A user-centric approach for personalized service provisioning in pervasive environments

Published version of an article published in Wireless Personal Communications (2011). Also available from the publisher at http://dx.doi.org/10.1007/s11277-011-0387-3The vision of pervasive environments is being realized more than ever with the proliferation of services and computing resources located in our surrounding environments. Identifying those services that deserve the attention of the user is becoming an increasingly-challenging task. In this paper, we present an adaptive multi-criteria decision making mechanism for recommending relevant services to the mobile user. In this context, "Relevance" is determined based on a user-centric approach that combines both the reputation of the service, the user's current context, the user's profile, as well as a record of the history of recommendations. Our decision making mechanism is adaptive in the sense that it is able to cope with users' contexts that are changing and drifts in the users' interests, while it simultaneously can track the reputations of services, and suppress repetitive notifications based on the history of the recommendations. The paper also includes some brief but comprehensive results concerning the task of tracking service reputations by analyzing and comprehending Word-of-Mouth communications, as well as by suppressing repetitive notifications. We believe that our architecture presents a significant contribution towards realizing intelligent and personalized service provisioning in pervasive environments

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.Deploying a network of sensors to monitor an environment is a common practice. For example, cameras in museums, supermarkets, or buildings are installed for surveillance purposes. However, while a decade ago, most deployed sensor networks involved a limited number of sensors, wired to a central processing unit, nowadays, the focus is on wireless, distributed, sensing nodes. Sensor technology has greatly advanced in terms of size, power consumption, processing capabilities, and low cost, thus fostering deployments of self-organizing wireless sensor networks over large geographical areas. For example, sensor networks have been used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Yet, sensor networks are usually perceived as ``something'' remote in the forest or on the battlefield, and regular users do not yet benefit from them. With the ubiquity and ever-increasing capabilities of mobile devices, such as smart phones and computers embedded in cars, urban environments offer the elements necessary to create people-centric mobile sensor networks and support a large variety of so-called sensing applications ranging from emergency and surveillance to tourist guidance and entertainment. For example, near-ubiquitous smart phones with audio and video sensing capabilities and more sensors in the near future can be used to provide shopping recommender services to inform users of special offers at the mall. Sensor-equipped cars can be used to provide traffic information services to alert drivers to upcoming traffic jams. However, urban mobile sensor networks are challenging programming environments due to the dynamism of mobile devices, the resource constraints of battery-powered devices, the software and hardware heterogeneity, and the large number of concurrent applications that they need to support. These requirements hinder the direct adoption of traditional distributed computing platforms developed for static resource-rich networks. This dissertation presents two architectures that can support the development of mobile sensing applications in urban environments. Contory offers a declarative programming model that views the urban network as a distributed sensor database. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption. The proposed architectures offer many opportunities to flexibly and quickly establish customized services that can greatly enhance the users' urban experience. Further steps to fully accomplish people-centric mobile sensing applications will have to address more technical issues as well as social and legal concerns

Recommending Services in Pervasive Environments

The presence of mobile devices with network connectivity continues to increase in all parts of the world, opening up direct channels to mobile users. The threat of information overload is prevalent, and if not subjected to control in terms of legislation and deployment of more intelligent and user-considerate systems it is likely to cause problems. This is particularly important in the case of push-based advertisement systems where information must be of relevance to the mobile user preferences, needs, and interest. This paper proposes a solution and architecture of a consumer-oriented, push-based, context aware location based advertisement system. The system is designed to operate in compliance with the World Wireless Research Foundation (WWRF) guidelines for the future space of information services: personalization, ambient awareness, and adaptability. The system is intended to operate in pervasive environments. The proposed system, called AdvertLBS, harvest knowledge about service providers and consumers in terms of preferences, geographical and temporal locations. The system applies knowledge about services, consumers, and learns context information in order to establish a broad service recommendation context. The AdvertLBS system adopts a hybrid approach to recommendation logic and proposes to use a subset of suitable matching algorithms to produce service recommendations relevant to the consumer’s interests and needs

Context-sensitive user Interfaces for semantic services

Service-centric solutions usually require rich context to fully deliver and better reflect on the underlying applications. We present a novel use of context in the form of customized user interface services with the concept of User Interface as a Service (UIaaS). UIaaS takes user profiles as input to generate context-aware interface services. Such interface services can be used as context to augment semantic services with contextual information leading to UIaaS as a Context (UIaaSaaC). The added serendipitous benefit of the proposed concept is that the composition of a customized user interface with the requested service is performed by the service composition engine, as is the case with any other services. We use a special-purpose language (called User Interface Description Language (UIDL)) to model and realize user interfaces as services. We use a real-life e-government application, human services delivery for the citizens, as a proof-of-concept. We also present a comprehensive evaluation of the proposed approach using a functional evaluation and a nonfunctional evaluation consisting of an end user usability test and expert usability reviews

Intelligent Learning Automata-based Strategies Applied to Personalized Service Provisioning in Pervasive Environments

Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, Grimstad, 201

Proximity-based systems: Incorporating mobility and scalability through proximity sensing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis argues that the concept of spatial proximity offers a viable and practical option for the development of context-aware systems for highly mobile and dynamic environments. Such systems would overcome the shortcomings experienced by today’s location-based and infrastructure dependent systems whose ability to deliver context-awareness is prescribed by their infrastructure. The proposed architecture will also allow for scalable interaction as against the single level of interaction in existing systems which limits services to a particular sized area. The thesis examines the concept of spatial proximity and demonstrates how this concept can be exploited to take advantage of technological convergence to offer mobility and scalability to systems. It discusses the design of a proximity-based system that can deliver scalable context-aware services in highly mobile and dynamic environments. It explores the practical application of this novel design in a proximity-sensitive messaging application by creating a proof-of-concept prototype. The proof-of-concept prototype is used to evaluate the design as well as to elicit user views and expectations about a proximity-based approach. Together these provide a valuable insight into the applicability of the proximity-based approach for designing context-aware systems. The design and development work discussed in the thesis presents a Proximity-Sensitive System Architecture that can be adapted for a variety of proximity-sensitive services. This is illustrated by means of examples, including a variety of context-aware messaging applications. The thesis also raises issues for information delivery, resource sharing, and human-computer interaction. While the technological solution (proximity-based messaging) offered is only one among several that can be developed using this architecture, it offers the opportunity to stimulate ideas in the relatively new field of proximity and technological convergence research, and contributes to a better understanding of their potential role in offering context-aware services