Vasile-Marian Scuturici

A comprehensive approach to model and use context for adapting applications in pervasive environments

With an increasing diversity of pervasive computing devices integrated in our surroundings and an increasing mobility of users, it will be important for computer systems and applications to be context-aware. Lots of works have already been done in this direction on how to capture context data and how to carry it to the application. Among the remaining challenges are to create the intelligence to analyze the context information and deduce the meaning out of it, and to integrate it into adaptable applications. Our work focuses on these challenges by defining generic context storage and processing model and by studying its impact on the application core. We propose a reusable context ontology model that is based on two levels: a generic level and a domain specific level. We propose a generic adaptation framework to guarantee adaptation of applications to the context in a pervasive computing environment. We also introduce a comprehensive adaptation approach that involves content adaptation and presentation adaptation inline with the adaptation of the core services of applications. Our case study shows that the context model and the application adaptation strategies provide promising service architecture.

A semantic approach to life cycle assessment applied on energy environmental impact data management

Environmental impact assessment of goods and services is nowadays a major challenge for both economic and ethical reasons. Life Cycle Assessment (LCA) provides a well-accepted methodology for modelling environmental impacts of human activities. One stage of the LCA methodology is Life Cycle Inventory, which consists of decomposing economic activities as elementary processes linked together through interdependency relations. This stage is needed in order to evaluate the environmental impacts of processes. A global analysis of economic activities requires considering a huge amount of elementary processes and interdependency links, making the model difficult to understand. In this paper, we propose a semantic approach for the modelling of lice cycle inventory databases. The method has the advantage of offering a more comprehensible model. We explain our model and illustrate it with life cycle inventory data for the U. S. electricity production.

Topological representation model for image database query

Search algorithms in image databases usually return k nearest neighbours (kNN) of an image according to a similarity measure. This approach presents some anomalies and is based on assumptions that are not always satisfied. We have examined the causes of these anomalies and we have concluded that image query models have to exploit topological properties rather than the similarity degree. This paper proposes a topological model based on neighbourhood graphs built on automatically extracted image features. Each image is represented as a feature vector in R p and stands for a node in the neighbourhood graph. The graph exploration corresponds to database browsing, the neighbours of a node represent similar images. In order to perform query by example, the query image is represented as a R p feature vector and inserted in the graph by locally updating the neighbourhood graph. The topology of an image database is more informative than a similarity measure usually applied in content based image retrieval, as proved by our experiments. A prototype of a visualization and query tool called Smart Image Query (SIQ) is also introduced.

Efficient Execution of Service Composition for Content Adaptation in Pervasive Computing

Multimedia content adaptation has been proved to be an effective mechanism to mitigate the problem of devices and networks heterogeneity and constraints in pervasive computing environments. Moreover, it enables to deliver data taking into consideration the users preferences and the context of his/her environment. In this paper, we present an algorithm for service composition and protocols for executing service composition plan. Both the algorithm and the protocols are implemented in our distributed content adaptation framework (DCAF) which provides a service-based content adaptation architecture. Finally, a performance evaluation of the algorithm and the protocols is presented.

ConAMi: Collaboration Based Content Adaptation Middleware for Pervasive Computing Environment

In this paper, we propose ConAMi, a collaboration - based content adaptation middleware, for a dynamic pervasive computing environment such as a mobile ad hoc network (MANET). ConAMi allows co-located devices to perform content adaptation in collaboration. A content adaptation is done by composing available services in the vicinity. To compose services efficiently, we propose an algorithm that arranges services in a colored tree.

UbiWare: web-based dynamic data & service management platform for AmI

The surrounding space is constantly augmented by a myriad of devices that expose heterogeneous data, like slower-changing data, dynamic data streams and functionalities. Developing applications that cope with heterogeneous data and diverse communication protocols is a tedious task. The success of such applications depends on the performance of data access and on the easy management of available data. To address these challenges, we propose UbiWare, a middleware that facilitates application development for ambient intelligence. We abstract the surrounding space as a database-like environment and the heterogeneous entities and devices as data services that produce data. To query the distributed data services and access their data, we introduce an API that greatly simplifies application development and is compatible with the different operators used by query engines in Data Stream Management Systems or Pervasive Environment Management Systems.

Positioning Support in Pervasive Environments

In order to implement reactive and proactive functionalities in a pervasive environment, contextual data must be processed. One of the most important features of the context is the position of the users and the devices. In this paper, we describe a method to determine the position of a WiFi enabled device. The prediction is based on the signal strength of the available access points. The prediction model is built from a database containing the signal strength measured in some known locations. The result is the name of the room/office where the device is localised. We also present a usage scenario, in which the user/device position is used to start proactive actions in our pervasive service environment called PerSE

Modeling user intention in pervasive service environments

The introduction of pervasive computing environments in everyday life will not just be a big step for users, but also for application designers. The well defined interaction interfaces will make place for other, more intuitive ways of interaction. It is the challenge for a pervasive system middleware to capture and model the user intention in a smart way and to solve ambiguousness in the user’s expression of a pervasive action. This paper introduces the Pervasive Service Action Query Language (PsaQL), a language to formalize the description of a user intention using composed pervasive services. The work describes a way of translating the user intention into an executable action and propose algorithms performing this translation. Considerations to implement this process are given within the scope of PerSE, a pervasive service environment developed by our research group, together with general evaluation metrics for such algorithms.

ColisTrack: testbed for a pervasive environment management system

One of the leading challenges for pervasive computing is to ease the application development to smoothly handle the surrounding environment. We consider the case where the environment produces heterogeneous and continuous data, e. g. temperature readings, car positions... We have defined a scenario for containers transportation tracking in a medical context involving the transportation of fragile biological matter in sensor-enhanced containers. This scenario has been simulated as a testbed and offers a very nice setting to measure the agility of data-centric application development. On top of this scenario, we have built a pervasive application using a Pervasive Environment Management System called SoCQ (Service oriented Continuous Queries). SoCQ provides a data-oriented perspective of the pervasive environment, mixing classical data, streams and functionalities. For the demo, our objective is twofold: first, from the application developer point of view, she has access to the underlying SoCQ-schema and she may pose her own SQL-like queries to the simulated environment. Second, from the end-user point of view, she may quite easily interact with the environment either through a general dynamic visualization with Google Maps of hospitals, cars moving along roads and medical containers waiting or being transported, or by getting SMS notifications on her own phone of results of predefined queries.

Multiple-robot monitoring system based on a service-oriented DBMS

In this paper, we present a human-targeted monitoring system composed of two autonomous mobile robots based on a service-oriented DBMS, mainly from the viewpoint of positioning control. Each robot is equipped with a Kinect and monitors the target human from appropriate angles and distances. The service-oriented DBMS, which manages the monitoring system and enables a rapid development and extension of the system, views each robot as a data source which generates a data stream to be stored and processed in the DBMS. The results of the experiments conducted in a real office are promising.