process the rest of Pieter's comments

[phd-thesis.git] / top / finale.tex

diff --git a/top/finale.tex b/top/finale.tex
index 6b002bb..ffbd9f4 100644 (file)
--- a/top/finale.tex
+++ b/top/finale.tex
@@ -94,7 +94,7 @@ Regular preemptive multithreading is too memory intensive for smaller microcontr
 Manual interleaving of imperative code can be automated to certain extents.
 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}.
 This table extends a comparison table with various solutions to multitasking to \gls{MTASK} in the relevant categories.
-\todo[inline]{Uitleg over de talen geven}
+%\todo[inline]{Uitleg over de talen geven}
 
 \begin{table}
        \begin{threeparttable}
@@ -157,7 +157,7 @@ These \gls{IO} functions can then be used as signals and combined as in any \gls
 Due to the compilation to \gls{C} it is possible to run emfrp programs on tiny computers.
 However, in contrast to in \gls{MTASK}, the tasks are not interpreted and there is no automated communication with a server.
 
-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}.
+Other examples are CFRP \citep{suzuki_cfrp_2017}, XFRP \citep{shibanai_distributed_2018}, Juniper \citep{helbling_juniper:_2016}, Hailstorm \citep{sarkar_hailstorm_2020}, Haski \citep{valliappan_towards_2020}, arduino-copilot \citep{hess_arduino-copilot_2020}.
 
 \subsection{Task-oriented programming}\label{sec:related_top}
 \Gls{TOP} as a paradigm has proven to be effective for implementing distributed, multi-user applications in many domains.
@@ -204,7 +204,7 @@ In \gls{MTASK}, all work expressed by tasks is already split up in atomic pieces
 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 is interesting to see what \gls{TOP} abstraction are useful for intermittent computing and what solutions are required to make this work.
 
-Mesh networks allow for communication not only to-and-fro the device and server but also between devices.
+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 different machines.
 It is interesting to investigate how this networking technique can be utilised in \gls{MTASK}.