动态Web服务行为适配方法初探

面向服务的计算是当前软件工程领域和软件产业界的研究热点之一。随着Web服务组合技术的广泛应用,服务间的行为交互日趋复杂,已存在的静态Web服务行为适配方法难以支持复杂Web服务间的行为适配。以此为背景,首先介绍Web服务适配的相关概念,然后分析现有的静态Web服务行为适配方法的研究现状和存在的主要问题,最后探讨动态Web服务行为适配的基本原理、一般方法和技术优势。     

内容适配技术研究综述

内容适配技术是实现通用多媒体接入的技术体系。MPEG-21标准提出了内容适配技术框架和服务环境描述技术规范。针对MPEG-21内容适配框架,从内容适配系统、服务环境数据交换、适配决策等方面,介绍国内外相关研究现状。     

面向SOA的企业服务总线研究与实现

针对企业日益增长的信息共享和业务整合的需求,面向SOA的企业服务总线屏蔽各类异构的应用从而实现基于SOA架构的企业应用集成是大势所趋。现有的面向SOA的企业服务总线（s-ESB）大多立足于提供Web服务容器,并没有提供统一的适配机制无缝集成各类企业应用,从而极大限制s-ESB的高可用性和可扩展性。首先,提出了一种新型的基于SOA架构的企业应用集成环境,从而明确了s-ESB在构建企业应用集成中的地位和作用;其次,提出了s-ESB的体系结构模型,并解决了协议适配,服务适配和公共服务等关键技术问题;最后,原型系统证明s-ESB的灵活性,可有效集成各类异构企业应用。     

面向MPEG-21 DIA的适配决策模型

通用多媒体内容访问是未来多媒体服务的常用模式。针对这一访问模式,MPEG-21提出了DIA技术框架,以期实现相关技术标准化。但是,DIA现在只对上下文描述等元数据制定了标准,而适配决策引擎仍然是一个开放问题。针对已有适配决策模型存在的问题,提出了一种适配决策树模型,该模型将适配决策视为序列决策,并用决策树对其建模。为满足多媒体服务的个性化需求,利用用户偏好信息建立适配决策树。此外,利用优化模型构建决策空间,使参与决策的对象数缩小为模态数,从而减少了适配决策时间,满足了多媒体服务的实时性。通过仿真实验证明,该适配决策树模型在决策误差和平均迭代次数两个指标上都优于或相近于已有的适配决策模型。     

DANCE:一种面向云-端动态集成的服务适配方法

边缘计算可以通过将计算移到边缘设备上来提高大型物联网流数据处理质量以及降低网络运行成本.对于流数据处理,边缘设备通常只有有限的计算能力和存储能力,显然不能支持所有的实时流数据查询和处理.本文尝试引入服务并在边缘和云之间灵活地划分服务来实现云-端集成,云服务和端服务之间通过事件机制进行服务适配.物联网动态环境中,云-端服务的动态适配是使云基础设施和端设备间无缝集成的关键.动态集成背景下的服务适配需要把握适配时机来应对端服务适配请求的不确定性和非完全适配等难题.针对这一问题,论文提出了一种面向云-端动态集成的服务适配方法(Dynamic Adaption cloud Services with Edge Services,DANCE).这种方法的主要贡献在于:将云服务实例和端服务实例之间的适配问题建模为二分图顶点之间的动态匹配问题,同时结合排队论中的M/M/c/∞模型对二分图最优匹配Kuhn-Munkres算法进行了优化改进,保障适配过程中端服务实例的全局平均请求响应时间最小.最后,基于真实的电能质量监控案例和数据,验证了本文方法的有效性.     

基于规范流网的Web服务行为适配方法研究

Web服务适配是面向服务计算领域的重要研究内容.针对现有服务行为建模和适配技术在循环服务行为、数据流建模和状态空间爆炸方面存在的问题,提出一种新的服务行为建模和适配方法,并结合实例阐述该方法如何以规范流网为基础,建模服务行为,构造服务行为的符号化可覆盖树,构建数据依赖关系和动作依赖关系,构建符号化执行轨迹适配器,直至最后完成服务行为适配的整个建模和适配过程.     

移动服务平台终端智能适配框架的研究

为了满足移动服务平台(MSP)对终端智能适配的要求--智能识别终端,返回用户需要的服务结果,高效地开发移动媒体应用,结合常用开发方法的分析提出了基于移动服务平台终端智能适配框架,介绍了智能适配的框架所采用的模板技术、框架体系结构和框架关键点的设计与实现.在实际的运营中验证智能适配框架具有可复用、易管理、可满足用户人性化要求等良好特性,同时降低了MSP上业务开发难度,解决了平台中多种媒体业务和手机终端间的大量适配问题.     

基于适配的服务协作流程动态管理

服务协作以服务为构造单元,通过组合不同的服务,实现复杂的业务逻辑,并以此为基础构建新的应用.为实现正确的服务协作,服务之间的交互必须是兼容且一致的.适配技术通过构造适配器来弥补服务之间的交互差异,为解决协作的一致性问题提供了有效的方法途径.然而考虑到服务计算环境的动态特性,协作适配器本身应具有动态调整及重新配置的能力,从而避免使其成为协作系统响应动态变化的可适应能力的瓶颈.文中首先给出了一种基于适配的服务协作方法,以保证服务交互的一致性.并针对提出的适配器结构,建立了适配器的执行模型,在此基础上给出了适配器的动态更新方法,使适配器具有可重配置以及动态调整的能力,从而保证了基于适配的服务协作系统的灵活性和动态可适应性.     

CORBA对象联编与对象适配研究

针对基CORBA标准的分布对象软件平台中,对象请求如何准确定位到服务器端对象实现的联编技术进行研究。分析了瞬态IOR与持久IOR对象联编的实现方法。同时针对CORBA服务器端的对象适配机制及策略进行研究,基于对象适配模型,提出了对象基本框架与相应适配策略控制层相结合的对象适配框架。采用框架适配方法集的层次划分方法,对对象适配策略进行优化。     

基于分布式协调模型的服务协作方法研究

由于服务是由彼此独立的提供商开发的,无法在开发阶段就预测到其潜在的所有交互可能,因此需要在实际协作时检查服务之间的兼容性,从而保障协作的正确性和一致性.提出了一种基于分布式协调模型的方法,以提高服务的可复用性和服务协作的灵活性.该方法通过失败等价(failure-equivalent)行为语义保持的投影规则,将协作流程转换为协作子流程,以实现分布式的成对兼容性检查,并提出基于适配的检查方法,检验服务是否可以通过适配机制满足兼容性的要求,同时给出了适配器自动生成的算法.适配机制的引入进一步降低了服务与协作环     

人工智能框架技术趋势研究

作为人工智能开发环节中的基础工具,人工智能框架承担着AI技术生态中操作系统的角色,是AI学术创新与产业商业化的重要载体。随着其重要性的不断突显,人工智能框架已经成为人工智能产业创新的焦点之一,引起了学术界、产业界的高度重视。在此背景下,本文从人工智能框架的概念内涵、价值意义入手,梳理人工智能框架演进历程,总结当前人工智能框架技术体系,最后研判得出人工智能框架技术发展的“四泛”趋势,即泛开发、泛设备、泛场景、泛工程。     

Integrating semantic analysis and scalable video coding for efficient content-based adaptation

Scalable video coding has become a key technology to deploy systems where the adaptation of content to diverse constrained usage environments (such as PDAs, mobile phones and networks) is carried out in a simple and efficient way. Content-based adaptation and summarization are fields that aim for providing improved adaptation to the user, trying to optimize the semantic coverage in the adapted/summarized version. This paper proposes the integration of content analysis with scalable video adaptation paradigm. They must be fitted in such a way that the efficiency of scalable adaptation is not damaged. An integrated framework is proposed for semantic video adaptation, as well as an adaptive skimming scheme that can use the results of semantic analysis. They are described using the MPEG-21 DIA tools to provide the adaptation in a standard framework. Particularly, the case of activity analysis is described to illustrate the integration of semantic analysis in the framework, and its use for online content summarization and adaptation. Overall efficiency is achieved by means of computing activity using compressed domain analysis with several metrics evaluated as measures of activity. Work supported by the Ministerio de Ciencia y Tecnología of the Spanish Government under project TIN2004-07860 (MEDUSA) and by the Comunidad de Madrid under project S-0505-TIC-0223 (PROMULTIDIS).     

An integrated runtime QoS-aware middleware framework for distributed multimedia applications

Future-generation distributed multimedia applications are expected to be highly scalable to a wide variety of heterogeneous devices, and highly adaptive across wide-area distributed environments. This demands multiple stages of run-time support in QoS-aware middleware architectures, particularly, probing the performance of QoS parameters, instantiating the initial component configurations, and adapting to on-the-fly variations. However, few of the past experiences in related work have shown comprehensive run-time support in all of the above stages – they often design and build a middleware framework by focusing on only one of the run-time issues. In this paper, we argue that distributed multimedia applications need effective run-time middleware support in all these stages to be highly scalable and adaptive across a wide variety of execution environments. Nevertheless, the design of such a middleware framework should be kept as streamlined and simple as possible, leading to a novel and integrated run-time middleware platform to unify the probing, instantiation and adaptation stages. In addition, for each stage, the framework should enable the interaction of peer middleware components across host boundaries, so that the corresponding middleware function can be performed in a coordinated and coherent fashion. We present the design of such an integrated architecture, with a case study to illustrate how it is simple yet effective to monitor and configure complex multimedia applications.     

Adaptation in Multimedia Systems

Multimedia systems can profit a lot from personalization. Such a personalization is essential to give users the feeling that the system is easily accessible especially if it is done automatically. The way this adaptive personalization works is very dependent on the adaptation model that is chosen.We introduce a generic two-dimensional classification framework for user modeling systems. This enables us to clarify existing as well as new applications in the area of user modeling. In order to illustrate our framework we evaluate push and pull based user modeling in user modeling systems.Paul de Vrieze received his Masters degree in Information Science in 2002 from the University Of Tilburg, The Netherlands. He is currently junior researcher at the University of Nijmegen. His main research interests include adaptive systems and user modelling.Patrick van Bommel received his Masters degree in Computer Science in 1990, and the degree of Ph.D in Mathematics and Computer Science, from the University of Nijmegen, the Netherlands in 1995. He is currently assistant professor at the University of Nijmegen. His main research interests include information modelling and information retrieval.Prof.Dr.Ir. Th.P. van der Weide received his masters degree from the Technical University Eindhoven, the Netherlands in 1975, and the degree of Ph.D in Mathematics and Physics from the University of Leiden, the Netherlands in 1980. He is currently professor at the University of Nijmegen, the Netherlands. His main research interests include information systems, information retrieval, hypertext and knowledge based systems.     

鲁棒的自适应尺度和方向的目标跟踪方法

针对在视频序列图像目标跟踪中,跟踪目标尺寸和跟踪目标相对背景运动的方位角都在实时变化,常规目标跟踪算法会引起尺度和方向定位偏差,导致跟踪漂移,甚至跟踪失败问题,提出鲁棒的目标尺度和方向自适应的跟踪方法。在Kalman滤波框架下,通过将运动目标的最小外接矩形信息转化为Kalman滤波参数,对目标运动进行建模。采用基于最小外接矩形的两步块匹配搜索方式实现对目标的中心定位,然后采用增量式搜索匹配方法根据最优尺度和角度的判别条件修正目标尺度和方向角度。通过动态评估不同目标模型在不同跟踪场景中的置信度,对目标模型进行动态更新。使用公用视频图像序列测试,实验结果验证了该方法的有效性。     

Training fuzzy logic based software components by combining adaptation algorithms

 A training framework of an effective method for off-line training of a class of control software components (e.g., for first-order nonlinear feedback control systems) using combinations of three kinds of adaptation algorithms is presented. Each control software component is represented at the abstract level by means of a set of adaptive fuzzy logic (FL) rules and at the concrete level by means of fuzzy membership functions (MBFs). At the concrete representation level adaptation algorithms specified for use in adapting MBFs are: genetic algorithms, neural net algorithms, and Monte Carlo algorithms. We specify effective combinations of these three existing adaptation algorithms to train a faulty FL rule-based software component for the tracker problem. In the framework, training consists of two phases: testing and adapting. In the testing phase, a test driver generates an effective fault scenario ( fs) and locates the faulty fuzzy elements (FFEs) by using each or a combination of three adaptation algorithms. In the adapting phase, for each fault scenario adaptation algorithms and their combinations are used to modify the MBFs of the component. Effectiveness of the two phase training is determined in terms of testability, flexibility, adaptability, and stability. An initial design of the simulation environment is presented. In the experiment, for a given circumstance (environment and fuzzy rules) we apply a combination of a genetic algorithm GA) and a neural network (NN) with an error back-propagation algorithm (BP) in the testing phase for generating fault scenarios. Then we apply GA-only method in the adapting phase for adapting the faulty software component. Simulation results on effectiveness and efficiency are discussed.     

Conceptualising the link between information systems and resilience: A developing country field study

Resilience—the ability of systems to cope with external shocks and trends—is a topic of increasing interest to research and practice. That growing interest is reflected within information systems (IS), but a structured review of IS literature shows a number of knowledge gaps around the conceptual and empirical application of resilience. This paper investigates what the subdiscipline of information and communication technologies for development (ICT4D) can contribute; finding that it offers the IS discipline fresh insights that can be built into a new framework of resilience, and an arena within which this new framework can appropriately be field tested. Application of the resilience framework was undertaken through interviews and a survey in an urban community in Costa Rica; benchmarking both community resilience and “e‐resilience” (understood here as the contribution of ICTs to community resilience), and developing from these a set of action priorities. The paper reflects on what can be learned generally from this conceptualisation and operationalisation of resilience. It also reflects on what ICTs contribute to resilience in developing countries and on what this ICT4D‐based research specifically contributes to the identified IS knowledge gaps. This includes identification of a future research agenda on information systems and resilience.     

Assessing flexibility in event-driven process adaptation

Business process management (BPM) has emerged as a prominent information management approach focusing on the design, execution and governance of organizational business processes. The ability to deal with both foreseen and unforeseen changes in business processes is considered critical for contemporary business process management systems. This paper proposes an approach that couples an event-driven framework for detecting and reasoning in situations that pose the need for process adaptations with MCDM methods for selecting adaptations. The proposed approach has been implemented in an aspect-oriented extension of a BPMN2.0 engine in order to enact adaptations of business processes in real-time.