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9.1 Introduction 321
wants to take part of a system, it will request a repository where an ontology
is stored what format needs to declare the information is able or willing to
provide — shaped as services — (1). The device will get a reply dealing with
the accurate format that is required (2); this format will be defined by the
ontology and will be the one used in the instances of the devices using that
ontology. Afterwards, the services that are provided by the device are sent to
another repository — which can be the same the ontology is stored in or not —
where are kept with the data of the other devices, in a sort of profile of the
services that are available (3). In this way, many different devices can be added
to the system at a fast pace. Interoperability is made easier as well: the data
format provided by ontologies makes services equally available, regardless of
the device they are being provided by.
Another significant enablers for interoperability in the Internet of Things
are discovery and metadata capabilities, and therefore, key enablers for removing
friction in the current IoT value chain.
One of the challenges for the IoT is to develop specifications and open
source reference implementations that allow a quick market development.
Thereby, IoT will be able to take off from its current status of not real business
models or companies exploiting the IoT market.
The added value for the IoT can be defined with the intelligence. For this
purpose, Big Data is being considered as one of the key enablers. Big Data
will provide context-awareness capabilities, but for make feasible the Big
Data over the IoT will require before focus on enable the IoT with semantic
capabilities and context-aware discovery. The main difference between the
classic data mining and the big data is the quantity of data. Therefore, IoT
requires solutions founded in the Big Data principles to provide a suitable
scalability for the data analysis.
Finally, an automated service discovery mechanism is required to reduce
costs and automate the deployment process by removing human involvement
and offline provisioning, i.e., bootstrapping phases.
For that reason, IoT requires a homogenous and suitable mechanism for
the global resource discovery, devices access for the deployed smart objects in
the different scenarios, sensors and devices from the end users (participative
sensing), the integration of legacy and already available sensors in the smart
buildings are required features for a solution based on IoT.
In this chapter, a set of protocols and technology is presented for maximizing
efficiency and sustainability of IoT deployments through a resolution