A multi-agent based user context Bayesian neural network analysis system

The increasing user mobility demands placed upon IT services necessitates an environment that enables users to access optimal services at any time and in any place. This study presents research conducted to develop a system that is capable of analyzing user IT service patterns and tendencies and provides the necessary service resources by sharing each user’s context information. First, each user’s context information is gathered to provide the multi-agent software training data necessary to describe user operations in a hybrid peer-to-peer (P2P) structured communication environment. Next, the data collected about each user’s mobile device is analyzed through a Bayesian based neural network system to identify the user’s tendency and extract essential service information. This information provides a communication configuration allowing the user access to the best communication service between the user’s mobile device and the local server at any time and in any place, thereby enhancing the ubiquitous computing environment.     

Design and implementation of a smart system for personalization and accurate selection of mobile services

Wireless mobile services are computing applications that run on handheld wireless devices. Such applications must work within the daunting constraints of the devices, which include memory, processing power, input capabilities, and size of display. It is therefore important that mobile services take into account the user’s context, optimize resource usage, and minimize input effort imposed on the user. In this paper, we present the design and implementation of a smart agent-enabled system for personalizing wireless mobile services and advertisements for Java 2 Micro Edition (J2ME) or Java ME, and Wireless Application Protocol (WAP) enabled devices. We use software agents for context filtering because such autonomous software entities have characteristics that can benefit mobile devices and the wireless environment, and the Composite Capability/Preference Profiles (CC/PP) standard for defining profiles for user preferences and device capabilities. The system incorporates the use of artificial neural networks to adaptively and iteratively learn to select the best available service based on contextual information. The system is evaluated using practical operating scenarios, as well as empirical data and results show an 87% success rate in the selection of the best available service.     

Learning opponent’s preferences for effective negotiation: an approach based on concept learning

We consider automated negotiation as a process carried out by software agents to reach a consensus. To automate negotiation, we expect agents to understand their user’s preferences, generate offers that will satisfy their user, and decide whether counter offers are satisfactory. For this purpose, a crucial aspect is the treatment of preferences. An agent not only needs to understand its own user’s preferences, but also its opponent’s preferences so that agreements can be reached. Accordingly, this paper proposes a learning algorithm that can be used by a producer during negotiation to understand consumer’s needs and to offer services that respect consumer’s preferences. Our proposed algorithm is based on inductive learning but also incorporates the idea of revision. Thus, as the negotiation proceeds, a producer can revise its idea of the consumer’s preferences. The learning is enhanced with the use of ontologies so that similar service requests can be identified and treated similarly. Further, the algorithm is targeted to learning both conjunctive as well as disjunctive preferences. Hence, even if the consumer’s preferences are specified in complex ways, our algorithm can learn and guide the producer to create well-targeted offers. Further, our algorithm can detect whether some preferences cannot be satisfied early and thus consensus cannot be reached. Our experimental results show that the producer using our learning algorithm negotiates faster and more successfully with customers compared to several other algorithms.     

A dual-layered model for web services representation and composition

Nowadays more and more companies and organizations implement their business services in the Internet due to the tremendous progress made recently in the field of Web services. It becomes possible to publish, locate and invoke applications across the Web. Thus, the ability to select efficiently and integrate at runtime services located in different sites on the Web is an important issue. In some situations, if no single Web service can satisfy the request of the user, there should be a possibility to combine existing services together in order to meet the user’s request. This paper provides a dual-layered model for web services, where the first model layer captures the high-level functional specifications (namely goals, achievement contexts, and external behaviours), and the second model layer captures the low-level functional specifications (namely interfaces). This model allows the service composition process to be performed on both high-level and low-level specifications. We also introduce the composition operators (both high-level and low-level) to allow composition of virtual services.     

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.     

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.     

A biologically inspired multimedia content repurposing system in heterogeneous environments

The application of biologically inspired algorithms to multimedia repurposing systems in heterogeneous network environments is gaining importance due to its ability to adapt and customize multimedia content to frequently changing network environments. This paper presents a biologically inspired proxy-based multimedia content adaptation system, which is used to repurpose multimedia content dynamically for the transmission over heterogeneous networks and end devices. We use a series of repurposing proxies’ services in a chain fashion between the sender and multiple end devices. In order to find the appropriate chain of repurposing services that satisfy the Quality of Experience (QoE) requirements, the proposed service selection algorithm uses the ant colony metaphor. During the communication session, the algorithm uses biological foraging behavior inspired from ant agents to find optimal service paths between the media sender and the destination. Experimental results demonstrate that the proposed algorithm provides significant performance gain over traditional, state of the art selection algorithms and saves the average delay.     

Adaptive IPTV services based on a novel IP Multimedia Subsystem

Heterogeneous communication devices are emerging and changing the way of communication. Innovative multimedia applications are now accessible through these embedded systems. The 3GPP IP Multimedia Subsystem (IMS) provides a basic architecture framework for the Next Generation Network (NGN) supporting the convergence platform for service provisioning in heterogeneous networks. ETSI TISPAN standardization effort focuses on delivering IPTV services on such platform. Nevertheless, IPTV on IMS standardization suffers from a lack of efficient user-centric network management mechanisms as the end-user may consume IPTV service from different access networks, on different mobile devices, at anytime. User’s Perceived Quality of Service (PQoS) or Quality of Experience (QoE) of IPTV service may also suffer from wireless access network impairments. This paper introduces new functionalities in IPTV over IMS architecture which optimize satisfaction of the end-user and resource utilization of the operator’s networks. A context-sensitive User Profile (UP) model is used to deliver IPTV streams adapted to the user’s environment. In order to optimize the operator network usage, the impact of spatiotemporal dynamics of the video content on the deduced perceptual quality is considered. A Multimedia Content Management System (MCMS) is proposed to perform dynamic cross-layer adaptation of the IPTV stream based on PQoS measurements at the end-user side.     

Exploring agent support at the user interface in e-commerce applications

In this paper, we present some of the results from our ongoing research work in the area of ‘agent support’ for electronic commerce, particularly at the user interface level. Our goal is to provide intelligent agents to assist both the consumers and the vendors in an electronic shopping environment. Users with a wide variety of different needs are expected to use the electronic shopping application and their expectations about the interface could vary a lot. Traditional studies of user interface technology have shown the existence of a ‘gap’ between what the user interface actually lets the users do and the users’ expectations. Agent technology, in the form of personalized user interface agents, can help to narrow this gap. Such agents can be used to give a personalized service to the user by knowing the user’s preferences. By doing so, they can assist in the various stages of the users’ shopping process, provide tailored product recommendations by filtering information on behalf of their users and reduce the information overload. From a vendor’s perspective, a software sales agent could be used for price negotiation with the consumer. Such agents would give the flexibility offered by negotiation without the burden of having to provide human presence to an online store to handle such negotiations. Published online: 25 July 2001     

MASHA: A multi-agent system handling user and device adaptivity of Web sites

A user that navigates on the Web using different devices should be characterized by a global profile, which represents his behaviour when using all these devices. Then, the user’s profile could be usefully exploited when interacting with a site agent that is able to provide useful recommendations on the basis of the user’s interests, on one hand, and to adapt the site presentation to the device currently exploited by the user, on the other hand. However, it is not suitable to construct such a global profile by a software running on the exploited device since this device (e.g., a mobile phone or a palmtop) may have limited resources. Therefore, in this paper, we propose a multi-agent architecture, called MASHA, handling user and device adaptivity of Web sites, in which each device is provided with a client agent that autonomously collects information about the user’s behaviour associated to just that device. However, the user profile contained in this client is continuously updated with information coming from a unique server agent, associated with the user. Such information is collected by the server agent from the different devices exploited by the user, and represents a global user profile. The third component of this architecture, called adapter agent, is capable to generate a personalized representation of the Web site, containing some useful recommendations derived by both an analysis of the user profile and the suggestions coming from other users exploiting the same device.     

A user-adaptive city guide system with an unobtrusive navigation interface

In this paper, we describe an intelligent location-aware city guide system, which adapts to each user’s preferences, and uses an intuitive “metal detector” interface for navigation. Our system analyzes each user’s past location data history to estimate individual preferences, and allows users to find shops that match their tastes in the same way a metal detector would be used to detect metal objects. The procedure with which the system picks out shops that match each user’s preferences includes a newly developed place learning algorithm, which can efficiently find frequented places, complete with their proper names (e.g. “The Ueno Royal Museum”). We have conducted a series of evaluation tests at a popular shopping district inside Tokyo, and the results validate the effectiveness of our overall approach.     

Mobile home automation: merging mobile value added services and home automation technologies

In this paper we study mobile home automation, a field that emerges from an integration of mobile application platforms and home automation technologies. We motivate our research and provide a conceptual introduction, which illustrates the need for such applications by a two-dimensional conceptual model of mobility. As a first steps towards a solution we take the user’s perspective and discuss different options of how he might access a mobile home automation service and the controlled devices. Subsequently, we suggest a general system architecture for mobile home automation services and discuss related design decision. This design has been implemented in a research prototype, which we named Remotile. This helps us to discuss typical components, such as modules that integrate various home automation devices. A previous version of this paper was presented at the Sixth International Conference on Mobile Business, 2007. “Andreas Rosendahl, J. Felix Hampe, and Goetz Botterweck, Mobile Home Automation, Merging Mobile Value Added Services and Home Automation Technologies, Proceedings, Sixth International Conference on Mobile Business, 8–11 July 2007, IEEE Computer Society, ISBN 0-7695-2803-1”.     

Supporting device discovery and spontaneous interaction with spatial references

The RELATE interaction model is designed to support spontaneous interaction of mobile users with devices and services in their environment. The model is based on spatial references that capture the spatial relationship of a user’s device with other co-located devices. Spatial references are obtained by relative position sensing and integrated in the mobile user interface to spatially visualize the arrangement of discovered devices, and to provide direct access for interaction across devices. In this paper we discuss two prototype systems demonstrating the utility of the model in collaborative and mobile settings, and present a study on usability of spatial list and map representations for device selection.     

A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives

Although a few studies have focused on mobile value from the distinctive feature of a mobile technology perspective, limited attempts have been made from a mobile user’s value tendency perspective. In this study, building upon prior research on productivity-oriented and pleasure-oriented nature of systems, we categorize mobile values as having utilitarian and hedonic use. Based on these two values, we conceptualize types of tendency of mobile users’ application use namely utilitarian tendency and hedonic tendency. The goal of this study is to examine the relationships between mobile consumers’ value tendency and their perceptions of mobile Internet service quality in terms of three different mobile quality dimensions (i.e., connection quality, design quality, and information quality). In addition, drawing upon the “digital divide” literature, the relationships between mobile users’ personal dispositions (i.e., maturity and socio-economic status) and their mobile value tendency are also tested. The empirical results of the study, the interpretation of the results, research contributions, and limitations are discussed.     

A context-aware mobile application framework using audio watermarking

Multimedia Systems - In this paper, we propose a proximity-based indoor positioning system which is capable of monitoring mobile device user’s indoor locations where the commonly used GPS...     

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.