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
+~\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 in
-healthcare\cite{riazul_islam_internet_2015}. For example, for a few euros a
+\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
+~\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 tasks can be modelled using
+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
+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 tasks and let
-them interact. A lot of the actual tasks could be performed by small
+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.
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. A
-lot of the 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
-smaller devices like \acrshort{ARM} devices\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.
+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
+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
+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}
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 on in this dissertation.
+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
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{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
+\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
\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}.
+~\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
+~\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
+~\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
repositories / msc-thesis1617.git / blobdiff