Juan Carlos López

Intelligent Agents for Automatic Service Composition in Ambient Intelligence

The Ubiquitous Computing concept was first defined by Mark Weiser in (Weiser, 1995), referring to a new computing era where electronic devices merge with the background, becoming invisible, in such a way that people could make use of those devices in an unconsciously way, focusing just on their needs and not in the interaction. One decade later, the IST Advisory Group first states the concept of Ambient Intelligence (Ducatel et al., 2001), which lying on the ubiquitous computing paradigm, refers to those environments where people are surrounded by all kind of intelligent intuitive devices, capable of recognising and responding to their changing needs. In these contexts, people perceive the surrounding as a service provider that satisfies their needs or inquiries in a seamless, unobtrusive, and invisible way. These computing paradigms set a frame of reference, characterised by being mainly concentrated on releasing mechanisms that gather information about users, match behavioural patterns, or predict user actions, requirements and needs (Costa et al., 2007) (Cugola & Picco, 2006) (Issarny et al., 2005) (Prete & Capra, 2008). Nevertheless, the Ambient Intelligence paradigm is meant to consider users as constituent parts of the context, although in most solutions presented to date, users are considered in isolation. In this regard, extending the user-centered view, in order to encompass the context services and purposes, arises as key requirements for systems in Ambient Intelligence. It soon becomes apparent the need for a multidisciplinary approach capable of addressing all the emerging challenges. One of these fields is concerned with the communication support. The heterogeneity of the context devices, as well as their dinamism, impose high demands upon the middleware platform, that it is now responsible for abstracting the technological peculiarities. It is then possible to provide a common and well-known set of communication interfaces. These interfaces are described in terms of a semantic model, that can be easily shared and translated into different languages, so that in can be used by the rest of involved technologies (intelligent agents and reasoning engine). Finally, and probably the most important part of the provided solution, refers to the context-awareness, in charge of understanding the context. This requires some approach that resembles human behaviour in regard to its ability to deal with information of an imprecise nature, ambiguous, and of a questionable retrievability, but also capable of making decisions based on this partial information. To this 2

Process-in-Network: A Comprehensive Network Processing Approach

A solid and versatile communications platform is very important in modern Ambient Intelligence (AmI) applications, which usually require the transmission of large amounts of multimedia information over a highly heterogeneous network. This article focuses on the concept of Process-in-Network (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and introduces a more comprehensive approach than current network processing technologies. PIN can take advantage of waiting times in queues of routers, idle processing capacity in intermediate nodes, and the information that passes through the network.

Efficient and decentralized data transfer architecture for component based embedded systems

Multimedia embedded systems usually expose a chain-based architecture where each functional stage of the media algorithm is encapsulated in a media core in charge of processing the stream of data. Therefore, in this kind of systems, the interconnection mechanisms are key to cope with the enormous bandwidth demands. In this paper, we present a decentralized data transfer architecture for bus based embedded systems. The communication infrastructure introduced here is parameterizable, dynamically configurable and optimized for hardware media component processing platforms. Unlike conventional approaches, where a software control routine has to oversee all the steps of the data exchanging process (e.g. DMA configuration, trapping interruptions, ...), our approach moves such responsibility to the hardware components which are highly autonomous. This has a positive impact in performance since the processor is not mediating in every single data transfer that takes place in the system.

Flexible, Open and Efficient Embedded Multimedia Systems

The first approaches dealing with hardware-based acceleration were based on the design of custom ASICs (Application Specific Integrated Circuits) or the use of DSPs (Digital Signal Processors). Lately, the emergence of high capacity reconfigurable devices such as FPGAs (Field Programmable Gate Arrays) is encouraging developers to use this technology for the implementation of multimedia embedded systems. Some of the reasons that back up this trend are: short development/prototyping time, the ability to customize hardware, its flexibility, or reconfiguration facilities, just to name a few of them.

Services Everywhere: an Object-Oriented Distributed Platform to Support Pervasive Access to HW and SW Objects in Ambient Intelligence Environments

The Ubiquitous Computing concept was first defined by Mark Weiser (Weiser, 1995) and it refers to a new computing era where electronic devices merge with the background. People make use of those electronic devices unconsciously, focusing just on their needs and not in how to accomplish them. The concept of Ambient Intelligence (Ducatel et al., 2001), lying on the ubiquitous computing paradigm, refers to those environments where people are surrounded by all kind of intelligent intuitive devices, capable of recognising and responding to their changing needs. People perceive the surroundings as a service provider that satisfies their needs or inquiries in a seamless, unobstrusive and invisible way. It is generally agreed that AmI (Ambient Intelligence) will have a great impact in economy and society. The potential of AmI technologies in various application areas has been object of numerous studies. For example, the IPTS/ESTO Ambient Intelligence in Everyday Life Roadmap (Friedewald & Da Costa, 2003) report analyzes key application areas in order to find out which are the technological requirements that must support the functions that will make the difference in each of those application areas (housing, mobility and transport, shopping and commerce, education and learning, health, culture, leisure and entertainment). But AmI is not only its technological facet. There is also a social and a politics dimension besides the devices and software upon which the intelligent environments are built. Technology must be helpfull, work with users and not against them trying to pull down the wall of the natual resistance of the human being to revolutionary changes.