Requirements-driven data engineering

In the early 1990s, the effectiveness and efficiency of the information systems (IS) supporting the US Department of Defense's non-combat operations was questioned. As had many organizations, the support had evolved into multiple, redundant, unintegrated, undocumented, stove-piped IS. These systems require unnecessarily large non-combat IS expenses, supporting war fighting efforts. Lack of integration hindered the Department from effectively providing mission support information. DOD's efforts to re-engineer the non-combat IS is one of the first attempts to apply requirements-driven data engineering to a large systems environment. Its application to DOD's non-combat IS data environment has provided tangible results: (1) from the top down, an enterprise model (EM) now specifies Department-wide requirements capable of guiding future integration and development efforts; (2) from the bottom up, non-combat IS are being significantly reduced, simplifying the overall problem; and (3) data quality engineering methods, guided by the EM, are being developed and applied to the remaining IS. This success has achieved a prerequisite necessary to increase the effectiveness and efficiency of the systems.     

软件功能需求驱动的商业构件评估

提出了一种由软件功能需求驱动的评估和选择商业构件（COTS）的新方法。该方法首先基于FCD方法将系统的功能需求分解到各个功能模块。对每个功能模块,识别出一组候选构件,用户根据给定的模板评价候选构件对功能需求的满足度和构件功能的有用性。最优构件组合在给定成本约束下,具有最大的全局需求满足度。选择最优组合的过程是求解一系列优化问题的过程。最后用一个例子进一步说明和验证了该方法。     

Requirements-driven database systems benchmark method

Benchmarks are the vital tools in the performance measurement, evaluation, and comparison of relational database management systems (RDBMS). Standard benchmarks such as the TP1, TPC-A, TPC-B, TPC-C, TPC-D, TPC-H, TPC-R, TPC-W, Wisconsin, and AS³AP benchmarks have been used to assess the performance of relational database management systems. These benchmarks are synthetic and domain-specific. Test results from these benchmarks are estimates of possible system performance for certain pre-determined application types. Database system performance on actual database domain may vary significantly from those in the standard benchmarks. In this paper, we describe a new benchmark method that is computer-assisted and developed from the perspective of the user's requirements.     

基于岗位需求驱动的Java实训课程体系构建研究

针对目前高职院校实训课程体系技能培养不能很好满足企业相应岗位需求的问题,以自身企业行业实践和校企合作开发经验为基础,提出从岗位需求分析出发,涵盖设计指导原则、实训框架设计、阶段项目考核方式的实训课程体系构建模式,实践教学结果证明,该模式在学生技能培养提高和岗位适应能力方面都有非常明显的效果。     

Requirements-driven incremental adoption of variability management techniques and tools: an industrial experience report

In theory, software product line engineering has reached a mature state. In practice though, implementing a variability management approach remains a tough case-by-case challenge for any organization. To tame the complexity of this undertaking, it is inevitable to handle variability from multiple perspectives and to manage variability consistently across artifacts, tools, and workflows. Especially, a solid understanding and management of the requirements to be met by the products is an inevitable prerequisite. In this article, we share experiences from the ongoing incremental adoption of explicit variability management at TRW Automotive’s department for automotive slip control systems—located in Koblenz, Germany. On the technical side, the three key drivers of this adoption effort are (a) domain modeling and scoping, (b) handling of variability in requirements and (c) tighter integration of software engineering focus areas (e.g., domain modeling, requirements engineering, architectural modeling) to make use of variability-related data. In addition to implementation challenges with using and integrating concrete third-party tools, social and workflow-related issues are covered as well. The lessons learned are presented, discussed, and thoroughly compared with the state of the art in research.     

一种多层次的追踪器部署策略*

结合K-剪枝算法,提出了一种多层次追踪器部署策略,在第一层的追踪器部署时选择较大的k值进行剪枝,以较小的改造代价部署相对较少的追踪器,来进行关键追踪,在第二层通过二次剪枝,以部署剪枝域内追踪器,对无法通过第一层次节点进行追踪的攻击进行再次追踪,确定攻击来源。该方案能够以较低的网络改造代价以及网络性能代价完成准确追踪。理论分析以及仿真结果验证了该方案的正确性和有效性。     

基于多样性的微服务韧性部署机制

针对微服务架构软件系统的共享漏洞问题,面向微服务下的部署工作进行了研究,提出了一种面向韧性抗毁的多样性微服务动态部署策略,能够利用多样性部署特点,根据资源约束情况部署多样化的微服务组件,兼顾集中式部署与负载均衡的优势,有效缓解了同构性带来的问题,增强了软件系统的韧性能力。在此基础上实现了一种最小负载部署算法(Load-Min),并通过实验和六种算法进行了比较,实验结果显示Load-Min部署算法相较其他经典算法,在资源利用效能、系统安全性等方面均有较大的提升。     

一种软件智能部署方法的研究

研究了能够根据不同环境自动调整软件部署过程的软件智能部署问题。介绍并分析现有软件的部署工具,提出了软件智能部署的概念、整体框架和部署工作流程。介绍并分析了软件规范化描述语言和客户端信息的模型描述方法。在此基础之上,提出了一种能够根据环境差异,自动调整软件部署过程的软件智能部署算法。最后,对比并分析了软件智能部署实际应用效果。     

云计算环境下虚拟机部署策略的优化

针对虚拟机群在云计算平台动态部署过程中现有的部署机制所存在的局限性,提出一种优化的部署模型。首先建立预分块存储的分布式预定制虚拟机全镜像模板库;然后由调度中心依据调度策略选择适当的宿主机,并通过多源并行传输的方式提高部署效率;最后由对应的虚拟机监视器完成实例化任务。实验结果显示,在不同的虚拟机群部署规模下,单台虚拟机的平均部署时间较以往缩短3%～45%。实验结果验证了该模型的有效性。     

P3P deployment on websites

We studied the deployment of computer-readable privacy policies encoded using the standard W3C platform for privacy preferences (P3P) format to inform questions about P3P’s usefulness to end users and researchers. We found that P3P adoption is increasing overall and that P3P adoption rates greatly vary across industries. We found that P3P had been deployed on 10% of the sites returned in the top-20 results of typical searches, and on 21% of the sites returned in the top-20 results of e-commerce searches. We examined a set of over 5000 websites in both 2003 and 2006 and found that P3P deployment among these sites increased over that time period, although we observed decreases in some sectors. In the Fall of 2007 we observed 470 new P3P policies created over a 2-month period. We found high rates of syntax errors among P3P policies, but much lower rates of critical errors that prevent a P3P user agent from interpreting them. We also found that most P3P policies have discrepancies with their natural language counterparts. Some of these discrepancies can be attributed to ambiguities, while others cause the two policies to have completely different meanings. Finally, we show that the privacy policies of P3P-enabled popular websites are similar to the privacy policies of popular websites that do not use P3P.     

Reliability-driven deployment optimization for embedded systems

One of the crucial aspects that influence reliability of embedded systems is the deployment of software components to hardware nodes. If the hardware architecture is designed prior to the customized software architecture, which is often the case in product-line manufacturing (e.g. in the automotive domain), the system architect needs to resolve a nontrivial task of finding a (near-)optimal deployment balancing the reliabilities of individual services implemented on the software level.In this paper, we introduce an approach to automate this task. As distinct to related approaches, which typically stay with quantification of reliability for a specific deployment, we target multi-criteria optimization and provide the architect with near-optimal (non-dominated) deployment alternatives with respect to service reliabilities. Toward this goal, we annotate the software and hardware architecture with necessary reliability-relevant attributes, design a method to quantify the quality of individual deployment alternatives, and implement the approach employing an evolutionary algorithm.     

国家航空电信网的建设研究

航空电信网是CNS/ATM系统的重要组成部分,是下一代航空通信系统的全面解决方案.建立一个全球化的、开放结构的互联网络,使空中交通管制系统、航空公司、航空行政管理部门的各种网络有机地连接成一个整体,达到系统互联、信息互通、资源共享的目标是目前研究的热点问题.通过对航空电信网的基本概念、网络组成、协议结构等特点的阐述,分析了当前航空电信网研究中存在的关键问题.结合现行空中管制体制建设的特点,对航空电信网建设提出建议.     

Toward architecture-based context-aware deployment and adaptation

Software systems are increasingly expected to dynamically self-adapt to the changing environments. One of the main adaptation mechanisms is dynamic recomposition of application components. This paper addresses the key issues that arise when context knowledge is used to steer the run-time (re)composition process so as to match the new environmental conditions. In order to integrate such knowledge into this process, A Continuous Context-Aware Deployment and Adaptation (ACCADA) framework is proposed. To support run-time component composition, the essential runtime abstractions of the underlying component model are studied. By using a layered modeling approach, our framework gradually incorporates design-time as well as run-time knowledge into the component composition process. Service orientation is employed to facilitate the changes of adaptation policy. Results show that our framework has significant advantages over traditional approaches in light of flexibility, resource usage and lines of code. Although our experience was based on the OSGi middleware, we believe our findings to be general to architecture-based management systems using reflective component models.     

Cost engineering with quality function deployment

Conventional Quality Function Deployment (QFD) is technically one-sided. Prioritization of technical attributes, if carried out at all, attempts to maximize customer satisfaction without considering the costs incurred. However, product design is usually a techno-economic process, hence there is always a tradeoff between quality goals and limited budgets. Based on a prioritization method suggested by Wasserman [1], this paper integrates design costs into the QFD framework. This proposed approach enables designers to optimize product development resources towards customer satisfaction and conduct analytical investigations to facilitate decision making in product design and development.     

On the modelling of CDNaaS deployment

With the increasing demand for over the top media content, understanding user perception and Quality of Experience (QoE) estimation have become a major business necessity for service providers. Online video broadcasting is a multifaceted procedure and calculation of performance for the components that build up a streaming platform requires an overall understanding of the Content Delivery Network as a service (CDNaaS) concept. Therefore, to evaluate delivery quality and predicting user perception while considering NFV (Network Function Virtualization) and limited cloud resources, a relationship between these concepts is required. In this paper, a generalized mathematical model to calculate the success rate of different tiers of online video delivery system is presented. Furthermore, an algorithm that indicates the correct moment to switch between CDNs is provided to improve throughput efficiency while maintaining QoE and keeping the cloud hosting costs as lowest possible.