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

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

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

Assessment of the Digital Filter Approach for Generating Large-eddy Simulation Inlet Conditions

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

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

Novel Implementation and Assessment of a Digital Filter Based Approach for the Generation of Large Eddy Simulation Inlet Conditions

A novel implementation of a digital filter based inlet condition generator for Large Eddy Simulation (LES) is presented. The effect of using spatially varying turbulence scales as inputs is investigated; it is found that this has impact on both accuracy and affordability, and has prompted the algorithm implementation changes described in the paper. LES of a channel flow with a periodically repeating constriction was used as a test case. The accuracy of the present simulation using a streamwise periodic boundary condition (PBC) was first established by comparison with a previously published highly resolved LES study. Post-processed statistics from the PBC simulation were then input into a Digital Filter Generator (DFG) algorithm. Three time series were created using the DFG for subsequent use as LES inlet conditions. In the first, as well as inputting the spatially varying first and second moments of the velocity field over the inlet plane from the PBC simulation, the turbulence scales input into the DFG were chosen to be spatially uniform with values specified by an area weighted average across the channel inlet height. In the second and third time-series, the turbulence scales were allowed to change in the wall normal direction, their variation again being deduced from the PBC simulation. These various time series were then used as inlet boundary conditions for LES prediction of the same flow case. Analysis of the results and comparison to the PBC predictions showed that the use of spatially varying turbulence scales increased the accuracy of the simulation in some important areas. However, the cost of generating unsteady inlet conditions using the DFG approach increased significantly with the use of spatially varying turbulence scales. Consequently, a new technique applied as part of the DFG approach is described (used as an 'on the fly' method), which significantly reduces the cost of generating LES inlet conditions, even when spatially non-uniform turbulent scales are use