Policy management and enforcement using OWL and SWRL for the internet of things

© Springer International Publishing AG 2017. As the number of connected devices is exponentially growing, the IoT community is investigating potential ways of overcoming the resulting heterogeneity to enable device compatibility, interoperability and integration. The Semantic Web technologies, frequently used to address these issues, have been employed to develop a number of ontological frameworks, aiming to provide a common vocabulary of terms for the IoT domain. Defined in Web Ontology Language – a language based on the Description Logics, and thus equipped with the ‘off-the-shelf’ support for formal reasoning – these ontologies, however, seem to neglect the built-in automated reasoning capabilities. Accordingly, this paper discusses the possibility of leveraging this idle potential for automated analysis in the context of defining and enforcing policies for the IoT. As a first step towards a proof of concept, the paper focuses on a simple use case and, using the existing IoT-Lite ontology, demonstrates different types of semantic classification to enable policy enforcement. As a result, it becomes possible to detect a critical situation, when a dangerous temperature threshold has been exceeded. With the proposed approach, IoT practitioners are offered an already existing, reliable and optimised policy enforcement mechanism. Moreover, they are also expected to benefit from support for policy governance, separation of concerns, a declarative approach to knowledge engineering, and an extensible architecture

Large-eddy simulation of low-frequency unsteadiness in a turbulent shock-induced separation bubble

The need for better understanding of the low-frequency unsteadiness observed in shock wave/turbulent boundary layer interactions has been driving research in this area for several decades. We present here a large-eddy simulation investigation of the interaction between an impinging oblique shock and a Mach 2.3 turbulent boundary layer. Contrary to past large-eddy simulation investigations on shock/turbulent boundary layer interactions, we have used an inflow technique which does not introduce any energetically significant low frequencies into the domain, hence avoiding possible interference with the shock/boundary layer interaction system. The large-eddy simulation has been run for much longer times than previous computational studies making a Fourier analysis of the low frequency possible. The broadband and energetic low-frequency component found in the interaction is in excellent agreement with the experimental findings. Furthermore, a linear stability analysis of the mean flow was performed and a stationary unstable global mode was found. The long-run large-eddy simulation data were analyzed and a phase change in the wall pressure fluctuations was related to the global-mode structure, leading to a possible driving mechanism for the observed low-frequency motions

An LES Turbulent Inflow Generator using A Recycling and Rescaling Method

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The present paper describes a recycling and rescaling method for generating turbulent inflow conditions for Large Eddy Simulation. The method is first validated by simulating a turbulent boundary layer and a turbulent mixing layer. It is demonstrated that, with input specification of mean velocities and turbulence rms levels (normal stresses) only, it can produce realistic and self-consistent turbulence structures. Comparison of shear stress and integral length scale indicates the success of the method in generating turbulent 1-point and 2-point correlations not specified in the input data. With the turbulent inlet conditions generated by this method, the growth rate of the turbulent boundary/mixing layer is properly predicted. Furthermore, the method can be used for the more complex inlet boundary flow types commonly found in industrial applications, which is demonstrated by generating non-equilibrium turbulent inflow and spanwise inhomogeneous inflow. As a final illustration of the benefits brought by this approach, a droplet-laden mixing layer is simulated. The dispersion of droplets in the near-field immediately downstream of the splitter plate trailing edge where the turbulent mixing layer begins is accurately reproduced due to the realistic turbulent structures captured by the recycling/rescaling method

Advanced service brokerage capabilities as the catalyst for future cloud service ecosystems.

Market analysts have foreseen the emergence of cloud brokers in the mediation of cloud services. But rather than focus on current kinds of intermediary role, it is more constructive to consider the kinds of brokerage capability that could be offered in the future, which go far beyond the integration, aggregation and customization services available today. This paper identifies advanced capabilities for cloud service governance, quality assurance and optimization that will be critical in catalyzing the emergence of cloud service ecosystems, environments in which all parties will find their symbiotic niches. It shows the path whereby a platform provider could evolve to become the hub of a cloud service ecosystem, through gradually taking on more of these advanced brokerage capabilities. The paper provides an overview of work conducted by the EU FP7 Broker@Cloud project towards realizing these advanced brokerage capabilities

Efficient generation of inflow conditions for large-eddy simulation of street-scale flows

Using a numerical weather forecasting code to provide the dynamic largescale inlet boundary conditions for the computation of small-scale urban canopy flows requires a continuous specification of appropriate inlet turbulence. For such computations to be practical, a very efficient method of generating such turbulence is needed. Correlation functions of typical turbulent shear flows have forms not too dissimilar to decaying exponentials. A digital-filter-based generation of turbulent inflow conditions exploiting this fact is presented as a suitable technique for large eddy simulations computation of spatially developing flows. The artificially generated turbulent inflows satisfy the prescribed integral length scales and Reynoldsstress-tensor. The method is much more efficient than, for example, Klein’s (J Comp Phys 186:652–665, 2003) or Kempf et al.’s (Flow Turbulence Combust 74:67–84, 2005) methods because at every time step only one set of two-dimensional (rather than three-dimensional) random data is filtered to generate a set of two-dimensional data with the appropriate spatial correlations. These data are correlated with the data from the previous time step by using an exponential function based on two weight factors. The method is validated by simulating plane channel flows with smooth walls and flows over arrays of staggered cubes (a generic urban-type flow). Mean velocities, the Reynolds-stress-tensor and spectra are all shown to be comparable with those obtained using classical inlet-outlet periodic boundary conditions. Confidence has been gained in using this method to couple weather scale flows and street scale computations

Development of a New Subgrid Scale (SGS) Model Based on the Energy Spectrum

No description supplie

Policy management and enforcement using OWL and SWRL for the internet of things

© Springer International Publishing AG 2017. As the number of connected devices is exponentially growing, the IoT community is investigating potential ways of overcoming the resulting heterogeneity to enable device compatibility, interoperability and integration. The Semantic Web technologies, frequently used to address these issues, have been employed to develop a number of ontological frameworks, aiming to provide a common vocabulary of terms for the IoT domain. Defined in Web Ontology Language – a language based on the Description Logics, and thus equipped with the ‘off-the-shelf’ support for formal reasoning – these ontologies, however, seem to neglect the built-in automated reasoning capabilities. Accordingly, this paper discusses the possibility of leveraging this idle potential for automated analysis in the context of defining and enforcing policies for the IoT. As a first step towards a proof of concept, the paper focuses on a simple use case and, using the existing IoT-Lite ontology, demonstrates different types of semantic classification to enable policy enforcement. As a result, it becomes possible to detect a critical situation, when a dangerous temperature threshold has been exceeded. With the proposed approach, IoT practitioners are offered an already existing, reliable and optimised policy enforcement mechanism. Moreover, they are also expected to benefit from support for policy governance, separation of concerns, a declarative approach to knowledge engineering, and an extensible architecture

Policy management and enforcement using OWL and SWRL for the internet of things

© Springer International Publishing AG 2017. As the number of connected devices is exponentially growing, the IoT community is investigating potential ways of overcoming the resulting heterogeneity to enable device compatibility, interoperability and integration. The Semantic Web technologies, frequently used to address these issues, have been employed to develop a number of ontological frameworks, aiming to provide a common vocabulary of terms for the IoT domain. Defined in Web Ontology Language – a language based on the Description Logics, and thus equipped with the ‘off-the-shelf’ support for formal reasoning – these ontologies, however, seem to neglect the built-in automated reasoning capabilities. Accordingly, this paper discusses the possibility of leveraging this idle potential for automated analysis in the context of defining and enforcing policies for the IoT. As a first step towards a proof of concept, the paper focuses on a simple use case and, using the existing IoT-Lite ontology, demonstrates different types of semantic classification to enable policy enforcement. As a result, it becomes possible to detect a critical situation, when a dangerous temperature threshold has been exceeded. With the proposed approach, IoT practitioners are offered an already existing, reliable and optimised policy enforcement mechanism. Moreover, they are also expected to benefit from support for policy governance, separation of concerns, a declarative approach to knowledge engineering, and an extensible architecture

Policy management and enforcement using OWL and SWRL for the internet of things

© Springer International Publishing AG 2017. As the number of connected devices is exponentially growing, the IoT community is investigating potential ways of overcoming the resulting heterogeneity to enable device compatibility, interoperability and integration. The Semantic Web technologies, frequently used to address these issues, have been employed to develop a number of ontological frameworks, aiming to provide a common vocabulary of terms for the IoT domain. Defined in Web Ontology Language – a language based on the Description Logics, and thus equipped with the ‘off-the-shelf’ support for formal reasoning – these ontologies, however, seem to neglect the built-in automated reasoning capabilities. Accordingly, this paper discusses the possibility of leveraging this idle potential for automated analysis in the context of defining and enforcing policies for the IoT. As a first step towards a proof of concept, the paper focuses on a simple use case and, using the existing IoT-Lite ontology, demonstrates different types of semantic classification to enable policy enforcement. As a result, it becomes possible to detect a critical situation, when a dangerous temperature threshold has been exceeded. With the proposed approach, IoT practitioners are offered an already existing, reliable and optimised policy enforcement mechanism. Moreover, they are also expected to benefit from support for policy governance, separation of concerns, a declarative approach to knowledge engineering, and an extensible architecture