\section{Introduction}
\Gls{IoT} technology is emerging very quickly. It offers myriads of solutions
and transforms the way we interact with technology.

Initially the term was coined to describe \gls{RFID} devices and the
communication between them.  However, currently the term \gls{IoT} encompasses
all small devices that communicate with each other and the world. These devices
are often equipped with sensors, \gls{GNSS}\footnote{e.g.\ the American
\gls{GPS} or the Russian \gls{GLONASS}} and actuators%
~\cite{da_xu_internet_2014}. With these new technologies information
can be tracked very accurately using very little power and bandwidth. Moreover,
\gls{IoT} technology is coming into people's homes, clothes and
healthcare~\cite{riazul_islam_internet_2015}. For example, for a few euros a
consumer ready fitness tracker watch can be bought that tracks heartbeat and
respiration levels.

The \gls{TOP} paradigm and the corresponding \gls{iTasks} implementation offer
a high abstraction level for real life workflow tasks%
~\cite{plasmeijer_itasks:_2007}. These workflow tasks can be described through
an \gls{EDSL} and modeled as \glspl{Task}. The system will generate multi-user
web app from the specification. This web service can be accessed through a
browser and is used to complete these \glspl{Task}. Familiar workflow patterns
like sequence, parallel and conditional \glspl{Task} can be modelled using
combinators.

\gls{iTasks} has been proven to be useful in many fields of operation such as
incident management~~\cite{lijnse_top_2013}. Interfaces are automatically
generated for the types of data which makes rapid development possible.
\Glspl{Task} in the \gls{iTasks} system are modelled after real life workflow
tasks but the modelling is applied on a very high level. Therefore it is
difficult to connect \gls{iTasks}-\glspl{Task} to real world \glspl{Task} and
allow them to interact. A lot of the actual tasks could be performed by small
\gls{IoT} devices. Nevertheless, adding such devices to the current system is
difficult to say the least as it was not designed to cope with these devices. 

In the current system such adapters connecting devices to \gls{iTasks} --- in
principle --- can be written as \glspl{SDS}\footnote{Similar as to resources
such as time are available in the current \gls{iTasks} implementation}.
However, this
requires a very specific adapter to be written for every device and function.
This forces a fixed logic in the device that is set at compile time. Many
small \gls{IoT} devices have limited processing power but can still contain
decision making. Oortgiese et al.\ lifted \gls{iTasks} from a single server
model to a distributed server architecture that is also runnable on small
devices such as those powered by \acrshort{ARM}~~\cite{%
oortgiese_distributed_2017}. However, this is limited to fairly high
performance devices that are equipped with high speed communication channels.
Devices in \gls{IoT} often have only \gls{LTN} communication with low bandwidth
and a very limited amount of processing power and are therefore not suitable to
run an entire \gls{iTasks} core.

\section{Problem statement}
The updates to the \gls{mTask}-system~\cite{koopman_type-safe_nodate} will
bridge this gap by introducing a new communication protocol, device application
and \glspl{Task} synchronizing the formers. The system can run on devices as
small as \gls{Arduino} microcontrollers~\cite{noauthor_arduino_nodate} and
operates via the same paradigms and patterns as regular \glspl{Task} in the
\gls{TOP} paradigm.  Devices in the \gls{mTask}-system can run small imperative
programs written in an \gls{EDSL} and have access to \glspl{SDS}. \Glspl{Task}
are sent to the device at runtime, avoiding recompilation and thus write cycles
on the program memory.

\section{Document structure}
The structure of this thesis is as follows.

Chapter~\ref{chp:introduction} contains the problem statement, motivation,
related work and the structure of the document.
Chapter~\ref{chp:top} introduces the reader to the basics of \gls{TOP} and
\gls{iTasks}.
Chapter~\ref{chp:dsl} discusses the pros and cons of different embedding
methods to create \gls{EDSL}.
Chapter~\ref{chp:mtask} shows the existing \gls{mTask}-\gls{EDSL} on which is
extended upon in this dissertation.
Chapter~\ref{chp:arch} shows the architecture used for \gls{IoT}-devices that
are a part of the new \gls{mTask}-system.
Chapter~\ref{chp:mtaskcont} shows the extension added to the
\gls{mTask}-\gls{EDSL} that were needed to make the system function.
Chapter~\ref{chp:itasksint} shows the integration with \gls{iTasks} that was
built to realise the system.
Chapter~\ref{chp:conclusion} concludes by answering the research questions
and discusses future research.
Appendix~\ref{app:communication-protocol} shows the concrete protocol used for
communicating between the server and client.
Appendix~\ref{app:device-interface} shows the concrete interface for the
devices.

Text written using the \CI{Teletype} font indicates code and is often
referring to a listing. \emph{Emphasized} text is used for proper nouns and
words that have a unexpected meaning.

\section{Related work}
Several types of similar research have been conducted concerning these matters.
Microcontrollers such as the \gls{Arduino} can be remotely controlled by the
\gls{Firmata}-protocol\footnote{``firmata/protocol: Documentation of the
Firmata protocol.'' (\url{https://github.com/firmata/protocol}). [Accessed:
23-May-2017].}. This protocol
is designed to expose the peripherals such as sensors to the server. This
allows very fine grained control but with the cost of excessive communication
overhead since no code is executed on the device, only the peripherals are
queried. A \gls{Haskell} implementation of the protocol has been created%
\footnote{``hArduino by LeventErkok.'' (\url{%
https://leventerkok.github.io/hArduino}). [Accessed: 23-May-2017].}.

\Gls{Clean} has a history of interpretation and there is a lot of research
happening on the intermediate language \gls{SAPL}. \Gls{SAPL} is a purely
functional intermediate language that has interpreters written in
\gls{C++}~\cite{jansen_efficient_2007} and \gls{Javascript}%
~\cite{domoszlai_implementing_2011} and \gls{Clean} and \gls{Haskell} compiler
backends~\cite{domoszlai_compiling_2012}. However, interpreting the resulting
code is still heap-heavy and therefore not directly suitable for devices with as
little as $2K$ of RAM such as the \gls{Arduino} \emph{UNO}. It might be
possible to compile the \gls{SAPL} code into efficient machine language or
\gls{C} but then the system would lose its dynamic properties since the
microcontroller then would have to be reprogrammed every time a new \gls{Task}
is sent to the device.

\Glspl{EDSL} have often been used to generate \gls{C} code for microcontroller
environments. For starters, this work is built upon the \gls{mTask}-\gls{EDSL}
that generates \gls{C} code to run a \gls{TOP}-like system on microcontrollers%
~\cite{plasmeijer_shallow_2016}~\cite{koopman_type-safe_nodate}.
Again, this requires a reprogramming cycle every time the
\gls{Task}-specification is changed.

Another \gls{EDSL} designed to generate low-level high-assurance programs is
called \gls{Ivory} and uses \gls{Haskell} as a host language%
~\cite{elliott_guilt_2015}. The language uses the \gls{Haskell} type-system to
make unsafe languages type safe. For example, \gls{Ivory} has been used in the
automotive industry to program parts of an autopilot%
~\cite{pike_programming_2014}~\cite{hickey_building_2014}. \Gls{Ivory}'s syntax
is deeply embedded but the type system is shallowly embedded. This requires
several \gls{Haskell} extensions that offer dependent type constructions. The
process of compiling an \gls{Ivory} program happens in stages. The embedded
code is transformed into an \gls{AST} that is sent to a backend. The
\gls{mTask} \gls{EDSL} transforms the embedded code during compile-time
directly into the backend which is often a state transformer that will execute
on runtime.
