Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures
Abstract
:1. Introduction
- A common standardized model is used to describe cloud and testbed infrastructures. The extensibility of this model is built into it from the start in the form of additional ontologies that describe new types of resources. The machinery to deal with extensions is built into standard semantic web toolkits, leaving the designers free to think about the information model while affixing the data model.
- Different resources and descriptions easily can be related and connected semantically. Semantic web mechanisms intuitively represent computer network graph structures. Network topologies are embedded into the RDF graph using graph homeomorphisms and then are annotated with additional information, addressing structural and semantic constraints in a single structure.
- Model errors can be detected early, before testbed resources are provisioned, by using many standard inference tools.
- Rules can in particular be used to complement queries. Rules for harmonizing relationships should to be defined and applied on the federation level. This is where specialties and commonalities of the involved testbeds are known and this approach lifts the burden from users to formulate complex queries.
- The annotation process, i.e., the conversion from XML-based RSpecs to RDF-based graphs, is automatic and configurable to take testbed specific extensions and federation-wide agreements into account.
- Using standard Semantic Web tools, complex queries can be formulated to discover resources. A common way for testbeds to operate is by ingesting JSON/XML or other encoding of the user request or resource advertisement and then converting it into a non-portable native form on which queries and embeddings are performed. Semantic web tools allow us to store testbed-state information natively in RDF and to operate on that information using a multitude of native inference and query tools, thus simplifying and abstracting many parts of testbed operations.
- Once cloud resources are described semantically, they can be interlinked to other Linked Open Data (LOD) [7] cloud data sets. These linkages provide additional information about resource availability or constraints and help to link resources, e.g., to policies governing their allocation.
- Semantic resource descriptions support convergence from multiple syntactic-schema based representations of testbed resources to a single semantically enriched representation that combines information from multiple sources. Such sources include various RSpecs describing testbed resources, out-of-band knowledge that may be encoded in resource names or contained in human-readable online Web pages, an approach consistent with Ontology-based Data Access (OBDA). Encoding this information in a structured way into a single representation prepares it for direct analysis, without need of an intermediate representation. Answers are derived by matching resources required by the user to those available at one or more different testbeds, federating the testbeds automatically, with minimal human intervention.
2. Related Work
2.1. Semantic Models For Grids, Clouds and IoT
2.2. OMN Background
3. Open-Multinet Ontology Set
3.1. Design
3.1.1. OMN Upper Ontology
- Resource: a stand-alone component of the infrastructure that can be provisioned, i.e., granted to a user such as a network node.
- Service: is a manageable entity that can be controlled and/or used via either APIs or capabilities that it supports, such as a SSH login.
- Component: constitutes a part of a Resource or a Service, such as a port of a network node.
- Attribute: helps to describe the characteristics and properties of a specific Resource, Group, Resource, or Component, such as Quality of Service (QoS).
- Group: is a collection of resources and services, for instance, a testbed or a requested network topology logically grouped together to perform a particular function.
- Dependency: describes a unidirectional relationship between two elements such as Resource, Service, Component, or Group. It may define, for example, an order in which particular resources need to be instantiated: first, a network link, and then, the compute nodes attached to it. This class opens up the possibility of adding more properties to a dependency via annotation.
- Layer: describes a place within a hierarchy to which a specific Group, Resource, Service, or Component can adapt. Infrastructure resources naturally fall into layers, with resources at higher layers requiring presence of resources at lower layers in order to function.
- Environment: the conditions under which a Resource, Group, or Service is operating, as in, e.g., concurrent virtual machines.
- Reservation: a specification of a guarantee for a certain duration. Hence, it is a subclass of the ”Interval” class of the W3C Time ontology [53].
- hasAttribute: the Attribute associated with a Component, Resource, Service, or Group; e.g., CPU speed, or uptime.
- hasComponent: links a Component , Resource, or Service to its subcomponent.
- hasGroup: connects a Group to its subgroup; it is the inverse of isGroupOf.
- hasReservation: relates Group, Resource or Service to its Reservation.
- hasResource: declares that a specific Group has a Resource.
- hasService: declares that a Group, Resource or Service provides a Service.
- withinEnvironment: defines the ”Environment” in which a Group, Resource, Service, or Component operates. An example of environment is the operating system under which a resource works.
3.1.2. OMN Federation
3.1.3. OMN Life Cycle
- the infrastructure provider advertises an Offering describing the available resources;
- the user forms a Request defining the required collection of resources to the infrastructure provider;
- the Confirmation contains an agreement by the provider, termed bound (tied to a specific set of physical resources) or unbound, to provide the requested resources;
- and, finally, a Manifest describes the provisioned resources and their properties.
3.1.4. OMN Monitoring
3.1.5. OMN Resource
3.1.6. OMN Component
3.1.7. OMN Service
3.1.8. OMN Policy
- Authorization policies that specify authorization rights of users within the federation.
- Event-condition-action policies that enforce control and management actions upon certain events within the managed environment.
- Role-based-access control policies that assign users to roles, with different permissions/usage priorities on resources.
- Mission policies that define inter-platform obligations in a federation.
3.1.9. OMN Domain Specific
3.2. Use of Existing Ontologies
3.3. Implementation
4. Information Querying and Validation
4.1. DBcloud Application For Federated Experimental Infrastructures
4.2. Knowledge Extension and Information Querying
4.2.1. Knowledge Extension
4.2.2. Information Querying
4.3. Validation
5. Performance Evaluation
6. Conclusion and Future Work
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
AC4 | Activity Chain 4—Service Openness and Interoperability Issues/Semantic Interoperability |
AM | Aggregate Manager |
API | Application Programming Interface |
DC | Dublin Core |
ETSI | European Telecommunications Standards Institute |
FCFA | Federated Cloud Framework Architecture |
Fed4FIRE | Federation for FIRE |
FI | Future Internet |
FIRE | Future Internet Research and Experimentation |
GENI | Global Environment for Network Innovations |
GLUE | Grid Laboratory for a Uniform Environment |
GR | Good Relations |
IaaS | Infrastructure as a Service |
ICT | Information and Communication Technology |
IEEE | Institute of Electrical and Electronics Engineers |
IERC | European Research Cluster on the Internet of Things |
IIoT | Industrial Internet of Things |
IMF | Information Modeling Framework |
INDL | Infrastructure and Network Description Language |
IoT | Internet of Things |
JAXB | Java Architecture for XML Binding |
JSON | JavaScript Object Notation |
LDAP | Lightweight Directory Access Protocol |
LOD | Linked Open Data |
M2M | Machine-To-Machine Communication |
MAS | OneM2MWorking Group 5 Management, Abstraction and Semantics |
mOSAIC | Open-Source API and Platform for Multiple Clouds |
NDL-OWL | Network Description Language based on the Web Ontology Language |
NML | Network Mark-Up Language |
NOVI | Networking innovations Over Virtualized Infrastructures |
OGF | Open Grid Forum |
OMN | Open-Multinet |
OOPS | OntOlogy Pitfall Scanner |
OWL-S | Semantic Markup forWeb Services |
P2302 | Standard for Intercloud Interoperability and Federation |
PI4.0 | Plattform Industrie 4.0 |
QoS | Quality of Service |
RDF | Resource Description Framework |
RSpec | Resource Specification |
S-OGSA | Semantic Open Grid Service Architecture |
SFA | Slice-based Federation Architecture |
SPARQL | SPARQL Protocol And RDF Query Language |
SQL | Structured Query Language |
SSH | Secure Shell |
SSN | Semantic Sensor Network |
TOSCA | Topology and Orchestration Specification for Cloud Applications |
TTL | Turtle |
UCI | Unified Cloud Interface |
URL | Uniform Resource Locator |
VANN | Vocabulary for Annotating Vocabulary Descriptions |
VOAF | Vocabulary of a Friend |
VoID | Vocabulary of Interlinked Datasets |
W3C | WorldWide Web Consortium |
WoT | Web of Things |
XML | Extensible Markup Language |
XSD | XML Schema Definition |
YANG | Yet Another Next Generation |
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HW Type | Description |
---|---|
alix3d2 | 500 MHz AMD Geode LX800, 256 MB DDR DRAM, 1 GB flash card storage |
pcgen3 | 2x Hexacore Intel E5645 (2.4 GHz) CPU, 24 GB RAM, 250 GB harddisk |
Median Duration [ms] | Phase |
---|---|
24 | Translation from XML to JAXB (on average) |
20 | Translation from JAXB to RDF (on average) |
583 | Translation of 19.371 XML elements (CloudLab) |
5453 | Listing resources (CloudLab) |
129 | Querying three largest aggregates (Listing 10)) |
168 | Matching resources (Listing 14) |
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Willner, A.; Giatili, M.; Grosso, P.; Papagianni, C.; Morsey, M.; Baldin, I. Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures. Data 2017, 2, 21. https://doi.org/10.3390/data2030021
Willner A, Giatili M, Grosso P, Papagianni C, Morsey M, Baldin I. Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures. Data. 2017; 2(3):21. https://doi.org/10.3390/data2030021
Chicago/Turabian StyleWillner, Alexander, Mary Giatili, Paola Grosso, Chrysa Papagianni, Mohamed Morsey, and Ilya Baldin. 2017. "Using Semantic Web Technologies to Query and Manage Information within Federated Cyber-Infrastructures" Data 2, no. 3: 21. https://doi.org/10.3390/data2030021