Norm-based and Commitment-driven Agentification of the Internet of Things

There are no doubts that the Internet-of-Things (IoT) has conquered the ICT industry to the extent that many governments and organizations are already rolling out many anywhere,anytime online services that IoT sustains. However, like any emerging and disruptive technology, multiple obstacles are slowing down IoT practical adoption including the passive nature and privacy invasion of things. This paper examines how to empower things with necessary capabilities that would make them proactive and responsive. This means things can, for instance reach out to collaborative peers, (un)form dynamic communities when necessary, avoid malicious peers, and be “questioned” for their actions. To achieve such empowerment, this paper presents an approach for agentifying things using norms along with commitments that operationalize these norms. Both norms and commitments are specialized into social (i.e., application independent) and business (i.e., application dependent), respectively. Being proactive, things could violate commitments at run-time, which needs to be detected through monitoring. In this paper, thing agentification is illustrated with a case study about missing children and demonstrated with a testbed that uses di_erent IoT-related technologies such as Eclipse Mosquitto broker and Message Queuing Telemetry Transport protocol. Some experiments conducted upon this testbed are also discussed

Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography

High angular resolution diffusion imaging (HARDI)-based tractography has been increasingly used in longitudinal studies on white matter macro- and micro-structural changes in the language network during language acquisition and in language impairments. However, test-retest reliability measurements are essential to ascertain that the longitudinal variations observed are not related to data processing. The aims of this study were to determine the reproducibility of the reconstruction of major white matter fiber bundles of the language network using anatomically constrained probabilistic tractography with constrained spherical deconvolution based on HARDI data, as well as to assess the test-retest reliability of diffusion measures extracted along them. Eighteen right-handed participants were scanned twice, one week apart. The arcuate, inferior longitudinal, inferior fronto-occipital, and uncinate fasciculi were reconstructed in the left and right hemispheres and the following diffusion measures were extracted along each tract: fractional anisotropy, mean, axial, and radial diffusivity, number of fiber orientations, mean length of streamlines, and volume. All fiber bundles showed good morphological overlap between the two scanning timepoints and the test-retest reliability of all diffusion measures in most fiber bundles was good to excellent. We thus propose a fairly simple, but robust, HARDI-based tractography pipeline reliable for the longitudinal study of white matter language fiber bundles, which increases its potential applicability to research on the neurobiological mechanisms supporting language

Towards a Quality-of-Thing based Approach for Assigning Things to Federations

In the context of an Internet-of-Things (IoT) ecosystem, this paper discusses 2 necessary stages for managing federations of things. The first stage defines things in terms of duties and non-functional properties that define the quality of these duties. And, the second stage uses these properties to assign appropriate things to future federations. Specialized into adhoc and planned, federations are expected to satisfy needs and requirements of real-life situations like traffic control that arise at run-time. A set of experiments using a mix of real and simulated datasets, demonstrate the technical doability of thing assignment to federations and are presented in the paper, as well

Effect of Compositional Grading On reservoir Performance

In reservoirs with thickness exceeding fifty meters, compositional guiding has been found to cause significant variation in performance. Main fluid properties, governing the magnitude of reservoir performance, such as density; formation volume factor and fluid viscosity experience variation due to varying fluid composition along the hydrocarbon column. These variations cause erroneous estimation of stock-tank oil in place and may infer reservoir engineers to consider inappropriate secondary oil recovery methods, for example. In the presence of gravity segregation within the oil column, heavy ends will form a heavy oil blanket in the lower part of the reservoir. Such a scenario may result in poor displacement and an earlier breakthrough when water drive is the dominant fluid flow mechanism. In this paper reservoir performance due to varying reservoir fluid composition has been examined using  reservoir simulation analysis and recommendations for better characterization of reservoir fluid sampling are outlined

A linear program for optimal configurable business processes deployment into cloud federation

International audienceA configurable process model is a generic model from which an enterprise can derive and execute process variants that meet its specific needs and contexts. With the advent of cloud computing and its economic pay-per-use model, enterprises are increasingly outsourcing partially or totally their process variants to cloud providers, and recently to cloud federations. A main challenge in this regard is to allocate optimally cloud resources to the process variants' activities. More specifically, an enterprise may be interested in outsourcing only those that result in an optimal deployment. Due to the diversity of the enterprise QoS requirements, the heterogeneity of resources offered by the cloud federation and the large number of possible configurations in a configurable process model, finding the optimal process variant deployment becomes a highly challenging problem. In this paper, we propose a novel approach to solve this problem through a binary/(0-1) linear program with a quadratic objective function under a set of constraints pertinent to both the enterprise and cloud federation requirements. Our prototypical implementation demonstrates the feasibility and the results of our experiments highlight the effectiveness of our proposed solutio

Des objets sans sens : connaissances concrètes et démence sémantique.

International audienc