No abstract

Location is considered as the most important and relevant context information. Bluetooth technology, being a common feature of commercial mobile devices, is a (or the) key technology that is pervasively available nowadays. There has been not much success in using Bluetooth technology for indoor localization, mainly due to the limitation of the technology. Using the Context Management Frame (CMF) infrastructure deployed in our office building, we have designed, implemented and evaluated a Bluetooth based indoor localization solution that determines the locations of stationary mobile users at a room level. The solution is based on the inquiry response rate of Bluetooth technology. This approach does not require establishing any connectivity between Bluetooth devices. Further, since the solution is infrastructure-and network-based, it does not require mobile devices to be upgraded in any way in order to be localized. The results of experiments show that our solution has 98% accuracy in rooms with full Bluetooth sensor coverage, when the target device being stationary for 3 minutes.

Synchronous dataow (SDF) graphs are a widely used formalism for modelling, analysing and realising streaming applications, both on a single processor and a multiprocessing context. Ecient schedules are necessary to obtain maximal throughput with the optimum energy consumption in such a way that the number of resources used to run these applications is kept as low a possible. This paper presents an approach of scheduling SDF graphs using a proven formalism for timed systems called timed automata (TA). TA holds a good balance between the expressiveness and tractability, and are supported by many verication tools e.g. Kronos and Uppaal. We describe an algorithm for the compositional translation of SDF graphs to TA and implementation of the translation to analyse and verify SDF graphs in state-of-the-art tool Uppaal. This approach does not require any transformation of SDF graphs to HSDF graphs and helps to nd the schedules with a best compromise between number of the processors required and the throughput. It also allows quantitative model checking and verication of the user-dened properties like absence of deadlocks, safety, liveness and throughput analysis. The translation also forms the basis for future work of extending SDF graphs with the new features, e.g. stochastics, energy consumption and costs. This work also strives for bridging and extending the modelling computational formalisms towards energy aspects of self supporting computation. * This research has been supported by the EU FP7 project named SENSATION.

Today's consumers have a wide variety of interactive media and services at their disposal, for instance, through IPTV networks, the Internet, and in-home and mobile networks. A major problem, however, is that media and services do not interoperate across networks because they use different user identities, metadata formats, and signaling protocols, for example. As a result, users cannot easily combine media and services from different network infrastructures and share them in an integrated manner with their family and friends. In addition to limiting people's media experience, this also hinders the introduction of new services and business models as providers cannot easily develop and operate cross-network services. The goal of our work is to overcome this problem by means of an open and intelligent service platform that allows applications to easily combine media and services from different network infrastructures, and enables consumers to easily share them in an integrated way. The platform includes support for managing multi-user sessions across networks, context-aware recommendations, and cross-network identity management. While there has been prior work on platforms for converged media, our platform is unique in that it provides open, intelligent, and interoperable facilities for sharing media and services across network infrastructures. In addition, our work involves several specific innovations, for instance, pertaining to cross-network session management and synchronization. In this article we discuss the platform, its most important enabling services, and some of the applications we have built on top of it. We also briefly consider the new kinds of business models our platform makes possible

Abstract-In this paper we present a novel approach to throughput analysis of synchronous dataflow (SDF) graphs. Our approach is based on describing the evolution of actor firing times as a linear time-invariant system in max-plus algebra. Experimental results indicate that our approach is faster than stateof-the-art approaches to throughput analysis of SDF graphs. The efficiency of our approach is due to the exploitation of the regular structure of the max-plus system's graphical representation, the properties of which we thoroughly prove.