的一体化性能监控SaaS云设计与实现

以往独立、分散式的软硬件监控管理方式已经难以适应实时测控数据处理对设备的可靠性需求。基于微服务(Microservice)体系架构,依托云平台设计并实现一体化性能监控系统,通过云平台提供的SaaS(Software as a Service)云服务Web接口可以透明地对中心的各类设备、服务进行分类管理,实现监控数据收集分析和故障自动识别报警等功能。实验表明,基于微服务架构的一体化性能监控SaaS云服务对被监控设备或服务的性能损耗和资源占用少、数据获取和推送速度快、异常事件触发精准、处理闭环,能够较好地满足实时测控中心对设备和服务的监控需求。

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.

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.

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.

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.

Extracting SOA Candidate Software Services from an Organization’s Object Oriented Models

Class diagrams and use case models are system models that are used to analyze, design and model object oriented systems. In this era of agile computing, service-oriented architecture has become increasingly popular for achieving efficient and agile business solutions that can maintain changes demanded by the business world. This paper proposes a methodology to identify services from a set of class diagrams and use case models in order to generate a service oriented model. An extensive evaluation of the generated services has shown that these services conform to the principles of Service Oriented Architecture (SOA), and provide a straightforward methodology, which can reuse the valuable business logic that resides within legacy applications to migrate to SOA-based systems.

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.

Application of Capability Maturity Model Integration to Innovation Management for Software and Service Companies

To look through innovation management in small project-based firms, such as software engineering companies, which are service firms that conduct projects for their clients, capability maturity model integration （CMMI） is introduced. It is a process improvement approach that provides organizations with the essential elements of effective processes. Taking ABC Software Company as an example, the performances before and after the introduction of CMMI in the firm were compared. The results indicated that after two years of application, the productivity increased 92%, and the ability of detecting errors improved 26.45% ; while the rate of faults and the cost of software development dropped 12.45% and 77.55%, respectively. To conclude, small project-based firms benefit a lot if they take CMMI into their process of innovation management, particularly for those R＆D firms, since the implementation of CMMI leads them to a promising future with higher efficiency and better effects.

Research on Software Architecture of the Extensible Services Router

With the rapid development of network technology, it is increasingly important to dynamically upgrade router’s software. In this paper, the authors present new software architecture to be applied to extensible services router. The novel feature of the architecture is the ability to dynamically load and configure extensible components at run time. Each component implements one function such as packets classification, packets scheduling and routing protocol. We design a simple configuration language (ESRCL) to configure and manage the router. The architecture can be configured according to the packet flows. At present, a prototype system based on highly efficient router operating system (HEROS) has been finished.

Assessing Internal Software Quality Attributes of the Object-Oriented and Service-Oriented Software Development Paradigms: A Comparative Study

Service-Oriented Architecture (SOA) is becoming the dominant approach for developing and organizing distributed enterprise-wide applications. Although the concepts of SOA have been extensively described in the literature and in-dustry, the effects of adopting SOA on software quality are still unclear. The aim of the paper is to analyze how adopt-ing SOA can affect software quality as opposed to the Object-Oriented (OO) paradigm and expose the differential implications of adopting both paradigms on software quality. The paper provides a brief introduction of the architectural differences between the Service-Oriented (SO) and OO paradigms and a description of internal software quality metrics used for the comparison. The effects and differences are exposed by providing a case study architected for both paradigms. The quantitative measure concluded in the paper showed that a software system developed using SOA approach provides higher reusability and lower coupling among software modules, but at the same time higher complexity than those of the OO approach. It was also found that some of the existing OO software quality metrics are inapplicable to SOA software systems. As a consequence, new metrics need to be developed specifically to SOA software systems.

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.

Artificial Intelligence Model for Software Reusability Prediction System

The most significant invention made in recent years to serve various applications is software.Developing a faultless software system requires the soft-ware system design to be resilient.To make the software design more efficient,it is essential to assess the reusability of the components used.This paper proposes a software reusability prediction model named Flexible Random Fit(FRF)based on aging resilience for a Service Net(SN)software system.The reusability predic-tion model is developed based on a multilevel optimization technique based on software characteristics such as cohesion,coupling,and complexity.Metrics are obtained from the SN software system,which is then subjected to min-max nor-malization to avoid any saturation during the learning process.The feature extrac-tion process is made more feasible by enriching the data quality via outlier detection.The reusability of the classes is estimated based on a tool called Soft Audit.Software reusability can be predicted more effectively based on the pro-posed FRF-ANN(Flexible Random Fit-Artificial Neural Network)algorithm.Performance evaluation shows that the proposed algorithm outperforms all the other techniques,thus ensuring the optimization of software reusability based on aging resilient.The model is then tested using constraint-based testing techni-ques to make sure that it is perfect at optimizing and making predictions.

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。

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。

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。

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。