Multiple-Agent Perspectives in Reasoning About Situations for Context-Aware Pervasive Computing Systems

In open heterogeneous context-aware pervasive computing systems, suitable context models and reasoning approaches are necessary to enable collaboration and distributed reasoning among agents. This paper proposes, develops, and demonstrates the following: 1) a novel context model and reasoning approach developed with concepts from the state-space model, which describes context and situations as geometrical structures in a multidimensional space; and 2) a context algebra based on the model, which enables distributed reasoning by merging and partitioning context models that represent different perspectives of computing entities over the object of reasoning. We show how merging and reconciling different points of view over context enhances the outcomes of reasoning about the context. We develop and evaluate our proposed algebraic operators and reasoning approaches with cases using real sensors and with simulations. We embed agents and mobile agents with these modeling and reasoning capabilities, thus facilitating context-aware and adaptive mobile agents operating in open pervasive environments.     

面向普适计算的动态自适应中间件模型

为了提高普适计算系统的开发效率, 设计了一个基于OSGi框架的动态普适计算中间件模型. 该中间件模型以OSGi框架为基础, 建立移动管理器管理用户和服务的移动, 利用上下文管理器来管理上下文, 动态调整自己的行为, 支持上下文感知应用. 通过标准的接口实现各种异构普适设备间的互操作性. 实验结果表明该中间件能够满足通用普适计算环境的要求, 对于普适计算系统的开发具有一定的借鉴意义.     

Mobile context-based framework for threat monitoring in urban environment with social threat monitor

Engaging users in threat reporting is important in order to improve threat monitoring in urban environments. Today, mobile applications are mostly used to provide basic reporting interfaces. With a rapid evolution of mobile devices, the idea of context awareness has gained a remarkable popularity in recent years. Modern smartphones and tablets are equipped with a variety of sensors including accelerometers, gyroscopes, pressure gauges, light and GPS sensors. Additionally, the devices become computationally powerful which allows for real-time processing of data gathered by their sensors. Universal access to the Internet via WiFi hot-spots and GSM network makes mobile devices perfect platforms for ubiquitous computing. Although there exist numerous frameworks for context-aware systems, they are usually dedicated to static, centralized, client-server architectures. There is still space for research in the field of context modeling and reasoning for mobile devices. In this paper, we propose a lightweight context-aware framework for mobile devices that uses data gathered by mobile device sensors and performs on-line reasoning about possible threats based on the information provided by the Social Threat Monitor system developed in the INDECT project.     

Supporting pervasive computing applications with active context fusion and semantic context delivery

Future pervasive computing applications are envisioned to adapt the applications’ behaviors by utilizing various contexts of an environment and its users. Such context information may often be ambiguous and also heterogeneous, which make the delivery of unambiguous context information to real applications extremely challenging. Thus, a significant challenge facing the development of realistic and deployable context-aware services for pervasive computing applications is the ability to deal with these ambiguous contexts. In this paper, we propose a resource optimized quality assured context mediation framework based on efficient context-aware data fusion and semantic-based context delivery. In this framework, contexts are first fused by an active fusion technique based on Dynamic Bayesian Networks and ontology, and further mediated using a composable ontological rule-based model with the involvement of users or application developers. The fused context data are then organized into an ontology-based semantic network together with the associated ontologies in order to facilitate efficient context delivery. Experimental results using SunSPOT and other sensors demonstrate the promise of this approach.     

面向普适计算的多Agent协同设计系统模型

根据普适计算的特点,提出了一种多agent协同设计系统框架模型.考虑到普适计算环境下移动设备的交互和多通道的信息集成,该模型在已有多agent协同设计系统的框架模型上增加了相应的agent,并且在设计agent的结构中包含了通道识别、上下文生成及多通道信息整合模块,以处理多通道的信息.详细介绍了在该agent模型中基于设计上下文的知识表示、搜索和更新式学习算法,以及协同设计系统中多agent知识共享的方法.该研究对于普适计算在设计领域中的应用有重要的意义.     

iConAwa - An intelligent context-aware system

Context-awareness becomes an increasingly important concept in the development of mobile and ubiquitous systems. Applications and services, which run in these kinds of highly dynamic environments, should be aware of and adapt to their contexts. Context-aware applications improve and enrich people’s interactions with devices, computers and other people.In this paper, design and development of iConAwa, which is an intelligent context-aware multi-agent system proactively providing mobile users with context-aware information and services, is described. In iConAwa, mobile users can get information and services about nearby resources (attraction points) according to their context and also communicate with each other by exchanging messages. Context and point of interest ontologies are developed in OWL. Context and points of interest are modelled in a flexible and extensible way by the developed ontology models. Knowledge sharing and knowledge reuse are also provided by using these ontology models. iConAwa makes use of rule-based context reasoning which provides derivation of high level implicit context from low level explicit context. With this approach context reasoning is decoupled from the source code of the system. JADE agent development framework is used to develop the agents and Jena semantic web framework is used to manipulate ontologies and for rule based reasoning.     

基于觉察上下文计算的健康智能家庭研究

利用觉察上下文计算技术来研究实现健康智能家庭,主要研究了健康智能家庭的上下文建模和上下文推理,并构建了一个实验系统AngelHome,分析了健康智能家庭中的各种上下文信息,利用本体技术对其进行建模,并用OWLDL语言表达上下文信息模型,构建了AngelHome本体;在上下文推理部分采用混合推理,对不同的推理任务分别采用本体推理机、自定义规则推理机和贝叶斯神经网络推理.AngelHome采用OSGi框架,具有良好的伸缩性,这里分析了系统的几个主要部分,并进行了测试.实验结果表明,利用觉察上下文计算技术来实现健康智能家庭是可行的.     

普适计算环境下基于中间件的上下文质量管理框架研究

随着信息技术的快速发展,分布式计算技术逐渐向普适计算技术演化,从而达到信息空间和物理空间融合的最终目标,为用户提供普适的智能化服务。为了达到这个目标,一个主要的困难就是如何有效地连续监测、才甫获与解释环境相关的上下文信息来确保精确的上下文感知性。很多研究者已先后投身于上下文感知的普适应用的研究工作中,但大多数往往直接针对原始上下文进行处理,没有考虑上下文质量(QoC)的影响。因此,提出了一种基于中间件的上下文质量管理框架,即通过上下文的质量门阂管理、重复与不一致的上下文丢弃等不同层次的控制机制,为上下文感知服务和应用用户提供有效而可靠的上下文服务。     

基于本体的上下文感知中间件框架

上下文感知是普适计算的核心技术之一,而描述和理解上下文信息是上下文感知的前提。由于上下文信息种类繁多、感知方式迥异,目前开发面向特定应用的上下文感知系统缺乏统一的机制和通用的架构,增加了系统开发的成本。引入语义Web技术,利用本体对上下文信息进行建模,采用本体描述语言描述上下文模型,提供了一个公共的上下文本体以实现多个独立开发的上下文感知系统对知识的共享和推理,构建了通用的上下文感知中间件框架,从而实现对域内上下文知识的共同理解。     

Context-adaptive and energy-efficient mobile transaction management in pervasive environments

Pervasive computing is a user-centric, scalable, parallel, and distributed computing paradigm, allowing users to access to their preferred services even while moving around. Transaction management for pervasive environments has to provide mobile users with reliable and transparent services anytime anywhere. To make such a vision a reality, the communication of pervasive transaction processing should be context-aware for adapting to dynamically changing execution environments, and energy-efficient for prolonging the lifetime of battery-powered mobile devices. In this paper, we propose a context model and a context-aware transaction model for pervasive transactions, and present a c\underline{\mathrm{c}} ontext-adaptive and e\underline{\mathrm{e}} nergy-efficient t\underline{\mathrm{t}} ransaction m\underline{\mathrm{m}} anagement mechanism (CETM) that can dynamically adjust transaction execution behaviors in terms of current context information. Moreover, we model and verify the correctness of the CETM through Petri nets. The simulation results have demonstrated that our transaction management mechanism CETM can significantly reduce the failed probability of concurrent pervasive transactions.     

Enhancing intelligence and dependability of a product line enabled pervasive middleware

To provide good support for user-centered application scenarios in pervasive computing environments, pervasive middleware must react to context changes and prepare services accordingly. At the same time, pervasive middleware should provide extended dependability via self-management capabilities, to conduct self-diagnosis of possible malfunctions using the current runtime context, and self-configuration and self-adaptation when there are service mismatches. In this article, we present an approach to combine the power of BDI practical reasoning and OWL/SWRL ontologies theoretical reasoning in order to improve the intelligence of pervasive middleware, supported by a set of Self-Management Pervasive Service (SeMaPS) ontologies featuring dynamic context, complex context, and self-management rules modeling. In this approach, belief sets are enriched with the results of OWL/SWRL theoretical reasoning to derive beliefs that cannot be obtained directly or explicitly. This is demonstrated with agents negotiating sports appointments. To cope with self-management, the corresponding monitoring, configuration, adaptation and diagnosis rules are developed based on OWL and SWRL utilizing SeMaPS ontologies. Evaluations show this combined reasoning approach can perform well, and that Semantic Web-based self-management is promising for pervasive computing environments.     

面向普适计算环境的Android平台服务编排框架

普适计算环境下的智能移动设备是面向终端用户的服务资源聚集和编排的主要载体。普适计算环境中的服务资源具有多种不同的形态,包括基于互联网提供的Web服务、终端设备自身服务和资源(例如本地应用、自带传感器)以及所处环境中可访问的服务(例如环境传感器)。此外,不断变化的上下文环境对软件本身的自适应能力提出了新的要求,而移动设备上的服务编排受设备计算能力和资源的限制。为了解决上述问题,提出了一个面向普适计算环境的Android平台服务编排框架ASOF。通过ASOF,移动终端可在运行时获取所需业务流程的服务模板,并对该模板中的抽象服务进行服务绑定,实现轻量级的混合服务编排,使终端能够动态获得调用普适计算环境中各种类型的服务的能力。随后,基于OSGi Felix框架给出了一套ASOF的标准实现,并以一个具体案例验证其有效性。     

A goal-based framework for contextual requirements modeling and analysis

Requirements engineering (RE) research often ignores or presumes a uniform nature of the context in which the system operates. This assumption is no longer valid in emerging computing paradigms, such as ambient, pervasive and ubiquitous computing, where it is essential to monitor and adapt to an inherently varying context. Besides influencing the software, context may influence stakeholders’ goals and their choices to meet them. In this paper, we propose a goal-oriented RE modeling and reasoning framework for systems operating in varying contexts. We introduce contextual goal models to relate goals and contexts; context analysis to refine contexts and identify ways to verify them; reasoning techniques to derive requirements reflecting the context and users priorities at runtime; and finally, design time reasoning techniques to derive requirements for a system to be developed at minimum cost and valid in all considered contexts. We illustrate and evaluate our approach through a case study about a museum-guide mobile information system.     

Privacy-Aware Autonomous Agents for Pervasive Healthcare

This article is part of a special issue on Intelligent Agents in Healthcare. Hospitals are natural candidates for pervasive computing technology, but they have significant privacy requirements. Autonomous agents can help developers design privacy-aware systems for pervasive healthcare environments. An extension of the SALSA agent framework incorporates customizable privacy mechanisms to adapt applications to a certain quality-of-privacy level, thereby harnessing the properties of autonomous agents. An implementation of a context-aware pervasive hospital application shows how this framework can help developers manage user privacy.     

FollowMeLite：用于普适计算的轻量级中间件平台

普适计算的目标是让环境和计算资源紧密结合，以便更好地为人类服务。为达到这一目标，移动设备和嵌入式设备构成了环境中计算资源的重要组成部分。然而，由于移动设备和嵌入式设备的计算资源有限，网络连接的多样性和不稳定性以及软硬件的异构性，开发用于这些设备的上下文感知应用复杂并且费时，其根本原因是缺乏一个统一的平台支持。为解决这一问题，我们提出了一种用于普适计算的轻量级中间件平台，叫做FollowMeLite。FollowMeLite是整个FollowMe普适计算基础结构中的一部分。它构建在OSGi之上，集成了基于本体的上下文模型和基于工作流的应用模型以及用于适应多种网络连接的通讯服务。通过部署不同的组件模块，FollowMeLite可以方便的适用于多种应用环境。     

有上下文觉察能力的智能会议室系统模型的研究

通过利用多Agent、语义Web、上下文觉察和逻辑推理等技术，参考早期的普适计算系统，提出了一个新的智能会议室系统模型。该模型使用本体Web语言——OWL实现知识共享和上下文推理；使用逻辑推理检测和解决上下文知识的不一致问题，并向使用者提供一种策略语言来控制他们的私人信息。     

普适计算环境下基于构件化中间件的上下文管理技术研究

上下文相关技术已经成为普适计算环境中用于应用服务的不可或缺的核心技术之一。对于基于构件的中间件来说,对高性能的上下文管理的需求更是必不可少,因为它构成了普适计算环境中构件适配和部署的重要基础。因此,在已有构件中间件的基础上,我们针对普适计算环境的特点提出了一种整体的上下文管理方法,将上下文管理集成在已有的构件化中间件中。应用表明,该方法能够更好地支持普适计算环境下上下文相关的构件化应用开发。     

Intelligent agents meet the semantic Web in smart spaces

A new smart meeting room system called EasyMeeting explores the use of multi-agent systems, Semantic Web ontologies, reasoning, and declarative policies for security and privacy. Building on an earlier pervasive computing system, EasyMeeting provides relevant services and information to meeting participants based on their situational needs. The system also exploits the context-aware support provided by the Context Broker Architecture (Cobra). Cobra's intelligent broker agent maintains a shared context model for all computing entities in the space and enforces user-defined privacy policies.