Other/Miscellaneous – Internet of Things Laboratory

@phdthesis{phdthesis:davoli,

title = {Architecture and Technologies for the Internet of Things},

author = {Luca Davoli},

url = {http://hdl.handle.net/1889/3423},

year  = {2017},

date = {2017-03-14},

school = {Department of Information Engineering, University of Parma},

abstract = {The Internet of Things (IoT) paradigm can been defined as a "network of networks" of devices interconnected in an Internet-like structure, generally denoted as Smart Objects, cooperating to collect data and provide services to users. SOs are extremely heterogeneous and differ for connectivity interfaces, battery, processing and memory capabilities, as well as dimensions, costs, and hardware features. They are typically equipped with a microcontroller, a radio interface for communication, sensors and/or actuators and, being typically battery-powered, there is a quest for energy-efficient technologies, communication/networking protocols and mechanisms. The IP protocol, and in particular IPv6, have been widely envisaged as the true IoT enablers, as they allow to bring the full interoperability among heterogeneous objects. At the application layer, CoAP protocol has been designed to bring the REST paradigm, which was originally conceived for applications based on HTTP, to the IoT and is expected to become the standard communication protocol for constrained applications. Research has now gone beyond the hardware and protocols barriers, providing several solutions for building IoT networks and opening a new challenge: the definition of effective paradigms and mechanisms aimed at integrating the IoT in common people's life. This challenge is very complex from a communication perspective, as it involves all layers of the protocol stack. A few examples of aspects to deal with are: the choice of SOs connectivity; the mechanisms for automatic endpoints discovery; the resources representation; final users application design; and the models of interaction between SOs and people. Related to the SOs connectivity, by definition, IoT concept encourage the reuse of existing communication paradigms, adding adaptation mechanisms, when needed. An example is represented by the adoption of the PLC as wired access technology. Another interesting technology for IoT is SDN, that can help in configuring and managing the backhaul network connecting different access domains. From the data point of view, an important aspect is the possibility to manage all sensed and gathered data in a smart and practical way. In this context, a possible solution is given by Big Data approaches, developed in the last few years and become popular due to the evolution of online and social/crowd services, which are able to address the need to process extremely large amounts of heterogeneous data for various purposes. However, these techniques typically have an intrinsic inertia (as they are based on batch processing) and focus on the data itself, rather than providing real-time processing and dispatching. For this reason, Big Data approaches might not be the right solution to manage the dynamicity of IoT scenarios with real-time processing. In order to better fit these requirements, it is needed to shift the Big Data paradigm to a new paradigm, denoted as "Big Stream", more oriented to the massive rate of data proper of IoT scenarios.},

keywords = {},

pubstate = {published},

tppubtype = {phdthesis}

}

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The Internet of Things (IoT) paradigm can been defined as a "network of networks" of devices interconnected in an Internet-like structure, generally denoted as Smart Objects, cooperating to collect data and provide services to users. SOs are extremely heterogeneous and differ for connectivity interfaces, battery, processing and memory capabilities, as well as dimensions, costs, and hardware features. They are typically equipped with a microcontroller, a radio interface for communication, sensors and/or actuators and, being typically battery-powered, there is a quest for energy-efficient technologies, communication/networking protocols and mechanisms. The IP protocol, and in particular IPv6, have been widely envisaged as the true IoT enablers, as they allow to bring the full interoperability among heterogeneous objects. At the application layer, CoAP protocol has been designed to bring the REST paradigm, which was originally conceived for applications based on HTTP, to the IoT and is expected to become the standard communication protocol for constrained applications. Research has now gone beyond the hardware and protocols barriers, providing several solutions for building IoT networks and opening a new challenge: the definition of effective paradigms and mechanisms aimed at integrating the IoT in common people's life. This challenge is very complex from a communication perspective, as it involves all layers of the protocol stack. A few examples of aspects to deal with are: the choice of SOs connectivity; the mechanisms for automatic endpoints discovery; the resources representation; final users application design; and the models of interaction between SOs and people. Related to the SOs connectivity, by definition, IoT concept encourage the reuse of existing communication paradigms, adding adaptation mechanisms, when needed. An example is represented by the adoption of the PLC as wired access technology. Another interesting technology for IoT is SDN, that can help in configuring and managing the backhaul network connecting different access domains. From the data point of view, an important aspect is the possibility to manage all sensed and gathered data in a smart and practical way. In this context, a possible solution is given by Big Data approaches, developed in the last few years and become popular due to the evolution of online and social/crowd services, which are able to address the need to process extremely large amounts of heterogeneous data for various purposes. However, these techniques typically have an intrinsic inertia (as they are based on batch processing) and focus on the data itself, rather than providing real-time processing and dispatching. For this reason, Big Data approaches might not be the right solution to manage the dynamicity of IoT scenarios with real-time processing. In order to better fit these requirements, it is needed to shift the Big Data paradigm to a new paradigm, denoted as "Big Stream", more oriented to the massive rate of data proper of IoT scenarios.

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