Survey of context provisioning middleware

In the scope of ubiquitous computing, one of the key issues is the awareness of context, which includes diverse aspects of the user's situation including his activities, physical surroundings, location, emotions and social relations, device and network characteristics and their interaction with each other. This contextual knowledge is typically acquired from physical, virtual or logical sensors. To overcome problems of heterogeneity and hide complexity, a significant number of middleware approaches have been proposed for systematic and coherent access to manifold context parameters. These frameworks deal particularly with context representation, context management and reasoning, i.e. deriving abstract knowledge from raw sensor data. This article surveys not only related work in these three categories but also the required evaluation principles. © 2009-2012 IEEE

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Service testing for the internet of things.

Services that represent sensor and actuator nodes, together with service orchestration, aid in overcoming the heterogeneous structure of the Internet of Things (IoT). Interconnecting different sensor and actuator nodes and exposing them as services is a complex topic which is even more demanding for testing. Further effort is needed to enable common and effcient methodologies for testing IoT-based services. IoT-based services differ from web services since they usually interact with the physical environment via sensor and actuator nodes. This changes how testing can be performed. An open research question is thereby how to apply Model-Based Testing (MBT) approaches for facilitating scalable and ef cient test automation. This thesis introduces a novel test framework to facilitate functional evaluation of IoT- based services based on MBT methodologies. The concept separates the service logic from connected sensor and actuator nodes in a sandbox environment. Furthermore, a new IoT service behaviour model is designed for representing relevant characteristics of IoT-based services and ensuring the automated emulation of sensor nodes. The IoT-behaviour model proves to be automatically transformable into executable Test Cases (TCs). As a proof of concept, the automated test approach is prototypically implemented as a novel test tool. The execution of the TCs reveals, that crucial failures, such as unexpected messages, data types, or data values, can be detected during test execution. Deriving tests from a test model typically result in huge number of TCs, which cannot be executed within a reasonable time and with limited resources. To enhance the diversity of executed TCs, similarity investigation algorithms are proposed and validated. The results show that the proposed Diversity-based Steady State Genetic algorithm can outperform existing solutions up to 11.6 % with less computation time. With regard to verifying the failure detection rate, experiments show that the proposed Group Greedy algorithm can enhance the rate up to 29 %

Automated Testing of Context-Aware Applications

he development of context-aware applications is a difficult and error-prone task. The dynamics of the environmental context combined with the complexity of the applications poses a vast number of possibilities for mistakes during the creation of new applications. Therefore it is important to test applications before they are deployed in a life system. For this reason, this paper proposes a testing tool, which will allow for automatic generation of various test cases from application description documents. Semantic annotations are used to create specific test data for context-aware applications. A test case reduction methodology based on test case diversity investigations ensures scalability of the proposed automated testing approach

Automated Testing of Context-Aware Applications

he development of context-aware applications is a difficult and error-prone task. The dynamics of the environmental context combined with the complexity of the applications poses a vast number of possibilities for mistakes during the creation of new applications. Therefore it is important to test applications before they are deployed in a life system. For this reason, this paper proposes a testing tool, which will allow for automatic generation of various test cases from application description documents. Semantic annotations are used to create specific test data for context-aware applications. A test case reduction methodology based on test case diversity investigations ensures scalability of the proposed automated testing approach

Performance simulation of a context provisioning middleware based on empirical measurements

© 2012 Elsevier B.V. The evaluation of context middleware systems is a challenging endeavour. On the one hand, testbed investigations suffer from an unrealistic environment in terms of number of users, high implementation effort for changes and questionable portability of results. On the other hand simulation of middleware systems is complex due to the high abstraction of implementation. This article contributes to the understanding of a broker based context provisioning system based on black-box measurements of a testbed which are further utilised to increase the accuracy of a simulation model. Both simulations and measurements help in understanding the complex behaviour of a context provisioning middleware and enable the evaluation of complex distributed systems. The presented investigations identify significant parameters and corresponding models for the response delay of the key components of a context provisioning middleware and discuss their integration into an overall simulation model