A component- and connector-based approach for end-user composite web applications development

Enabling real end-user development is the next logical stage in the evolution of Internet-wide service-based applications. Successful composite applications rely on heavyweight service orchestration technologies that raise the bar far above end-user skills. This weakness can be attributed to the fact that the composition model does not satisfy end-user needs rather than to the actual infrastructure technologies. In our opinion, the best way to overcome this weakness is to offer end-to-end composition from the user interface to service invocation, plus an understandable abstraction of building blocks and a visual composition technique empowering end users to develop their own applications. In this paper, we present a visual framework for end users, called FAST, which fulfils this objective. FAST implements a novel composition model designed to empower non-programmer end users to create and share their own self-service composite applications in a fully visual fashion. We projected the development environment implementing this model as part of the European FP7 FAST Project, which was used to validate the rationale behind our approach.     

XCML: providing context-aware language extensions for the specification of multi-device web applications

There is a vast body of research dealing with the development of context-aware web applications that can adapt to different user, platform and device contexts. However, the range and growing diversity of new devices poses two significant problems to existing approaches. First, many techniques require a number of additional design processes and modelling steps before applications can be adapted. Second, the new generation of platforms and technologies underlying these devices as well as upcoming web standards HTML5 and CSS3 have partly changed the way in which web applications are implemented nowadays and often limit the way in which they can be adapted. In this paper, we present XCML as one example of a domain-specific language that tightly integrates context-aware concepts and adaptivity mechanisms to support developers in the specification and implementation of multi-channel web applications. In contrast to most existing approaches, the objective is to use a more lightweight approach to adaptation that can dynamically evolve and support new requirements as they emerge. Our solution builds on versioning principles in combination with a context matching process based on a declaration of context-dependent variants of content, navigation and presentation in terms of context expressions at different levels of granularity that are specific to the application. To support this, a formally defined context algebra is used to parse and resolve the context expressions at compile-time and to determine the best-matching variants with respect to the client context at run-time. We present the language concepts and a possible execution environment together with context-aware developer tools for the authoring and testing of adaptive features and behaviour. We also report on two case studies: the first shows how our general approach allows for integration with existing technologies to leverage advanced context-aware mechanisms in applications developed using other platforms and languages and the second how existing web interfaces can be systematically extended to support new adaptation scenarios.     

EgoSpaces: facilitating rapid development of context-aware mobile applications

Today's mobile applications require constant adaptation to their changing environments, or contexts. Technological advances have increased the pervasiveness of mobile computing devices such as laptops, handhelds, and embedded sensors. The sheer amount of context information available for adaptation places a heightened burden on application developers as they must manage and utilize vast amounts of data from diverse sources. Facilitating programming in this data-rich environment requires a middleware that provides context information to applications in an abstract form. In this paper, we demonstrate the feasibility of such a middleware that allows programmers to focus on high-level interactions among programs and to employ declarative abstract context specifications in settings that exhibit transient interactions with opportunistically encountered components. We also discuss the novel context-aware abstractions the middleware provides and the programming knowledge necessary to write applications using it. Finally, we provide examples demonstrating the infrastructure's ability to support differing tasks from a wide variety of application domains.     

觉察上下文的Web服务研究与应用

现有的Web服务框架不能适应普适计算的特点,即无法为移动用户提供自定义的个性化的服务.通过对现有Web服务的扩展,提出了一个觉察上下文的自适应的Web服务开发与部署框架.在该框架中,客户端的上下文信息作为SOAP消息的头块被分布式地传递和处理,Web服务可为客户端提供自定义的个性化的服务.同时,上下文是可扩展的,通过自动的上下文处理,Web服务可自适应新的上下文而不需要改变Web服务本身.     

Framework for context-aware smartphone applications

This paper presents research and development of a dedicated system architecture, designed to enable its users to interact with each other as well as to access information on points of interest that exist in their immediate environment. This is accomplished through managing personal preferences and contextual information in a distributed manner and in real time. The advantage of this system is that it uses mobile devices, heterogeneous sensors and a selection of user interface paradigms to produce a sociotechnical framework to enhance the perception of the environment and promote intuitive interactions. Representation of the real-world objects, their spatial relations and other captured features are visualised on scalable interfaces, ranging from 2D to 3D models and from photorealism to stylised clues and symbols. The conceptual design and implementation of our location and orientation based algorithm for mobile augmented reality is presented in detail. The framework is fit for use in unknown environments and therefore suitable for ubiquitous operation. The presented prototype is multifaceted and capable of supporting peer-to-peer exchange of information in a pervasive fashion, usable in various contexts. The modalities of these interactions are explored and laid out particularly in the context of entertainment and urban navigation.     

MIMOSA: context-aware adaptation for ubiquitous web access

The ubiquitous computing scenario is characterized by heterogeneity of devices used to access services, and by frequent changes in the user’s context. Hence, adaptation according to the user’s context and the used devices is necessary to allow mobile users to efficiently exploit Internet-based services. In this paper, we present a distributed framework, named MIMOSA, that couples a middleware for context-awareness with an intermediary-based architecture for content adaptation. MIMOSA provides an effective and efficient solution for the adaptation of Internet services on the basis of a comprehensive notion of context, by means of techniques for aggregating context data from distributed sources, deriving complex contextual situations from raw sensor data, evaluating adaptation policies, and solving possible conflicts. The middleware allows programmers to modularly build complex adaptive services starting from simple ones, and includes tools for assisting the user in declaring her preferences, as well as mechanisms for detecting incorrect system behaviors due to a wrong choice of adaptation policies. The effectiveness and efficiency of MIMOSA are shown through the development of a prototype adaptive service, and by extensive experimental evaluations.     

Model-driven development of mobile applications for Android and iOS supporting role-based app variability

Rapidly increasing numbers of applications and users make the development of mobile applications to one of the most promising fields in software engineering. Due to short time to market, differing platforms, and fast emerging technologies, mobile application development faces typical challenges where model-driven development (MDD) can help. We present a modeling language and an infrastructure for the MDD of native apps in Android and iOS. Our approach allows a flexible app development on different abstraction levels: compact modeling of standard app elements such as standard data management and increasingly detailed modeling of individual elements to cover, for example, specific behavior. Moreover, a kind of variability modeling is supported such that mobile apps with variants can be developed. We demonstrate our MDD approach with several apps including a conference app, a museum guide with augmented reality functionality, and a SmartPlug.     

Programming mobile context-aware applications with TOTAM

In tuple space approaches to context-aware mobile systems, the notion of context is defined by the presence or absence of certain tuples in the tuple space. Existing approaches define such presence either by collocation of devices holding the tuples or by replication of tuples across all devices. We show that both approaches can lead to an erroneous perception of context. Collocation ties the perception of context to network connectivity which does not always yield the expected result. Tuple replication can cause that a certain context is perceived even if the device has left the context a long time ago. We propose a tuple space approach in which tuples themselves carry a predicate that determines whether they are in the right context or not. We present a practical API for our approach and show its use by means of the implementation of various mobile applications. Benchmarks show that our approach can lead to a significant increase in performance compared to other approaches.     

Crowdsourcing privacy preferences in context-aware applications

Developers of context-aware applications are faced with a tough challenge: powerful privacy controls are essential to maintain user trust, but they are also hard to use and not adequate in all situations. To address this tradeoff, we present Super-Ego, a crowdsourcing framework for privacy management of location information in ubiquitous environment. We study how crowdsourcing can be used to predict the user’s privacy preferences for different location on the basis of the general user population. The crowdsourcing methods are evaluated in a 2-week user study in which we tracked the locations of 30 subjects and asked them to provide privacy preferences for the locations they had visited. Our results show that by employing simple methods for semantic analysis of locations and by profiling the user’s privacy inclination, our methods can accurately predict the privacy preferences for 80 % of the user’s locations. By employing semi-automatic decision strategies, which ask the user to decide regarding the privacy of some of the locations, the accuracy rate raises to 90 %.     

Bringing context-aware access to the web through spoken interaction

The web has become the largest repository of multimedia information and its convergence with telecommunications is now bringing the benefits of web technology to hand-held devices. To optimize data access using these devices and provide services which meet the user needs through intelligent information retrieval, the system must sense and interpret the user environment and the communication context. In addition, natural spoken conversation with handheld devices makes possible the use of these applications in environments in which the use of GUI interfaces is not effective, provides a more natural human-computer interaction, and facilitates access to the web for people with visual or motor disabilities, allowing their integration and the elimination of barriers to Internet access. In this paper, we present an architecture for the design of context-aware systems that use speech to access web services. Our contribution focuses specifically on the use of context information to improve the effectiveness of providing web services by using a spoken dialog system for the user-system interaction. We also describe an application of our proposal to develop a context-aware railway information system, and provide a detailed evaluation of the influence of the context information in the quality of the services that are supplied.     

Model-driven development for early aspects

Currently, non-functional requirements (NFRs) consume a considerable part of the software development effort. The good news is that most of them appear time and again during system development and, luckily, their solutions can be often described as a pattern independently from any specific application or domain. A proof of this are the current application servers and middleware platforms that can provide configurable prebuilt services for managing some of these crosscutting concerns, or aspects. Nevertheless, these reusable pattern solutions presents two shortcomings, among others: (1) they need to be applied manually; and (2) most of these pattern solutions do not use aspect-orientation, and, since NFRs are often crosscutting concerns, this leads to scattered and tangled representations of these concerns. Our approach aims to overcome these limitations by: (1) using model-driven techniques to reduce the development effort associated to systematically apply reusable solutions for satisfying NFRs; and (2) using aspect-orientation to improve the modularization of these crosscutting concerns. Regarding the first contribution, since the portion of a system related to NFRs is usually significant, the reduction on the development effort associated to these NFRs is also significant. Regarding the second contribution, the use aspect-orientation improves maintenance and evolution of the non-functional requirements that are managed as aspects. An additional contribution of our work is to define a mapping and transition from aspectual requirements to aspect-oriented software architectures, which, in turn, contributes to improve the general issue of systematically relating requirements to architecture. Our approach is illustrated by applying it to a Toll Gate case study.     

Model-driven generative development of measurement software

Metrics offer a practical approach to evaluate properties of domain-specific models. However, it is costly to develop and maintain measurement software for each domain-specific modeling language. In this paper, we present a model-driven and generative approach to measuring models. The approach is completely domain-independent and operationalized through a prototype that synthesizes a measurement infrastructure for a domain-specific modeling language. This model-driven measurement approach is model-driven from two viewpoints: (1) it measures models of a domain-specific modeling language; (2) it uses models as unique and consistent metric specifications, with respect to a metric specification metamodel which captures all the necessary concepts for model-driven specifications of metrics. The benefit from applying the approach is evaluated by four case studies. They indicate that this approach significantly eases the measurement activities of model-driven development processes.     

An adaptive middleware framework for context-aware applications

We describe a middleware framework for the adaptive delivery of context information to context-aware applications. The framework abstracts the applications from the sensors that provide context. Further applications define utility functions on the quality of context attributes that describe the context providers. Then, given multiple alternatives for providing the same type of context, the middleware applies the utility function to each alternative and choose the one with maximum utility. By allowing applications to delegate the selection of context source to the middleware, our middleware can implement autonomic properties, such as self-configuration when new context providers appear and resilience to failures of context providers.

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Towards a programming model for context-aware applications

In mobile computing scenarios, users move in different environments and applications can automatically explore their surroundings. This type of context-aware application is an emerging trend, so far not widely disseminated. We believe that the proposal of a programming model specifically designed for the specification of context-aware applications, using general abstractions, will foster a rapidly widespread of such kind of software. In this article, we propose the use of the Holoparadigm (in short Holo) to fill this gap. We created a programming language based on Holo (called HoloL) to demonstrate the strengths of Holoparadigm to develop context-aware applications. The article uses a sample scenario to show the Holo's practical aspects related to implementation of context-aware applications. We also present a platform to HoloL (called HoloEnv), composed of a compiler, a virtual machine, and a distributed execution environment. Finally, different performance aspects of the HoloEnv's components were evaluated through experimental results.     

Model-driven development: a metamodeling foundation

Metamodeling is an essential foundation for MDD, but there's little consensus on the precise form it should take and role it should play. The authors analyze the underlying motivation for MDD and then derive a concrete set of requirements that a supporting infrastructure should satisfy. They discuss why the traditional "language definition" interpretation of metamodeling isn't a sufficient foundation and explain how it can be extended to unlock MDD's full potential.     

Toward an OSGi-based infrastructure for context-aware applications

Applications and services must adapt to changing contexts in dynamic environments. However, building context-aware applications is still complex and time-consuming due to inadequate infrastructure support. We propose a context-aware infrastructure for building and rapidly prototyping such applications in a smart-home environment. This OSGi-based infrastructure manages context-aware services reliably and securely and efficiently supports context acquisition, discovery, and reasoning. A formal, ontology-based context model enables semantic context representation, reasoning, and knowledge sharing. We propose an ontology-based context model that leverages Semantic Web technology and OWL (Web Ontology Language). OWL is an ontology markup language that enables context sharing and context reasoning. Based on our context model, we also propose a service-oriented context-aware middleware (SOCAM) architecture, including a set of independent services that perform context discovery, acquisition, and interpretation.     

Hybrid reasoning technique for improving context-aware applications

With the rapid adoption of GPS enabled smart phones and the fact that users are almost permanently connected to the Internet, an evolution is observed toward applications and services that adapt themselves using the user’s context, a.o. taking into account location information. To facilitate the development of such new intelligent applications, new enabling platforms are needed to collect, distribute, and exchange context information. An important aspect of such platforms is the derivation of new, high-level knowledge by combining different types of context information using reasoning techniques. In this paper, we present a new approach to derive context information by combining case-based and rule-based reasoning. Two use cases are detailed where both reasoners are used to derive extra useful information. For the desk sharing office use case, the combination of rule-based and case-based reasoning allows to automatically learn typical trajectories of a user and improve localization on such trajects with 42%. In both use cases, the hybrid approach is shown to provide a significant improvement.