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+
\begin{document}
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\chapter{Finale}%
\section{Finale}
The \gls{MTASK} system is a proof-of-concept system, though fully functioning, for integrating \gls{IOT} edge devices in \gls{TOP}.
In conjunction with \gls{ITASK}, it is possible to program all layers of the \gls{IOT} from a single declarative specification.
+The \gls{ITASK} system is used to program the top layers of an \gls{IOT} system, providing the server and the web \gls{UI}.
+Then, \gls{MTASK} can be used to integrate edge devices.
+Tasks for edge devices are written in the \gls{MTASK} \gls{DSL} and can be integrated in \gls{ITASK} using only a few functions.
+\todo{extend}
Deep embedding.
-\subsection{Future work}
+\section{Future work}
+\todo[inline]{De grens tussen future en related work is soms vaag maar ik heb het zo goed als mogelijk proberen te scheiden. Mis ik hier nog iets?}
There are many ways of extending the research on the \gls{MTASK} system that also concerns \gls{TOP} for resource constrained devices in general.
+Some obvious routes would be to add features, support more platforms,
+
+\todo{security}
+\subsection{Advanced edge devices techniques}
Edge devices may produce a lot of data and it is not always effective to send this data to the server for processing.
Leaving the produced data and computations on the edge device is called \emph{edge computing} \citep{shi_edge_2016}.
The \gls{MTASK} exhibits many properties of edge computing because it is possible to run entire workflows on the device.
The \gls{MTASK} language is a high-level \gls{DSL} so it would be obvious to introduce abstractions for edge computations.
For example, add \gls{TOP} support for machine learning on the edge device using TinyML \citep{sanchez-iborra_tinyml-enabled_2020}.
-Another recent advance in \gls{IOT} programming is intermittent computing.
-Intermittent computing
-
-Formal semantics
-
-Automatic peripherals
-
-Different architectures (FPGA?)
-
-Mesh communication
+Another recent advance in \gls{IOT} programming is battery-less or even battery-free computing.
+Instead of equipping the edge device with a battery, a capacitor is used in conjunction with some energy harvesting systems such as a solar panel.
+With the use of intermittent computing, resuming the computation after a, possibly unexpected, power loss, operation can still be achieved \citep{hester_batteries_2019}.
+After a reset, the program state is resumed from a checkpoint that was stored in some non-volatile memory.
+Many intermittent computing solutions rely on annotations from the programmer to divide the program into atomic blocks, sometimes called \emph{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.
+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.
+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.
+It would be interesting to see what \gls{TOP} abstraction could be useful for intermittent computing and what solutions are required to make this work.
+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.
+It would be interesting to investigate the possibilities for \gls{DVFS} in \gls{MTASK}.
+
+Mesh networks allow for communication not only to-and-fro the device and server but also between devices.
+The \gls{ITASK} system already contains primitives for distributed operation.
+For example, it is possible to run tasks or share data with \glspl{SDS} on a different machine.
+It would be interesting to investigate how this networking technique can be utilised in \gls{MTASK}.
+
+Finally, \glspl{FPGA} have been becoming cheaper and faster recently, allowing for purely functional code to be translated to \glspl{FPGA} code efficiently \citep{baaij_digital_2015}.
+It would be interested to see how and whether (parts of) \gls{TOP} programs or the functionality of the \gls{MTASK} \gls{OS} could be translated to \gls{FPGA} specifications.
+
+\subsection{Formal semantics}
+Semantics allow reasoning about the language and programs in order do (symbolic) simulation, termination checking, task equivalence, or otherwise.
+For \gls{ITASK} there have been two attempts to formally specify the language.
+First \citet{koopman_executable_2011} defined a semantics used for property based testing based on a minimal version of \gls{ITASK}.
+Then \citet{plasmeijer_task-oriented_2012} formalised \gls{ITASK} by providing an executable semantics for the language.
+Both semantics are not suitable for formal reasoning due to the complexity.
+Later, \citet{steenvoorden_tophat_2019} created \gls{TOPHAT}, a \gls{TOP} language with a complete formal specification with similar features to \gls{MTASK} \citep{steenvoorden_tophat_2019}.
+\Citet{antonova_mtask_2022} compared parts of \gls{MTASK} to the semantics of \gls{TOPHAT} semantics and created a preliminary semantics for a subset of \gls{MTASK}.
+Future research into extending the formal semantics of \gls{MTASK} is useful to give more guarantees on \gls{MTASK} programs.
+Maybe this opens the door to real-time operation as well.
+
+\subsection{\texorpdfstring{\Gls{TOP}}{Task-oriented programming}}
+In order to keep the resource constraints low, the \gls{MTASK} language contains only a minimal set of simple task combinators.
+From these simple combinators, complex collaboration patterns can be described.
+The \gls{ITASK} language is designed exactly the opposite.
+From just a few super combinators, all other combinators are derived.
+However, this approach requires a very powerful host language in which task combinators can be defined in terms of the host language.
+It would be fruitful to investigate which workflows cannot be specified with the limited set of combinators available in \gls{MTASK}.
+Furthermore, it is unclear whether all derived combinators from \gls{ITASK} can be expressed in terms of \gls{MTASK} combinators.
+\Citet{van_der_aalst_workflow_2003} defines a benchmark set of workflow patterns.
+It would be interesting to see which patterns can be implemented with \gls{MTASK}, and what additional combinators would be needed.
+Moreover, editors are a crucial part of \gls{TOP}.
+In \gls{MTASK}, sensors can be seen as read-only shared editors that are updated by the system.
+It would be interesting to investigate how actual interactive editors would fit in \gls{MTASK}.
+For example, many smartwatches contain touch sensitive screens that could be used to interact with the user in this way.
+
+\Glspl{SDS} in \gls{ITASK} have a rich set of combinators to transform and combine the \glspl{SDS} into new \gls{SDS}.
+In \gls{MTASK}, \glspl{SDS} are just typed global variables that may or may not proxy an \gls{ITASK} \gls{SDS}.
+It would be interesting to port the \gls{SDS} combinators to \gls{MTASK} as well, allowing them to be transformed and combined also.
+
+\subsection{Usability}
+The promise of \glspl{DSL} has often been that a domain expert could program with little technical knowledge of the host programming language.
+Some even propose that a \gls{DSL} is a \gls{UI} for domain experts to computation platforms \citep{management_association_evaluating_2014}.
+In practise this is not always the case due to crippling syntax and convoluted error messages.
+Recent approaches in interactive editors for programming language source code such as dynamic editors \citep{koopman_dynamic_2021} or typed tree editors such as Hazelnut \citep{omar_hazelnut_2017} could prove useful for supporting the \gls{DSL} programmer in using \gls{MTASK}.
+If the editor produces correct \gls{MTASK} code by construction, much of the problems could be avoided.
+In the same respect, as \gls{MTASK} is a tagless-final \gls{EDSL} and uses \gls{HOAS}, the error messages are complex and larded with host language features.
+Much research has gone into simplifying these error messages by translating them to the \gls{DSL} domain, see for example \citep{serrano_type_2018}.
+A future directions could be to apply the \gls{EDSL} error message techniques on \gls{MTASK} as well.
+
+The serialisation and deserialisation of data types is automated both on the server and the \gls{MTASK} device using generic programming.
+Using the structural information of the data type, the code responsible for the functionality is automatically generated.
+Peripherals are not yet fully integrated in such a way.
+When a peripheral is added, the programmer has to define the correct byte code, implement the instructions in the interpreter, add task tree nodes, and implement them in the rewrite system.
+It would be interesting to investigate whether this can be automated or centralised in a way.
\section{Related work}
The novelties of the \gls{MTASK} system can be compared to existing systems in several categories.
However, there is no integration between the client and the server other than that they are programmed from a single source.
Mat\`e is an example of an early tierless sensor network framework where devices are provided with a virtual machine using TinyOS for dynamic provisioning \citep{levis_mate_2002}.
-\subsubsection{\texorpdfstring{\Glsxtrlongpl{DSL}}{DSLs} for microcontrollers}\label{sec:related_dsl}
+\subsection{\texorpdfstring{\Glsxtrlongpl{DSL}}{DSLs} for microcontrollers}\label{sec:related_dsl}
Many \glspl{DSL} provide higher-level programming abstractions for microcontrollers, for example providing strong typing or memory safety.
For example Copilot \citep{hess_arduino-copilot_2020} and Ivory \citep{elliott_guilt_2015} are imperative \glspl{DSL} embedded in a functional language that compile to \ccpp{}.
\todo{uit\-brei\-den?}
FlowTask & 2011 & \CIRCLE{} & \CIRCLE{} & \Circle{} & \Circle{} & \Circle{} & \Circle{}\\
Ocram & 2013 & \CIRCLE{} & \CIRCLE{} & \Circle{} & \CIRCLE{} & \Circle{} & \Circle{}\\
C\'eu & 2013 & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \CIRCLE{}\\
- \Gls{MTASK} & 2022 & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \LEFTcircle{}\tnote{1} & \LEFTcircle{}\tnote{2}\\
+ \gls{MTASK} & 2022 & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \CIRCLE{} & \LEFTcircle{}\tnote{1} & \LEFTcircle{}\tnote{2}\\
\bottomrule
\end{tabular}
\begin{tablenotes}
Due to the compilation to \gls{C} it is possible to run emfrp programs on tiny computers.
However, the tasks are not interpreted and there is no communication with a server.
-Other examples are mfrp \citep{sawada_emfrp:_2016}, CFRP \citep{suzuki_cfrp_2017}, XFRP \citep{10.1145/3281366.3281370}, Juniper \citep{helbling_juniper:_2016}, Hailstorm \citep{sarkar_hailstorm_2020}, Haski \citep{valliappan_towards_2020}, arduino-copilot \citep{hess_arduino-copilot_2020}.
+Other examples are CFRP \citep{suzuki_cfrp_2017}, XFRP \citep{10.1145/3281366.3281370}, Juniper \citep{helbling_juniper:_2016}, Hailstorm \citep{sarkar_hailstorm_2020}, Haski \citep{valliappan_towards_2020}, arduino-copilot \citep{hess_arduino-copilot_2020}.
\subsection{\texorpdfstring{\Glsxtrlong{TOP}}{Task-oriented programming}}\label{sec:related_top}
\Gls{TOP} as a paradigm with has been proven to be effective for implementing distributed, multi-user applications in many domains.
repositories / phd-thesis.git / blobdiff