Mobile service oriented architectures for NN-queries

The ever-increasing number of mobile device users has also raised the users’ expectation of mobile services accordingly. This phenomenon has given pressures to the mobile service providers to improve their services in order to stay competitive in the market. The service oriented approach is seen to be a promising scheme for mobile services. This paper presents mobile service oriented architectures for Nearest-Neighbor (NN) queries that are classified into five categories, namely (i) intermittent query mobile services, (ii) continuous query mobile services, (iii) context-aware mobile services, (iv) continuous moving object query mobile services, and (v) data broadcast mobile services. These services incorporate query, location and context-aware services, ontological context model, and broadcast. The proposed architectures are concerned with mobile services for clients on the move requesting services based on their current location, which is arguably the most important feature in a wireless environment. Furthermore, we also discuss the Quality-of-Service (QoS) requirement for mobile services in which request latency time is one of the most important parameters to consider. Some analytical models for query latency measurement are presented and the results are compared with the simulation experiments.     

基于uSD的情境感知系统设计与实现*

基于移动终端、情境感知以及无线传感器网络的结合需求,提出了一种应用于移动终端的情境感知系统,包括若干无线传感器节点、情境感知及处理终端、应用服务及执行装置等。针对移动电子设备一般都不具备接入无线传感器网络所需功能单元的现状,利用uSD概念为移动终端设计了一个ZigBee通信功能扩展模块,使移动终端能够从无线传感器网络中获取情境信息,并提供相应的情境感知和处理功能。最后,设计了包含位置等信息的情境感知服务演示系统,初步验证了基于uSD的情境感知系统在移动终端上应用的新颖性和有效性。     

基于无线局域网的室内临近位置检测代理实现

传统基于网络的位置服务系统主要是为远程用户提供查询移动对象位置的信息服务。而现有基于移动终端的位置感知服务不能满足位置上下文应用的要求．为了达到系统自动自发的上下文交互目的。需要在应用中定义一个位置检测代理来捕获移动设备的位置变化事件．生成有效的上下文信息．本文使用简单贝叶斯分类算法实现了基于无线局域网的临近位置检测代理．在室内环境中进行实验表明。该方法可根据实际需要调整位置检测的范围与准确度。具有可行性与灵活性．     

QuesTInSitu: From tests to routes for assessment in situ activities

Test-based assessment tools are mostly focused on the use of computers. However, advanced Information and Communication Technologies, such as handheld devices, opens up the possibilities of creating new assessment scenarios, increasing the teachers’ choices to design more appropriate tests for their subject areas. In this paper we use the term Computing-Based Testing (CBT) instead of Computer-Based Testing, as it captures better the emerging trends. Within the CBT context, the paper is centered on proposing an approach for “Assessment in situ” activities, where questions have to be answered in front of a real space/location (situ). In particular, we present the QuesTInSitu software implementation that includes both an editor and a player based on the IMS Question and Test Interoperability specification and GoogleMaps. With QuesTInSitu teachers can create geolocated questions and tests (routes), and students can answer the tests using mobile devices with GPS when following a route. Three illustrating scenarios and the results from the implementation of one of them in a real educational situation show that QuesTInSitu enables the creation of innovative, enriched and context-aware assessment activities. The results also indicate that the use of mobile devices and location-based systems in assessment activities facilitates students to put explorative and spatial skills into practice and fosters their motivation, reflection and personal observation.     

Ubiquitous enterprise service adaptations based on contextual user behavior

Recent advances in mobile technologies and infrastructures have created the demand for ubiquitous access to enterprise services from mobile handheld devices. Further, with the invention of new interaction devices, the context in which the services are being used becomes an integral part of the activity carried out with the system. Traditional human–computer interface (HCI) theories are now inadequate for developing these context-aware applications, as we believe that the notion of context should be extended to different categories: computing contexts, user contexts, and physical contexts for ubiquitous computing. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information captured from mobile user behavior. Instead of redesigning or adapting existing enterprise services in an ad hoc manner, we introduce a methodology for the elicitation of context-aware adaptation requirements and the matching of context-awareness features to the target context by capability matching. For the implementation of such adaptations, we propose the use of three tiers of views: user interface views, data views, and process views. This approach centers on a novel notion of process views to ubiquitous service adaptation, where mobile users may execute a more concise version or modified procedure of the original process according to their behavior under different contexts. The process view also serves as the key mechanism for integrating user interface views and data views. Based on this model, we analyze the design and implementation issues of some common ubiquitous access situations and show how to adapt them systematically into a context-aware application by considering the requirements of a ubiquitous enterprise information system.

基于Android平台的车辆导航系统设计与实现

该文利用当今流行的Android平台和GPS特性,结合Google Map,设计并实现了一个基于Android平台的车载定位导航终端软件系统,并对整个软件系统的五个主要功能模块进行了详细的分析与研究。该系统经过严格测试,运行稳定可靠,自我定位精确,浏览地图流畅,地址搜索快速,路径跟踪直观,车辆跟踪准确,基本能够满足用户的车辆定位导航服务需求,并且具有广阔的推广应用前景。     

Inferring contextual preferences using deep encoder-decoder learners

ABSTRACT

Context-aware systems enable the sensing and analysis of user context in order to provide personalised services. Our study is part of growing research efforts examining how high-dimensional data collected from mobile devices can be utilised to infer users’ dynamic preferences that are learned over time. We suggest novel methods for inferring the category of the item liked in a specific contextual situation, by applying encoder-decoder learners (long short-term memory networks and auto encoders) on mobile sensor data. In these approaches, the encoder-decoder learners reduce the dimensionality of the contextual features to a latent representation which is learned over time. Given new contextual sensor data from a user, the latent patterns discovered from each deep learner is used to predict the liked item’s category in the given context. This can greatly enhance a variety of services, such as mobile online advertising and context-aware recommender systems. We demonstrate our contribution with a point of interest (POI) recommender system in which we label contextual situations with the items’ categories. Empirical results utilising a real world data set of contextual situations derived from mobile phones sensors log show a significant improvement (up to 73% improvement) in prediction accuracy compared with state of the art classification methods.     

Usability study of ME2.0

Mobile context-aware applications execute in the background of hosts mobile devices. The applications source process and aggregate hosts’ contextual and personal information. This information is disclosed to ubiquitously pervasive services that adapt their offerings to individual preferences. Unfortunately, many developers continue to ignore the user perspective in context-aware application designs as they complicate their overall task and generate exponential requirements. The additional incorporation of privacy mechanisms in context-aware applications to safeguard context and personal information disclosures also complicates users’ tasks resulting to misconfigured or completely abandoned applications. Misconfigured applications give end-users a false assurance of privacy exposing them to comprising services. We present a usability study on Mobile Electronic Personality Version 2 a privacy enhanced context-aware mobile application for personalising ubiquitous services and adapting pervasive smart-spaces. We draw conclusions on key issues related to user needs, based on user interviews, surveys, prototypes and field evaluations. Users’ needs are evaluated against five themes, learn-ability, efficiency, memorability, errors, satisfaction and privacy contention. In addition, design layout preferences, privacy manageability and consensus design comprehension are also evaluated. Clarity of priorities in context-aware mobile applications shaped by usability studies effectively increases the acceptance of levels of potential users.     

An Ontology-Based Approach to Personalized Situation-Aware Mobile Service Supply

Mobile devices such as personal digital assistants (PDAs) and mobile phones are in widespread use already today and converging to mobile smart phones. They enable users to access a wide range of services and information without guidance through their actual demands. Especially during mass events like the Olympic Games 2008 in Beijing—which was initially the context of our work—a large service space is expected to support all mobile visitors, being athletes, journalists, or spectators. Current approaches tackling such problems are location based, meaning that a user's location is central to service provision, and even context-aware, meaning that, beyond location, characteristics of a user's environment are taken into account. Such information obviously helps to deliver relevant information at the right time to the mobile users. Going one step further, a situation-aware system abstracts from the context dimensions by translating specific contexts into logical situations. Knowing the situation end users are in allows the system to better identify the information to be delivered to them and to choose the appropriate services with regard to their scope, which is referred to as service roaming. Even though many context frameworks have been introduced in the past few years, what is usually missing is the notion of characteristic features of contexts that are invariant during certain time intervals. This paper presents these concepts in the context of a platform development, namely FLAME2008, which is able to support its mobile users with personalized situation-aware services in push and pull mode.     

基于语义Web技术的上下文感知的智能移动服务

语义Web技术应用于上下文感知的智能移动服务，通过构建上下文信息本体，使得移动服务的实体之间可以进行上下文信息共享和语义互操作，并进行上下文信息推理，实现智能服务。本文首先介绍了语义Web及本体技术，其次阐述了语义Web技术应用于上下文感知的移动服务，然后详细分析了智能移动服务中的上下文信息本体构建，包括通用的上下文信息本体、用户概况本体、情境本体以及服务本体等，接着介绍了相关的研究项目，最后进行展望和总结。     

Context-aware multiagent system: Planning home care tasks

Context-aware systems are able to capture information from the context in which they are executed, assign a meaning to the gathered information, and change their behavior accordingly. As a result, the systems can offer services to users according to their individual situation within the context. This article analyzes the important aspects of context-aware computing such as capturing information for context attributes and determining the manner of interacting with users in the environment. Used in conjunction with mobile devices, context-aware systems are specifically used to improve the usability of applications and services. This article proposes the home care context-aware computing (HoCCAC) multiagent system that identifies and maintains a permanent fix on the location of patients in their home, and manages the infrastructure of services within their environment securely and reliably by processing and reasoning the data received. Based on the multiagent system, a prototype was developed to monitor patients in their home. The HoCCAC multiagent system uses a critical path method-based planning model that, in the present study, prepares the most optimal task-planning schedule for the patients in their home, is capable of reacting automatically when faced with dangerous or emergency situations, replanning any plans in progress and sending alert messages to the system. The results obtained with this prototype are presented in this article.     

Building ubiquitous QoC-aware applications through model-driven software engineering

As every-day mobile devices can easily be equipped with multiple sensing capabilities, ubiquitous applications are expected to exploit the richness of the context information that can be collected by these devices in order to provide the service that is the most appropriate to the situation of the user. However, the design and implementation of such context-aware ubiquitous appplications remain challenging as there exist very few models and tools to guide application designers and developers in mastering the complexity of context information. This becomes even more crucial as context is by nature imperfect. One way to address this issue is to associate to context information meta-data representing its quality. We propose a generic and extensible design process for context-aware applications taking into account the quality of context (QoC). We demonstrate its use on a prototype application for sending flash sale offers to mobile users. We present extensive performance results in terms of memory and processing time of both elementary context management operations and the whole context policy implementing the Flash sale application. The cost of adding QoC management is also measured and appears to be limited to a few milliseconds. We show that a context policy with 120 QoC-aware nodes can be processed in less than 100 ms on a mobile phone. Moreover, a policy of almost 3000 nodes can be instantiated before exhausting the resources of the phone. This enables very rich application scenarios enhancing the user experience and will favor the development of new ubiquitous applications.     

MobiLine: A Nested Software Product Line for the domain of mobile and context-aware applications

Mobile devices are multipurpose and multi-sensor equipments supporting applications able to adapt their behavior according to changes in the user’s context (device, location, time, etc.). Meanwhile, the development of mobile and context-aware software is not a simple task, mostly due to the peculiar characteristics of these devices. Although several solutions have been proposed to facilitate their development, reuse is not systematically used throughout the software development life-cycle. In this paper, we discuss an approach for the development of mobile and context-aware software using the Software Product Line (SPL) paradigm. Furthermore, a Nested SPL for the domain of mobile and context-aware applications is presented, lessons learned in the SPL development are discussed and a product for a context-aware visit guide is shown.     

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.     

Mosco: a privacy-aware middleware for mobile social computing

The proliferation of mobile devices coupled with Internet access is generating a tremendous amount of highly personal and sensitive data. Applications such as location-based services and quantified self harness such data to bring meaningful context to users’ behavior. As social applications are becoming prevalent, there is a trend for users to share their mobile data. The nature of online social networking poses new challenges for controlling access to private data, as compared to traditional enterprise systems. First, the user may have a large number of friends, each associated with a unique access policy. Second, the access control policies must be dynamic and fine-grained, i.e. they are content-based, as opposed to all-or-nothing. In this paper, we investigate the challenges in sharing of mobile data in social applications. We design and evaluate a middleware running on Google App Engine, named Mosco, that manages and facilitates sharing of mobile data in a privacy-preserving manner. We use Mosco to develop a location sharing and a health monitoring application. Mosco helps shorten the development process. Finally, we perform benchmarking experiments with Mosco, the results of which indicate small overhead and high scalability.     

A cloud-based platform to develop context-aware mobile applications by domain experts

Context-awareness enables the personalization of computer systems according to the users' needs and their particular situation at a given time. The personalization capabilities are usually implemented by programmers due to the complex processes that are involved. However, an important trend in software development is that more and more software systems are being implemented not only by programmers but also by people with expertise in other domains. Since most of the existing context-aware development toolkits are designed for programmers, non-technical users cannot develop these kinds of systems. The design of tools to create context-aware systems by users that do not have programming skills but are experts in the domain where the system is going to be deployed, will contribute to speed up the adoption of these kinds of services by the society. This paper presents a cloud-based platform to ease the development of context-aware mobile applications by people without programming skills. The platform has been designed to be used in a tourism domain. This way, tourism experts can send tourist information to mobile users according to their context data (indoor/outdoor location, language, and date and time range). An energy-efficient mobile app has been developed in order to obtain context data from the user's device and to receive personalized information in real time based on these data. The architecture and implementation details of the system are presented and the evaluation of the platform by tourism domain experts is discussed.     

User needs for location-aware mobile services

Mobile contexts of use vary a lot, and may even be continuously changing during use. The context is much more than location, but its other elements are still difficult to identify or measure. Location information is becoming an integral part of different mobile devices. Current mobile services can be enhanced with location-aware features, thus providing the user with a smooth transition towards context-aware services. Potential application fields can be found in areas such as travel information, shopping, entertainment, event information and different mobile professions. This paper studies location-aware mobile services from the user's point of view. The paper draws conclusions about key issues related to user needs, based on user interviews, laboratory and field evaluations with users, and expert evaluations of location-aware services. The user needs are presented under five main themes: topical and comprehensive contents, smooth user interaction, personal and user-generated contents, seamless service entities and privacy issues.     

Model-driven Engineering of Active Context-awareness

More and more Web users ask for contents and services highly tailored to their particular contexts of use. Especially due to the increasing affordability of new and powerful mobile communication devices, they also appreciate the availability of ubiquitous access, independent from the device actually in use. Due to such premises, traditional software design methods need to be extended, and new issues and requirements need to be addressed for supporting context-aware access to services and applications. In this paper we propose a model-driven approach towards adaptive, context-aware Web applications, accompanied by a general-purpose execution framework enabling active context-awareness. Whereas conventional adaptive hypermedia systems address the problem of adapting HTML pages in response to user-generated requests, in this work we especially stress the importance of user-independent, context-triggered adaptivity actions. This finally leads us to interpret the context as an active actor, operating independently from users during their navigations.     

Context-aware broadcasting approaches in mobile ad hoc networks

The aim of this paper is to compare different context-aware broadcasting approaches in mobile ad hoc networks (MANETs) and to evaluate their respective performances. Message broadcasting is one of the core challenges brought up by distributed systems and has therefore largely been studied in the context of traditional network structures, such as the Internet. With the emergence of MANETs, new broadcasting algorithms especially geared at these networks have been introduced. The goal of these broadcasting algorithms is to ensure that a maximum number of nodes deliver the broadcasted message (reliability), while ensuring that the minimum number of nodes retransmit the broadcasted message (efficiency), in order to save their resources, such as bandwidth or battery. In recent years, as more and more mobile devices have become context-aware, several broadcasting algorithms have been introduced that take advantage of contextual information in order to improve their performance. We distinguish four approaches with respect to context: (1) context-oblivious approaches, (2) network traffic-aware approaches, (3) power-aware approaches, and (4) location-aware approaches. This paper precisely aims at presenting these four different broadcasting approaches and at measuring the performance of algorithms built upon them.     

Modeling context in mobile distributed systems with the UML

Context-awareness plays an important role in mobile distributed systems since it enables the adaptation of mobile devices to the users. However, one of the major challenges is the preservation of the users’ privacy. Many different approaches of modeling the context of the user exist, but the incorporation of privacy restrictions into context models, which makes the protection of privacy apparent, is missing. This paper presents the Context Modeling Profile (CMP), a lightweight UML (Unified Modeling Language) extension, as a visual language for context models in mobile distributed systems. The resulting models embody metainformation of the context, i.e. source and validity of context information, and reflect privacy restrictions. The profile provides several well-formedness rules for context models and supports the development of context-aware mobile applications through an adequate visual modeling language. A case study is used to illustrate the approach.