1 \documentclass[../thesis.tex
]{subfiles
}
3 \input{subfilepreamble
}
5 \setcounter{chapter
}{7}
11 \begin{chapterabstract
}
12 \noindent This chapter wraps up the monograph by means of:
15 \item an outlook on future work;
16 \item an overview of the related work;
17 \item and a history of the
\gls{MTASK
} system.
22 The
\gls{MTASK
} system is a proof-of-concept system, though fully functioning, for integrating
\gls{IOT
} edge devices in
\gls{TOP
}.
23 In conjunction with
\gls{ITASK
}, it is possible to program all layers of the
\gls{IOT
} from a single declarative specification.
24 The
\gls{ITASK
} system is used to program the top layers of an
\gls{IOT
} system, providing the server and the web
\gls{UI
}.
25 Then,
\gls{MTASK
} can be used to integrate edge devices.
26 Tasks for edge devices are written in the
\gls{MTASK
} \gls{DSL
} and can be integrated in
\gls{ITASK
} using only a few functions.
32 \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?
}
33 There are many ways of extending the research on the
\gls{MTASK
} system that also concerns
\gls{TOP
} for resource constrained devices in general.
34 Some obvious routes would be to add features, support more platforms,
38 \subsection{Advanced edge devices techniques
}
39 Edge devices may produce a lot of data and it is not always effective to send this data to the server for processing.
40 Leaving the produced data and computations on the edge device is called
\emph{edge computing
} \citep{shi_edge_2016
}.
41 The
\gls{MTASK
} exhibits many properties of edge computing because it is possible to run entire workflows on the device.
42 However, it would be interesting to see how far this can be extended.
43 The
\gls{MTASK
} language is a high-level
\gls{DSL
} so it would be obvious to introduce abstractions for edge computations.
44 For example, add
\gls{TOP
} support for machine learning on the edge device using TinyML
\citep{sanchez-iborra_tinyml-enabled_2020
}.
46 Another recent advance in
\gls{IOT
} programming is battery-less or even battery-free computing.
47 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.
48 With the use of intermittent computing, resuming the computation after a, possibly unexpected, power loss, operation can still be achieved
\citep{hester_batteries_2019
}.
49 After a reset, the program state is resumed from a checkpoint that was stored in some non-volatile memory.
50 Many intermittent computing solutions rely on annotations from the programmer to divide the program into atomic blocks, sometimes called
\emph{tasks
} as well.
51 These blocks are marked as such because in the case of an reset of the system, the work must be done again.
52 Examples of such blocks are
\gls{I2C
} transmissions or calculations that rely on recent sensor data.
53 In
\gls{MTASK
}, all work expressed by tasks is already split up in atomic pieces of work.
54 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.
55 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.
56 An alternative to reducing the energy consumption by going to sleep is stepping down the processor frequency.
57 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.
58 It would be interesting to investigate the possibilities for
\gls{DVFS
} in
\gls{MTASK
}.
60 Mesh networks allow for communication not only to-and-fro the device and server but also between devices.
61 The
\gls{ITASK
} system already contains primitives for distributed operation.
62 For example, it is possible to run tasks or share data with
\glspl{SDS
} on a different machine.
63 It would be interesting to investigate how this networking technique can be utilised in
\gls{MTASK
}.
65 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
}.
66 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.
68 \subsection{Formal semantics
}
69 Semantics allow reasoning about the language and programs in order do (symbolic) simulation, termination checking, task equivalence, or otherwise.
70 For
\gls{ITASK
} there have been two attempts to formally specify the language.
71 First
\citet{koopman_executable_2011
} defined a semantics used for property based testing based on a minimal version of
\gls{ITASK
}.
72 Then
\citet{plasmeijer_task-oriented_2012
} formalised
\gls{ITASK
} by providing an executable semantics for the language.
73 Both semantics are not suitable for formal reasoning due to the complexity.
74 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
}.
75 \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
}.
76 Future research into extending the formal semantics of
\gls{MTASK
} is useful to give more guarantees on
\gls{MTASK
} programs.
77 Maybe this opens the door to real-time operation as well.
79 \subsection{\texorpdfstring{\Gls{TOP
}}{Task-oriented programming
}}
80 In order to keep the resource constraints low, the
\gls{MTASK
} language contains only a minimal set of simple task combinators.
81 From these simple combinators, complex collaboration patterns can be described.
82 The
\gls{ITASK
} language is designed exactly the opposite.
83 From just a few super combinators, all other combinators are derived.
84 However, this approach requires a very powerful host language in which task combinators can be defined in terms of the host language.
85 It would be fruitful to investigate which workflows cannot be specified with the limited set of combinators available in
\gls{MTASK
}.
86 Furthermore, it is unclear whether all derived combinators from
\gls{ITASK
} can be expressed in terms of
\gls{MTASK
} combinators.
87 \Citet{van_der_aalst_workflow_2003
} defines a benchmark set of workflow patterns.
88 It would be interesting to see which patterns can be implemented with
\gls{MTASK
}, and what additional combinators would be needed.
89 Moreover, editors are a crucial part of
\gls{TOP
}.
90 In
\gls{MTASK
}, sensors can be seen as read-only shared editors that are updated by the system.
91 It would be interesting to investigate how actual interactive editors would fit in
\gls{MTASK
}.
92 For example, many smartwatches contain touch sensitive screens that could be used to interact with the user in this way.
94 \Glspl{SDS
} in
\gls{ITASK
} have a rich set of combinators to transform and combine the
\glspl{SDS
} into new
\gls{SDS
}.
95 In
\gls{MTASK
},
\glspl{SDS
} are just typed global variables that may or may not proxy an
\gls{ITASK
} \gls{SDS
}.
96 It would be interesting to port the
\gls{SDS
} combinators to
\gls{MTASK
} as well, allowing them to be transformed and combined also.
98 \subsection{Usability
}
99 The promise of
\glspl{DSL
} has often been that a domain expert could program with little technical knowledge of the host programming language.
100 Some even propose that a
\gls{DSL
} is a
\gls{UI
} for domain experts to computation platforms
\citep{management_association_evaluating_2014
}.
101 In practise this is not always the case due to crippling syntax and convoluted error messages.
102 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
}.
103 If the editor produces correct
\gls{MTASK
} code by construction, much of the problems could be avoided.
104 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.
105 Much research has gone into simplifying these error messages by translating them to the
\gls{DSL
} domain, see for example
\citep{serrano_type_2018
}.
106 A future directions could be to apply the
\gls{EDSL
} error message techniques on
\gls{MTASK
} as well.
108 The serialisation and deserialisation of data types is automated both on the server and the
\gls{MTASK
} device using generic programming.
109 Using the structural information of the data type, the code responsible for the functionality is automatically generated.
110 Peripherals are not yet fully integrated in such a way.
111 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.
112 It would be interesting to investigate whether this can be automated or centralised in a way.
114 \section{Related work
}
115 The novelties of the
\gls{MTASK
} system can be compared to existing systems in several categories.
116 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
}).
117 \Cref{sec_t4t:TiredvsTierless
} contains an elaborate related work section regarding tierless systems in general.
119 \subsection{Interpretation
}\label{sec:related_int
}
120 There are a myriad of interpreted programming languages available for some of the bigger more powerful edge devices.
121 For example, for the popular ESP8266 chip there are ports of
\gls{MICROPYTHON
}, LUA, Basic, JavaScript and Lisp.
122 All of these languages, except the Lisp dialect uLisp (see
\cref{sec:related_fp
}), are imperative and do not support multiasking out of the box.
123 They lay pretty hefty constraints on the memory and as a result do not work on smaller microcontrollers.
124 Another interpretation solution for the tiniest devices is Firmata, a protocol for remotely controlling the microcontroller and using a server as the interpreter host
\citep{steiner_firmata:_2009
}.
125 \citet{grebe_haskino:_2016
} wrapped this in a remote monad for integration with
\gls{HASKELL
} that allowed imperative code to be interpreted on the microprocessors.
126 Later this system was extended to support multithreading as well, stepping away from Firmata as the basis and using their own
\gls{RTS
} \citep{grebe_threading_2019
}.
127 It differs from our approach because continuation points need to be defined by hand there is no automatic safe data communication.
128 \Citet{baccelli_reprogramming_2018
} provide a single language
\gls{IOT
} system based on the RIOT
\gls{OS
} that allows runtime deployment of code snippets called containers.
129 Both client and server are written in JavaScript.
130 However, there is no integration between the client and the server other than that they are programmed from a single source.
131 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
}.
133 \subsection{\texorpdfstring{\Glsxtrlongpl{DSL
}}{DSLs
} for microcontrollers
}\label{sec:related_dsl
}
134 Many
\glspl{DSL
} provide higher-level programming abstractions for microcontrollers, for example providing strong typing or memory safety.
135 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{}.
136 \todo{uit\-brei\-den?
}
138 \subsection{\texorpdfstring{\Glsxtrlong{FP
}}{Functional programming
}}\label{sec:related_fp
}
139 \Citet{haenisch_case_2016
} showed that there are major benefits to using functional languages for
\gls{IOT
} applications.
140 They showed that using function languages increased the security and maintainability of the applications.
141 Traditional implementations of general purpose functional languages have high memory requirements rendering them unusable for tiny computers.
142 There have been many efforts to create a general purpose functional language that does fit in small memory environments, albeit with some concessions.
143 For example, there has been a history of creating tiny Scheme implementations for specific microcontrollers.
144 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.
145 \Citep{suchocki_microscheme:_2015
} created Microscheme, a functional language targeting
\gls{ARDUINO
} compatible microcontrollers.
146 The
{*BIT
} languages all compile to assembly while Microscheme compiles to
\gls{CPP
}, heavily supported by
\gls{CPP
} lambdas available even on
\gls{ARDUINO
} AVR targets.
147 An interpreted Lisp implementation called uLisp also exists that runs on microcontrollers with as small as the
\gls{ARDUINO
} {UNO
} \citep{johnson-davies_lisp_2020
}.
149 \subsection{Multitasking
}\label{sec:related_multi
}
150 Applications for tiny computers are often parallel in nature.
151 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.
152 Microcontrollers often do not benefit from an
\gls{OS
} due to memory and processing constraints.
153 Therefore, writing multitasking applications in an imperative language is possible but the tasks have to be interleaved by hand
\citep{feijs_multi-tasking_2013
}.
154 This results in hard to maintain, error prone and unscalable spaghetti code.
156 There are many solutions to overcome this problem in imperative languages.
157 If the host language is a functional language (e.g.\ the aforementioned scheme variants) multitasking can be achieved without this burden relatively easy using continuation style multiprocessing
\citep{wand_continuation-based_1980
}.
158 Writing in this style is complicated and converting an existing program in this continuation passing style results in relatively large programs.
159 Furthermore, there is no built-in thread-safe communication possible between the tasks.
160 A
\gls{TOP
} or
\gls{FRP
} based language benefits even more because the programmer is not required to explicitly define continuation points.
162 Regular preemptive multithreading is too memory intensive for smaller microcontrollers and therefore not suitable.
163 Manual interleaving of imperative code can be automated to certain extents.
164 Solutions often require an
\gls{RTOS
}, have a high memory requirement, do not support local variables, no thread-safe shared memory, no composition or no events as described in
\cref{tbl:multithreadingcompare
}.
165 The table compares the solutions in the relevant categories with
\gls{MTASK
}.
168 \begin{threeparttable
}
170 An overview of imperative multithreading solutions for tiny computers with their relevant characteristics.
171 The characteristics are: sequential execution, local variable support, parallel composition, deterministic execution, bounded execution and safe shared memory (adapted from
\citet[p.\
12]{santanna_safe_2013
}).
172 }\label{tbl:multithreadingcompare
}
173 % \begin{tabular}{lc>{\columncolor[gray]{0.95}}cc>{\columncolor[gray]{0.95}}cc>{\columncolor[gray]{0.95}}cc}
175 \begin{tabular
}{lccccccc
}
177 \multicolumn{2}{c
}{Language
} &
\multicolumn{3}{c
}{Complexity
} &
\multicolumn{3}{c
}{Safety
}\\
179 Name & Year & SeqCmp & LocVar & ParCmp & DetEx & BndEx & SafeMem\\
181 Preemptive & many &
\CIRCLE{} &
\CIRCLE{} &
\Circle{} &
\Circle{} & rt &
\Circle{}\\
182 nesC &
2003 &
\Circle{} &
\Circle{} &
\Circle{} &
\CIRCLE{} & async &
\Circle{}\\
183 OSM &
2005 &
\Circle{} &
\CIRCLE{} &
\CIRCLE{} &
\Circle{} &
\Circle{} &
\Circle{}\\
184 Protothreads &
2006 &
\CIRCLE{} &
\Circle{} &
\Circle{} &
\CIRCLE{} &
\Circle{} &
\Circle{}\\
185 TinyThreads &
2006 &
\CIRCLE{} &
\CIRCLE{} &
\Circle{} &
\CIRCLE{} &
\Circle{} &
\Circle{}\\
186 Sol &
2007 &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\Circle{} &
\Circle{}\\
187 FlowTask &
2011 &
\CIRCLE{} &
\CIRCLE{} &
\Circle{} &
\Circle{} &
\Circle{} &
\Circle{}\\
188 Ocram &
2013 &
\CIRCLE{} &
\CIRCLE{} &
\Circle{} &
\CIRCLE{} &
\Circle{} &
\Circle{}\\
189 C\'eu &
2013 &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{}\\
190 \gls{MTASK
} &
2022 &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\CIRCLE{} &
\LEFTcircle{}\tnote{1} &
\LEFTcircle{}\tnote{2}\\
194 \item [1] Only for tasks, not for expressions.
195 \item [2] Using
\glspl{SDS
}.
200 \subsection{\texorpdfstring{\Glsxtrlong{FRP
}}{Functional reactive programming
}}\label{sec:related_frp
}
201 The
\gls{TOP
} paradigm is often compared to
\gls{FRP
} and while they appear to be similar---they are both event driven---in fact they are very different.
202 \Gls{FRP
} was introduced by
\citet{elliott_functional_1997
}.
203 The paradigm strives to make modelling systems safer, more efficient, composable.
204 The core concepts are behaviours and events.
205 A behaviour is a value that varies over time.
206 Events are happenings in the real world and can trigger behaviours.
207 Events and behaviours may be combined using combinators.
208 \Gls{TOP
} allows for more complex collaboration patterns than
\gls{FRP
} \citep{wang_maintaining_2018
}, and in consequence is unable to provide the strong guarantees on memory usage available in a restricted variant of
\gls{FRP
} such as arrowized
\gls{FRP
} \citep{nilsson_functional_2002
}.
210 The way
\gls{FRP
}, and for that matter
\gls{TOP
}, systems are programmed stays close to the design when the domain matches suits the paradigm.
211 The
\gls{IOT
} domain seems to suit this style of programming very well in just the device layer but also for entire
\gls{IOT
} systems.
213 For example, Potato is an
\gls{FRP
} language for building entire
\gls{IOT
} systems using powerful devices such as the Raspberry Pi leveraging the Erlang
\gls{VM
} \citep{troyer_building_2018
}.
214 It requires client devices to be able to run the Erlang
\gls{VM
} which makes it unsuitable for low memory environments.
216 The emfrp language compiles a
\gls{FRP
} specification for a microcontroller to
\gls{C
} code
\citep{sawada_emfrp:_2016
}.
217 The
\gls{IO
} part, the bodies of some functions, still need to be implemented.
218 These
\gls{IO
} functions can then be used as signals and combined as in any
\gls{FRP
} language.
219 Due to the compilation to
\gls{C
} it is possible to run emfrp programs on tiny computers.
220 However, the tasks are not interpreted and there is no communication with a server.
222 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
}.
224 \subsection{\texorpdfstring{\Glsxtrlong{TOP
}}{Task-oriented programming
}}\label{sec:related_top
}
225 \Gls{TOP
} as a paradigm with has been proven to be effective for implementing distributed, multi-user applications in many domains.
226 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
}.
227 In general,
\gls{TOP
} results in a higher maintainability, a high separation of concerns and more effective handling of interruptions of workflow.
228 \Gls{IOT
} applications contain a distributed and multi-user component, but the software on the device is mostly follows multiple loosely dependent workflows.
229 The only other
\gls{TOP
} language for embedded systems is $
\mu$Tasks
\citep{piers_task-oriented_2016
}.
230 It is a non-distributed
\gls{TOP
} \gls{EDSL
} hosted in
\gls{HASKELL
} designed for embedded systems such as payment terminals.
231 They showed that applications tend to be able to cope well with interruptions and be more maintainable.
232 However, the hardware requirements for running the standard
\gls{HASKELL
} system are high.
234 \section{History of
\texorpdfstring{\gls{MTASK
}}{mTask
}}
235 The development of
\gls{MTASK
} or its predecessors has been going on for almost seven years now though it really set off during my master's thesis.
236 This section provides an exhaustive overview of the work on
\gls{MTASK
} and its predecessors.
238 \subsection{Generating
\texorpdfstring{\ccpp{}}{\ccpp{}} code
}
239 A first throw at a class-based shallowly
\gls{EDSL
} for microcontrollers was made by
\citet{plasmeijer_shallow_2016
}.
240 The language was called
\gls{ARDSL
} and offered a type safe interface to
\gls{ARDUINO
} \gls{CPP
} dialect.
241 A
\gls{CPP
} code generation backend was available together with an
\gls{ITASK
} simulation backend.
242 There was no support for tasks nor even functions.
243 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
}.
244 The name then changed from
\gls{ARDSL
} to
\gls{MTASK
}.
246 \subsection{Integration with
\texorpdfstring{\gls{ITASK
}}{iTask
}}
247 \Citet{lubbers_task_2017
} extended this in his Master's Thesis by adding integration with
\gls{ITASK
} and a bytecode compiler to the language.
248 \Gls{SDS
} in
\gls{MTASK
} could be accessed on the
\gls{ITASK
} server.
249 In this way, entire
\gls{IOT
} systems could be programmed from a single source.
250 However, this version used a simplified version of
\gls{MTASK
} without functions.
251 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
}.
252 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.
253 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_2018
}.
255 \subsection{Transition to
\texorpdfstring{\gls{TOP
}}{TOP
}}
256 The
\gls{MTASK
} language as it is now was introduced in
2018 \citep{koopman_task-based_2018
}.
257 This paper updated the language to support functions, simple tasks, and
\glspl{SDS
} but still compiled to
\gls{ARDUINO
} \gls{CPP
} code.
258 Later the byte code compiler and
\gls{ITASK
} integration was added to the language
\citep{lubbers_interpreting_2019
}.
259 Moreover, it was shown that it is very intuitive to write microcontroller applications in a
\gls{TOP
} language
\citep{lubbers_multitasking_2019
}.
260 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).
261 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_2019
}.
263 \subsection{\texorpdfstring{\Glsxtrshort{TOP
}}{TOP
}}
264 In
2022, the SusTrainable summer school in Rijeka, Croatia hosted a course on developing greener
\gls{IOT
} applications using
\gls{MTASK
} as well
\citep{lubbers_green_2022
}.
265 Several students worked on extending
\gls{MTASK
} with many useful features:
266 \Citet{van_der_veen_mutable_2020
} did preliminary work on a green computing analysis, built a simulator, and explored the possibilities for adding bounded datatypes;
\citet{de_boer_secure_2020
} investigated the possibilities for secure communication channels;
\citeauthor{crooijmans_reducing_2021
} \citeyearpar{crooijmans_reducing_2021,crooijmans_reducing_2022
} added abstractions for low-power operation to
\gls{MTASK
} such as hardware interrupts and power efficient scheduling; and
\citet{antonova_mtask_2022
} defined a preliminary formal semantics for a subset of
\gls{MTASK
}.
267 In
2023, the SusTrainable summer school in Coimbra, Portugal will host a course on
\gls{MTASK
} as well.
269 \subsection{\texorpdfstring{\gls{MTASK
}}{mTask
} in practise
}
270 Funded by the Radboud-Glasgow Collaboration Fund, collaborative work was executed with Phil Trinder, Jeremy Singer, and Adrian Ravi Kishore Ramsingh.
271 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
}.
272 This research was later extended to include a four-way comparison:
\gls{PYTHON
},
\gls{MICROPYTHON
},
\gls{ITASK
}, and
\gls{MTASK
} \citep{lubbers_could_2022
}.
273 Currently, power efficiency behaviour of traditional versus
\gls{TOP
} \gls{IOT
} stacks is being compared as well adding a
\gls{FREERTOS
}, and an elixer/potato implementation to the mix as well.
275 \input{subfilepostamble
}
repositories / phd-thesis.git / blob