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J. R. Prasad et al.
Due to the above-mentioned techniques, experimentation becomes easy using the
Application Programming Interface (API) and set of tools. The major advantage of
using such techniques in the IoT environment is that we can have the cross-domain
communication and various kinds of innovative solutions for providing the scalability
and heterogeneity. Still, there is a need for solutions that can be used for the existing
IoT environment. One solution proposed is Experimentation as a Service (EaaS).
It consists of EaaS meta platform, Testbed APIs, different representation formats
for RDF (e.g. JSON-LD, RDF/XML, turtle, etc.) for common ontology topologies,
IoT registry, Experiment Result Storage (ERS), Experiment Management Console
(EMC), Experiment Registry Module (ERM), Experiment Execution Engine (EEE),
Semantic Annotator, Testbed Provider Service (TPS), Testbed and Resource Registration (TRR) module, Policy Enforcement Point (PEP), triplestore Database, Data
Endpoints, Resource Broker(RB), Resource Manager (RM), SPARQL Endpoints,
TDB query engine, web-based API, Results are captured in any data representation formats like JSON, CSV, XML, etc., Testbed Provider Interface(TPI), Testbed
Provider Services (TPS). To provide the experimenter with Data Analysis using
Knowledge Acquisition Toolkit (KAT) based Data Analytics web services (DAaaS).
The detailed architecture and results can be found in the paper [29].
The solution which is provided in this chapter is not bounded to any ontology
technique provided by semantic technology. The best part of these techniques is that
the solutions are extendable and reusable. In the future, we can create some service
for the cloud which will make the use of semantic technologies and will improve the
performance using the SDN and NFV together.
7.2 SDN Based Solution
In [22], the author has tried to provide a solution specific to SDN. He performed
some experiments and showed the applicability of SDN for Resource management.
To implement this solution usage of OWL, RDF, SPARQL was been done. The
Software of Protégé was used to replicate the results. In future various testbeds can
be created for providing the semantic IoT interoperability using SDN (Fig. 4).
We have proposed the SDN based IoT interoperability solution as shown in the
figure. The mentioned solution will be applicable for all kinds of IoT devices like
WSN, WiFi, and cellular networks.
Protégé implementation of Semantic SDN has been demonstrated, so this kind
of implementation can be replicated for Semantic IoT interoperability in the future
using some emulation, simulation, or testbed (Fig. 5).
J. R. Prasad et al.
Due to the above-mentioned techniques, experimentation becomes easy using the
Application Programming Interface (API) and set of tools. The major advantage of
using such techniques in the IoT environment is that we can have the cross-domain
communication and various kinds of innovative solutions for providing the scalability
and heterogeneity. Still, there is a need for solutions that can be used for the existing
IoT environment. One solution proposed is Experimentation as a Service (EaaS).
It consists of EaaS meta platform, Testbed APIs, different representation formats
for RDF (e.g. JSON-LD, RDF/XML, turtle, etc.) for common ontology topologies,
IoT registry, Experiment Result Storage (ERS), Experiment Management Console
(EMC), Experiment Registry Module (ERM), Experiment Execution Engine (EEE),
Semantic Annotator, Testbed Provider Service (TPS), Testbed and Resource Registration (TRR) module, Policy Enforcement Point (PEP), triplestore Database, Data
Endpoints, Resource Broker(RB), Resource Manager (RM), SPARQL Endpoints,
TDB query engine, web-based API, Results are captured in any data representation formats like JSON, CSV, XML, etc., Testbed Provider Interface(TPI), Testbed
Provider Services (TPS). To provide the experimenter with Data Analysis using
Knowledge Acquisition Toolkit (KAT) based Data Analytics web services (DAaaS).
The detailed architecture and results can be found in the paper [29].
The solution which is provided in this chapter is not bounded to any ontology
technique provided by semantic technology. The best part of these techniques is that
the solutions are extendable and reusable. In the future, we can create some service
for the cloud which will make the use of semantic technologies and will improve the
performance using the SDN and NFV together.
7.2 SDN Based Solution
In [22], the author has tried to provide a solution specific to SDN. He performed
some experiments and showed the applicability of SDN for Resource management.
To implement this solution usage of OWL, RDF, SPARQL was been done. The
Software of Protégé was used to replicate the results. In future various testbeds can
be created for providing the semantic IoT interoperability using SDN (Fig. 4).
We have proposed the SDN based IoT interoperability solution as shown in the
figure. The mentioned solution will be applicable for all kinds of IoT devices like
WSN, WiFi, and cellular networks.
Protégé implementation of Semantic SDN has been demonstrated, so this kind
of implementation can be replicated for Semantic IoT interoperability in the future
using some emulation, simulation, or testbed (Fig. 5).