\section{Related work}
The novelties of the \gls{MTASK} system can be compared to existing systems in several categories.
-It is a interpreted (\cref{sec:related_int}) \gls{TOP} (\cref{sec:related_top}) \gls{DSL} (\cref{sec:related_dsl}) that may seem similar at first glance to \gls{FRP} (\cref{sec:related_frp}), it is implemented in a functional language (\cref{sec:related_fp}) and due to the execution semantics, multitasking is automatically supported (\cref{sec:related_multi}).
+It is an interpreted (\cref{sec:related_int}) \gls{TOP} (\cref{sec:related_top}) \gls{DSL} (\cref{sec:related_dsl}) that may seem similar at first glance to \gls{FRP} (\cref{sec:related_frp}), it is implemented in a functional language (\cref{sec:related_fp}) and due to the execution semantics, multitasking is automatically supported (\cref{sec:related_multi}).
\Cref{sec_t4t:TiredvsTierless} contains an elaborate related work section regarding tierless systems in general.
\subsection{Interpretation}\label{sec:related_int}
\subsection{Functional programming}\label{sec:related_fp}
\Citet{haenisch_case_2016} showed that there are major benefits to using functional languages on edge devices.
They show that using function languages increased the security and maintainability of the applications.
-Traditional implementations of general purpose functional languages have high memory requirements rendering them unusable for resource-constrained computers.
+Traditional implementations of general purpose functional languages have high memory requirements rendering them unuseable for resource-constrained computers.
There have been many efforts to create a general purpose functional language that does fit in small memory environments, albeit with some concessions.
For example, there has been a history of creating tiny Scheme implementations for specific microcontrollers.
It started with BIT \citep{dube_bit:_2000} that only required \qty{64}{\kibi\byte} of memory, followed by {PICBIT} \citep{feeley_picbit:_2003} and {PICOBIT} \citep{st-amour_picobit:_2009} that lowered the memory requirements even more.
Applications for tiny computers are often parallel in nature.
Tasks like reading sensors, watching input devices, operating actuators and maintaining communication are often loosely dependent on each other and are preferably executed in parallel.
Microcontrollers often do not benefit from an \gls{OS} due to memory and processing constraints.
-Therefore, writing multitasking applications in an imperative language is possible but the tasks have to be interleaved by hand \citep{feijs_multi-tasking_2013}.
+Therefore, writing multitasking applications in an imperative language is possible, but the tasks have to be interleaved by hand \citep{feijs_multi-tasking_2013}.
This results in hard to maintain, error-prone and unscalable spaghetti code.
There are many solutions to overcome this problem in imperative languages.
\Gls{TOP} as a paradigm has proven to be effective for implementing distributed, multi-user applications in many domains.
Examples are conference management \citep{plasmeijer_conference_2006}, coastal protection \citep{lijnse_capturing_2011}, incident coordination \citep{lijnse_incidone:_2012}, crisis management \citep{jansen_towards_2010} and telemedicine \citep{van_der_heijden_managing_2011}.
In general, \gls{TOP} results in a higher maintainability, a high separation of concerns, and more effective handling of interruptions of workflow.
-\Gls{IOT} applications contain a distributed and multi-user component, but the software on the device is mostly follows multiple loosely dependent workflows.
+\Gls{IOT} applications contain a distributed and multi-user component, but the software on the device mostly follows multiple loosely dependent workflows.
The only other \gls{TOP} language for embedded systems is $\mu$Tasks \citep{piers_task-oriented_2016}.
It is a non-distributed \gls{TOP} \gls{EDSL} hosted in \gls{HASKELL} designed for embedded systems such as payment terminals.
They show that applications tend to be able to cope well with interruptions and are more maintainable.
After a reset, the program state is resumed from a checkpoint that was stored in some non-volatile memory.
This technique is called intermittent computing \citep{hester_batteries_2019}.
Many intermittent computing solutions rely on annotations from the programmer to divide the program into atomic blocks, sometimes called tasks as well.
-These blocks are marked as such, because in the case of an reset of the system, the work must be done again.
+These blocks are marked as such, because in the case of a reset of the system, the work must be done again.
Examples of such blocks are \gls{I2C} transmissions or calculations that rely on recent sensor data.
In \gls{MTASK}, all work expressed by tasks is already split up in atomic pieces of work, i.e.\ the work is a side effect of rewriting.
Furthermore, creating checkpoints should be fairly straightforward as \gls{MTASK} tasks do not rely on any global state---all information required to execute a task is stored in the task tree.
For example, the pin mode could be made a type parameter of the \gls{GPIO} pins, or interrupt handling could be made safer by incorporating the capabilities of the devices in order to reduce run-time errors.
\subsection{Scheduling}
-The scheduling in \gls{MTASK} works quite well but it is not real time.
+The scheduling in \gls{MTASK} works quite well, but it is not real time.
There is a variant of \gls{FRP} called \gls{PFRP} that allows for real-time operation \citep{belwal_variable_2013}.
Furthermore, an alternative to reducing the energy consumption by going to sleep is stepping down the processor frequency.
So called \gls{DVFS} is a scheduling technique that slows down the processor in order to reach the goals as late as possible, reducing the power consumption.
The language was called \gls{ARDSL} and offered a type safe interface to \gls{ARDUINO} \gls{CPP} dialect.
A \gls{CPP} code generation interpretation was available together with an \gls{ITASK} simulation interpretation.
There was no support for tasks nor functions.
-Some time later in the 2015 \gls{CEFP} summer school, an extended version was created that allowed the creation of imperative tasks, local \glspl{SDS} and the usage of functions \citep{koopman_type-safe_2019}.
+Some time later in the 2015 CEFP summer school, an extended version was created that allowed the creation of imperative tasks, local \glspl{SDS} and the usage of functions \citep{koopman_type-safe_2019}.
The name then changed from \gls{ARDSL} to \gls{MTASK}.
\subsection{Integration with iTask}
However, this version used a simplified version of \gls{MTASK} without functions.
This was later improved upon by creating a simplified interface where \glspl{SDS} from \gls{ITASK} could be used in \gls{MTASK} and the other way around \citep{lubbers_task_2018}.
It was shown by \citet{amazonas_cabral_de_andrade_developing_2018} that it was possible to build real-life \gls{IOT} systems with this integration.
-Moreover, a course on the \gls{MTASK} simulator was provided at the 2018 \gls{CEFP}\slash\gls{3COWS} winter school in Ko\v{s}ice, Slovakia \citep{koopman_simulation_2023}.
+Moreover, a course on the \gls{MTASK} simulator was provided at the 2018 \gls{3COWS} winter school in Ko\v{s}ice, Slovakia \citep{koopman_simulation_2023}.
\subsection{Transition to Task-oriented programming}
The \gls{MTASK} language as it is now was introduced in 2018 \citep{koopman_task-based_2018}.
Later the byte code compiler and \gls{ITASK} integration was added to the language \citep{lubbers_interpreting_2019}.
Moreover, it was shown that it is very intuitive to write microcontroller applications in a \gls{TOP} language \citep{lubbers_multitasking_2019}.
One reason for this is that a lot of design patterns that are difficult using standard means are for free in \gls{TOP} (e.g.\ multithreading).
-In 2019, the \gls{CEFP}\slash\gls{3COWS} summer school in Budapest, Hungary hosted a course on developing \gls{IOT} applications with \gls{MTASK} as well \citep{lubbers_writing_2023}.
+In 2019, the \gls{3COWS} summer school in Budapest, Hungary hosted a course on developing \gls{IOT} applications with \gls{MTASK} as well \citep{lubbers_writing_2023}.
\subsection{Task-oriented programming}
In 2022, the SusTrainable summer school in Rijeka, Croatia hosted a course on developing greener \gls{IOT} applications using \gls{MTASK} \citep{lubbers_green_2022}.
Funded by the Radboud-Glasgow Collaboration Fund, collaborative work was executed with Phil Trinder, Jeremy Singer, and Adrian Ravi Kishore Ramsingh.
An existing smart campus application was developed using \gls{MTASK} and quantitatively and qualitatively compared to the original application that was developed using a traditional \gls{IOT} stack \citep{lubbers_tiered_2020}.
This research was later extended to include a four-way comparison: \gls{PYTHON}, \gls{MICROPYTHON}, \gls{ITASK}, and \gls{MTASK} \citep{lubbers_could_2022}.
-Currently, power efficiency behaviour of traditional versus \gls{TOP} \gls{IOT} stacks is being compared as well adding a \gls{FREERTOS}, and an Elixir implementation to the mix as well.
+Currently, power efficiency behaviour of traditional versus \gls{TOP} \gls{IOT} stacks is being compared as well adding a FreeRTOS, and an Elixir implementation to the mix as well.
\input{subfilepostamble}
\end{document}
repositories / phd-thesis.git / blobdiff