Internet of Things (IoT) consists of tiny, battery-powered computing devices that are connected through a wireless network. Such networks are relatively cheap and easy to deploy and are therefore increasingly used for various monitoring and control applications.
Abstract: In this thesis we study the architecture and design process of compute and data-transport systems in large-scale distributed radio telescopes. The goal of such systems is to facilitate the maximum viable amount of scientific discovery for the investment made. To aid our discussions, we first introduce a model to more formally express value and cost of compute systems. This allows more granular evaluation of various systems, based not just on their cost, but on their value potential as well. We argue that, since modern radio telescopes are generally capable of producing overwhelming volumes of data, the data-transport system in such an instrument should be architected and designed together with the compute infrastructure. Examples both in the current LOFAR telescope, as well as in the Square Kilometre Array still under development, show that this co-design of data-transport and compute systems has significant value benefits. When these systems are considered together, interesting optimisations on the boundary of the two may be considered. We show two such optimisations that focus on controlling data-flows and reducing energy consumption of such data-flows respectively. Finally we consider the future. Over the last couple of decades compute capacity has continued to increase both predictably and dramatically. Current manufacturing technologies are approaching physical limits, which make this trend unsustainable, at least for conventional technologies. We inventory possible alternative technologies and how these may be applied in support of a radio telescope.