high abstraction level for real life workflow tasks. These workflow tasks can be
described through an \gls{EDSL} and modeled as \glspl{Task}
From the specification the system will then generate a multi-user web service.
-This web service can be accessed through a browser and used to complete these
+This web service is accessed through a browser and used to complete these
\glspl{Task}. Familiar workflow patterns like sequence, parallel and
conditional tasks can be modelled using combinators.
\gls{iTasks} has been shown to be useful in many fields of operation such as
incident management~\cite{lijnse_top_2013}. Interfaces are automatically
generated for the types of data which makes rapid development possible.
-However, while the tasks in the \gls{iTasks} system model after real life
-workflow tasks the modelling is very high level. It is difficult to connect
-actual tasks to the real tasks and let them interact. A lot of the actual tasks
-can be \emph{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.
+\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} tasks to the real world tasks and let them
+interact. A lot of the actual tasks can be \emph{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.
In the current system such adapters, in principle, can be written as
\glspl{SDS}\footnote{Similar as to resources such as time are available in
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~\cite{oortgiese_distributed_2017} that is also
-runnable on smaller devices like \acrshort{ARM} devices. However, this is
+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 only have \gls{LTN}
communication with low bandwidth and a very limited amount of processing power
Chapter~\ref{chp:introduction} contains the problem statement, motivation and
the structure of the document.
Chapter~\ref{chp:methods} describes the foundations on which the implementation
-is built together with the new techniques introduced.
-Chapter~\ref{chp:results} shows the results in the form of an example
+is built.
+Chapter~\ref{chp:results} shows the new techniques deviced and an example
application accompanied with implementation.
Chapter~\ref{chp:conclusion} concludes by answering the research questions
and discusses future research.
repositories / msc-thesis1617.git / blobdiff