Look, Ma, My homepage is Mobile!

Much of the ongoing research in ubiquitous computing has concentrated on providing context information, e.g. location information, to the level of services and applications. Typically, mobile clients obtain location information from their environment which is used to provide “locally optimal” services. In contrast, it may be of interest to obtain information about the current context a mobile user or device is in, from a client somewhere on the Web, i.e. to use the mobile device as an information provider for Internet clients. As an instance of such services we propose the metaphor of a “location-aware” Web homepage of mobile users providing information about, e.g. the current location a mobile user is at. Requesting this homepage can be as easy as typing a URL containing the mobile user's phone number such ashttp://mhp.net/+49123456789 in an off-the-shelf browser. The homepage is dynamically constructed as Web users access it and it can be configured in various ways that are controlled by the mobile user. We present the architecture and implementation and discuss issues around this example of “inverse” ubiquitous computing.     

Location-dependent services for mobile users

One of the main issues in mobile services' research (M-service) is supporting M-service availability, regardless of the user's context (physical location, device employed, etc.). However, most scenarios also require the enforcement of context-awareness, to dynamically adapt M-services depending on the context in which they are requested. In this paper, we focus on the problem of adapting M-services depending on the users' location, whether physical (in space) or logical (within a specific distributed group/application). To this end, we propose a framework to model users' location via a multiplicity of local and active service contexts. First, service contexts represent the mean to access to M-services available within a physical locality. This leads to an intrinsic dependency of M-service on the users' physical location. Second, the execution of service contexts can be tuned depending on who is requesting what M-service. This enables adapting M-services to the logical location of users (e.g., a request can lead to different executions for users belonging to different groups/applications). The paper firstly describes the framework in general terms, showing how it can facilitate the design of distributed applications involving mobile users as well as mobile agents. Then, it shows how the MARS coordination middleware, implementing service contexts in terms of programmable tuple spaces, can be used to develop and deploy applications and M-services coherently with the above framework. A case study is introduced and discussed through the paper to clarify our approach and to show its effectiveness.     

An unsupervised approach to modeling personalized contexts of mobile users

Mobile context modeling is a process of recognizing and reasoning about contexts and situations in a mobile environment, which is critical for the success of context-aware mobile services. While there are prior works on mobile context modeling, the use of unsupervised learning techniques for mobile context modeling is still under-explored. Indeed, unsupervised techniques have the ability to learn personalized contexts, which are difficult to be predefined. To that end, in this paper, we propose an unsupervised approach to modeling personalized contexts of mobile users. Along this line, we first segment the raw context data sequences of mobile users into context sessions where a context session contains a group of adjacent context records which are mutually similar and usually reflect the similar contexts. Then, we exploit two methods for mining personalized contexts from context sessions. The first method is to cluster context sessions and then to extract the frequent contextual feature-value pairs from context session clusters as contexts. The second method leverages topic models to learn personalized contexts in the form of probabilistic distributions of raw context data from the context sessions. Finally, experimental results on real-world data show that the proposed approach is efficient and effective for mining personalized contexts of mobile users.     

Personal service areas for mobile Web applications

Location-based mobile services let wireless mobile users access Web-based information about resources in their immediate vicinities. The authors describe an algorithm that draws on context mobility elements, such as the user's travel direction and speed, to form personal service areas. Their experimental context-aware tourist information system (CATIS) leverages XML technologies and Web services to provide tourist information to mobile users based on these personal service areas and the users' preferences. Because Web service performance depends on the underlying databases, the authors also developed a layered caching scheme for storing environmental data to improve response time.     

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.     

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.     

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.

Contextualized mobile recommendation service based on interactive social network discovered from mobile users

Personal context is the most significant information for providing contextualized mobile recommendation services at a certain time and place. However, it is very difficult for service providers to be aware of the personal contexts, because each person’s activities and preferences are very ambiguous and depending on numerous unknown factors. In order to deal with this problem, we have focused on discovering social relationships (e.g., family, friends, colleagues and so on) between people. We have assumed that the personal context of a certain person is interrelated with those of other people, and investigated how to employ his neighbor’s contexts, which possibly have a meaningful influence on his personal context. It indicates that we have to discover implicit social networks which express the contextual dependencies between people. Thereby, in this paper, we propose an interactive approach to build meaningful social networks by interacting with human experts. Given a certain social relation (e.g., isFatherOf), this proposed systems can evaluate a set of conditions (which are represented as propositional axioms) asserted from the human experts, and show them a social network resulted from data mining tools. More importantly, social network ontology has been exploited to consistently guide them by proving whether the conditions are logically verified, and to refine the discovered social networks. We expect these social network is applicable to generate context-based recommendation services. In this research project, we have applied the proposed system to discover the social networks between mobile users by collecting a dataset from about two millions of users.     

Long-term location privacy protection for location-based services in mobile cloud computing

The popularity of mobile devices, especially intelligent mobile phones, significantly prompt various location-based services (LBSs) in cloud systems. These services not only greatly facilitate people’s daily lives, but also cause serious threats that users’ location information may be misused or leaked by service providers. The dummy-based privacy protection techniques have significant advantages over others because they neither rely on trusted servers nor need adequate number of trustworthy peers. Existing dummy-based location privacy protection schemes, however, cannot yet provide long-term privacy protection. In this paper, we propose four principles for the dummy-based long-term location privacy protection (LT-LPP). Based on the principles, we propose a set of long-term consistent dummy generation algorithms for the LT-LPP. Our approach is built on soft computing techniques and can balance the preferred privacy protection and computing cost. Comprehensive experimental results demonstrate that our approach is effective to both long-term privacy protection and fake path generation for LBSs in mobile clouds.     

Contextual usage patterns in smartphone communication services

The mobile end user context has received a lot of attention from the mobile services industry lately. The location-based and context-sensitive information that are characteristic for smartphones can be utilized to study the use context of mobile end users. Accordingly, this article utilizes handset-based data in analyzing how the context of use affects the usage of smartphone communication services. The context is identified with an algorithm utilizing mobile network cell ID and WLAN data and resulting in five place-related contexts, namely Home, Office, Other meaningful, Elsewhere and Abroad. According to our analysis, voice calls are used least intensively in the Home context where the length of the voice calls is the longest, however. Email and SMS are used most intensively in the Office context, where the voice calls are the shortest in duration. Finally, mobile IM/VoIP and social media services are more free-time oriented as they are used most intensively in Elsewhere and Other meaningful contexts. The findings imply that people use smartphone communication services differently depending on the use context. However, context can be defined and identified in a number of ways, and this article presents only one solution that is highly dependent on the type of data collected.     

A new model for context-aware transactions in mobile services

With the ubiquity of handheld devices (such as smart phones and PDAs) and the availability of a wide range of mobile services (such as mobile banking, road traffic updates, and weather forecast), people can nowadays access information and conduct online transactions virtually anywhere and anytime. In such flexible, dynamic but less reliable environment, transaction management technology is believed to provide service reliability and data consistency. Indeed, in mobile and ubiquitous environments where devices as well as services can seamlessly join and leave the ubiquitous network; transaction management can be very helpful during the recovery of services from failure. Current transaction models and commit protocols do not take into account context information. However, in mobile environments, it is imperative to consider context information in the commit of a transaction—i.e., a transaction can be successfully completed if it meets the required context. In this paper, we propose a new model for context-aware transactions and their performance management in mobile environments. Unlike conventional transactions, context-aware transactions adapt to the required context. By context, we mean the service’s context as well as the users’ context that includes users’ needs and preferences. This paper designs and develops the proposed transaction model and evaluates its performance in terms of time and message complexities as well as transaction’s throughput.     

There is more to context than location

Context is a key issue in interaction between human and computer, describing the surrounding facts that add meaning. In mobile computing location is usually used to approximate context and to implement context-aware applications. We propose that ultra-mobile computing, characterized by devices that are operational and operated while on the move (e.g. PDAs, mobile phones, wearable computers), can significantly benefit from a wider notion of context. To structure the field we introduce a working model for context, discuss mechanisms to acquire context beyond location, and application of context-awareness in ultra-mobile computing. We investigate the utility of sensors for context-awareness and present two prototypical implementations — a light-sensitive display and an orientation-aware PDA interface. The concept is then extended to a model for sensor fusion to enable more sophisticated context recognition. Based on an implementation of the model an experiment is described and the feasibility of the approach is demonstrated. Further, we explore fusion of sensors for acquisition of information on more sophisticated contexts.     

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．     

移动位置服务的应用发展研究

移动位置服务是移动运营商和服务提供商联合推出的基于地理位置信息服务,用户通过移动终端获取位置信息及产品服务。中国的移动位置服务开展较早,但相比于美国等发达国家,并没有获得用户的广泛接受。本文通过研究移动位置服务的发展现状和用户行为,提出发展对策。     

Recommendation system using location-based ontology on wireless internet: An example of collective intelligence by using ‘mashup’ applications

Location-Based Service (LBS) is considered as a key component of upcoming ubiquitous environments. A recommendation system based on LBS is expected to be an important service in ubiquitous environments, and most hardware technologies such as location estimation of a user by using Global Positioning System (GPS), as well as hi-speed internet access through cell phones, are currently supported. However, in terms of software, most services are driven and supported by a LBS service provider only. Consequently, lack of participation of users may occur in mobile environments. In this study, we suggest a LBS knowledge base inference platform with ontology which considers the current location and available time of users. Our knowledge base supports user participation as collective intelligence. We mashed up Open Application Programming Interface (OpenAPI) for scalable implementation of the system. Through experiments, we show that a user can build up his/her knowledge base, and by using this information, the system recommends to other users appropriate information that matches the user’s condition and profile through inference.     

A Global Ticket-Based Access Scheme for Mobile Users

This article presents a ticket-based access model for mobile services. The model supports efficient authentication of users, services and service providers over different domains. Tickets are used to verify correctness of the requested service as well as to direct billing information to the appropriate user. The service providers can avoid roaming to multiple service domains, only contacting a Credential Centre to certify the user's ticket since tickets carry all authorization information needed for the requested services. The user can preserve anonymity and read a clear record of charges in the Credential Centre at anytime. Furthermore, the identity of misbehaving users can be revealed by a Trusted Centre.     

Joint contexts optimization for mobile grid

This paper presents joint contexts optimization in mobile grid. The paper describes device context information for context-aware services in the mobile device collaboration. The objective of the paper is to dynamically deliver services to mobile grid users according to current context of mobile grid environment. A utility function is used as objective function that expresses values for the current contexts. The optimization is carried out by the joint context parameter optimizer with respect to an objective function. A joint contexts optimization algorithm is proposed which decomposes mobile grid system optimization problem into sub-problems. In the experiment, the performance evaluation of joint contexts optimization algorithm is conducted.     

Transaction pseudonyms in mobile environments

Network Operators start to offer formerly hidden services such as location service, messaging services and presence services. This fosters the development of a new class of innovative context aware applications that are operated by third party application providers. However, without the implementation of proper privacy protection mechanisms, location and presence information, that is processed by third party application providers, may also imply severe risks to users. If no privacy protection is foreseen, the user’s identity could be used maliciously which renders such applications dangerous. To protect the user’s sensitive data such as location information we propose a novel service architecture which fosters the development of innovative applications that brings together internet applications with telco services. An underlying privacy enhancing mechanism that is based on the notion of pseudonyms allows even untrusted third party application providers to access sensitive data provided by telco services such as location, presence or messaging services. Due to their high security, pseudonyms guarantee that the user’s identity is kept secret towards the untrusted application providers. Due to its low computational complexity this pseudonym generation scheme can also be implemented on devices such as mobile phones and digital assistants with only little computational power and restricted memory capabilities. To illustrate our approach, we demonstrate a transportation ticket application that implements the proposed service architecture. This application allows the use of transportation tickets which are extended by the location-tracking functionality. Similar to the well known paper based transportation tickets our solution supports anonymity of users even if the ticket application “knows” the location of the holder. Oliver Jorns is a researcher at the Telecommunications Research Center in Vienna and is also a Lecturer at the University of Vienna. Oliver Jung is employed as a Senior Researcher at the Telecommunications Research Center Vienna. He is also member of ISO/IEC JTC1 SC27 (IT security techniques). Gerald Quirchmayr is Professor at the Institute for Computer Science and Business Informatics at the University of Vienna and since January 2005 he heads the Department of Distributed and Multimedia Systems, Faculty of Computer Science, at the University of Vienna.     

Protecting location privacy in mobile geoservices using fuzzy inference systems

Mobile geoservices, especially location-based services (LBSs), are becoming more popular each day. The most important goal of these services is to use a user’s location to provide location-aware services. Because the user’s spatial information can be abused by organizations or advertisers, and sometimes for criminal purposes, the protection of this information is a necessary part of such services. There has been substantial research on privacy protection in LBSs and mobile geoservices; most studies have attempted to anonymize the user and hide his/her identity or to engage the user in the protection process. The major defects of these previous approaches include an increased complexity of system architecture, a decrease in service capabilities, undesirable processing times, and a failure to satisfy users. Additionally, anonymization is not a suitable solution for context-aware services. Therefore, in this paper, a new approach is proposed to locate users with different levels of spatial precision, based on his/her spatio-temporal context and a user’s group, through fuzzy inference systems. The user’s location and the time of the request determine the spatio-temporal context of the user. A fuzzy rule base is formed separately for each group of users and services. An interview is a simple method to extract the rules. The spatial precision of a user’s location, which is obtained from a fuzzy system, goes to a spatial function called the conceptualization function, to determine the user’s location based on one of the following five levels of qualitative precision: geometrical coordinates, streets, parish, region, and qualitative location, such as the eastern part of the city. Thus, there is no need to anonymize users in mobile geoservices or to turn the service off. The applicability and efficiency of the proposed method are shown for a group of taxi drivers.     

Building a Context Sensitive Telephone: Some Hopes and Pitfalls for Context Sensitive Computing

Although the idea of making technology more context aware is an alluring one, this seemingly simple move hides a great deal of complexity. Even simple examples such as a context sensitive mobile phone which knows when not to ring, are unlikely to be successful. Any context sensitive technology is likely to make mistakes – like ringing in the middle of a film, or not ringing for an urgent call. Using three examples from fieldwork of alerting systems (two ringing phones and one medical alarm in a hospital), we suggest three guidelines for context systems which could genuinely assist users. First, we argue that context sensitive computing should be used defensively, where incorrect behaviour is tolerable. Second, that technology can provide structures to which people themselves can add context. Third, that technology can communicate context to users, allowing users to make sense of that contextual information themselves. Lastly we argue for an understanding of the long term use of technology use, dwelling with technology, a process which changes how the world is seen and experienced.