IoT-A and FIWARE: bridging the barriers between the Cloud and IoT systems design and implementation

Abstract: IoT systems are designed and implemented to address specific challenges based on domain specific requirements, thus not taking into consideration issues of openness, scalability, interoperability and use-case independence. As a result, they are less principled, vendor oriented and hardly replicable since the same IoT architecture cannot be used in more than one use-cases. To address the fragmentation of existing IoT solutions, the IoT-A project proposes an architecture reference model that defines the principles and standards for generating IoT architectures and promoting the interoperation of IoT solutions. However, IoT-A addresses the architecture design problem, and does not focus on whether existing cloud platforms can offer the tools and services to support the implementation of IoT-A compliant IoT systems. In this work we attempt to fill this gap and we propose an architectural approach based on IoT-A that focuses (as a use case) on the FIWARE open cloud platform that in turn provides the building blocks of Future Internet (FI) applications and services. We further correlate FIWARE and IoT-A approaches to identify the key features for FIWARE to support IoT-A compliant system implementations

Image Representation, Indexing and Retrieval Based on Spatial Relationships and Properties of Objects

IN THIS thesis, a new methodology is presented which supports the efficient representation, indexing and retrieval of images by content. Images may be indexed and accessed based on spatial relationships between objects, properties of individual objects, and properties of object classes. In particular, images are first decomposed into groups of objects, called "image subsets", and are indexed by computing addresses to all such groups. All groups up to a predefined maximum size are considered. This methodology supports the efficient processing of queries by image example and avoids exhaustive searching through the entire image database

Weighted Link Analysis for Logo and Trademark Image Retrieval on the Web

Image retrieval on the Web requires that important (authoritative) images satisfying the query selection criteria are assigned higher ranking over other relevant images. PicASHOW [5] achieves this goal using link information alone. This work proposes WPicASHOW (Weighted PicASHOW) a weighted scheme for co-citation analysis that incorporates within the link analysis method of PicASHOW the text and image content of the queries and of the Web pages. WPicASHOW is implemented and integrated into a fully automated Web retrieval system for logo and trademark images

A measure for cluster cohesion in semantic overlay networks

Semantic overlay networks cluster peers that are semantically, thematically or socially close into groups by means of a rewiring procedure that is periodically executed by each peer. Rewiring proceeds by establishing new connections to similar peers, and by discarding connections that are outdated or pointing to dissimilar peers. This process aims at improving cluster quality (how well peers with similar content are clustered together) and by this, at improving the flow of information in the network by reducing the number of messages that are exchanged. Therefore, measuring the quality of clustering is an important issue by itself. This is exactly the issue this work is dealing with. In this paper, we introduce a new clustering measure that takes into account the whole neighborhood of a peer (rather than its direct neighbors) thus, providing better insight on the quality of the underlying clustered organisation. Our experimental evaluation with real-word data and queries confirms our assumption that the new measure is better suited for measuring clustering quality than other known measures, such as the (generalised) clustering coefficient