Interoperability remains a fundamental challenge when connecting heterogeneous systems which encounter and spontaneously communicate with one another in pervasive computing environments. This challenge is exasperated by the highly heterogeneous technologies employed by each of the interacting parties, i.e., in terms of hardware, operating system, middleware protocols, and application protocols. This paper introduces Connect, a software framework which aims to resolve this interoperability challenge in a fundamentally different way. Connect dynamically discovers information about the running systems, uses learning to build a richer view of a system's behaviour and then uses synthesis techniques to generate a connector to achieve interoperability between heterogeneous systems. Here, we introduce the key elements of Connect and describe its application to a distributed marketplace application involving heterogeneous technologies.
We present IYOUIT, a prototype service to pioneer a context-aware mobile digital lifestyle and its reflection on the Web. The application is based on a distributed infrastructure that incorporates Semantic Web technologies in several places to derive qualitative interpretations of a user's digital traces in the real world. Networked components map quantitative sensor data to qualitative abstractions represented in formal ontologies. Subsequent classification processes combine these with formalized domain knowledge to derive meaningful interpretations and to recognize exceptional events in context histories. The application is made available on Nokia Series-60 phones and designed to seamlessly run 24/7.
Data interoperability is one of the main problems of system interoperability. Indeed, it is estimated that the cost of data interoperability ranges in the billions of dollars every year. The traditional approach to data interoperability is to define mappings between different data structures and different data formats. Whereas this is surely a very important part of the problem, it is not its only aspect. Often systems need to aggregate data coming from different systems, and to reason and derive conclusions from these data. In this paper, we will review the efforts performed in the semantic web to unlock this problem and highlight trends and pitfalls.
Many current smartphones need to be recharged every day despite only average usage. This problem is intensified when phones need to track their location on a continuous basis. We provide a yet unavailable platform for accurately measuring the energy consumption of different hardware / software solutions comparing up to three variants in a mobile setting. We show that the accuracy of our system is similar to a fixed, commercial system but is especially useful to evaluate and optimize technology and algorithms that require the phone to be used on the go.
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