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Models for Plug-and-Play IoT Architectures

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Mission-Oriented Sensor Networks and Systems: Art and Science

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 164))

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Abstract

The Internet of Things (IoT) is already counting more than 15 billion devices connected to the web and over the following years, a rapidly increasing number of businesses and individuals are expected to become a part of this industry. In this context, enabling technologies and services are needed in order to accommodate this unprecedented interest. One of the major bottlenecks during the development of IoT products and/or services has been the vast diversity and incompatibility that exists among sensors, communication, and computation/controller modules. The various modules operating on numerous communication buses and protocols requires development of platform-dependent hardware and software drivers as well as vigorous testing from the developer side. This process is nontrivial and time-consuming and redirects the focus of developers from “what” to “how” to develop. In addition, users/developers are discouraged when they are obligated to perform tedious manual configurations before they are ready to use their products. Furthermore, there is a significant heterogeneity in IoT network architectures and existing automatic service discovery and configuration protocols. The majority of these protocols have been developed for conventional computer systems and as a result, it cannot be used by resource-constrained IoT devices. For the above reasons, various models of the well-known concept in mainstream systems of Plug-and-Play (PnP), are being introduced to the embedded systems world as well, to tackle the above issues. In the following chapter, an overview of what a Plug-and-Play architecture consists as well as a survey of the state of the art is presented.

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Correspondence to Prashanth Reddy Marpu .

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Tsoupos, A., Jha, M., Marpu, P.R. (2019). Models for Plug-and-Play IoT Architectures. In: Ammari, H. (eds) Mission-Oriented Sensor Networks and Systems: Art and Science. Studies in Systems, Decision and Control, vol 164. Springer, Cham. https://doi.org/10.1007/978-3-319-92384-0_5

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