introduction.tex

   1 \section{Introduction}
   2 The \gls{TOP} paradigm and the according \gls{iTasks} implementation offer a
   3 high abstraction level for real life workflow tasks. These workflow tasks can be
   4 described through an \gls{EDSL} and modeled as \glspl{Task}
   5 From the specification the system will then generate a multi-user web service.
   6 This web service is accessed through a browser and used to complete these
   7 \glspl{Task}. Familiar workflow patterns like sequence, parallel and
   8 conditional tasks can be modelled using combinators.
   9
  10 \gls{iTasks} has been shown to be useful in many fields of operation such as
  11 incident management~\cite{lijnse_top_2013}. Interfaces are automatically
  12 generated for the types of data which makes rapid development possible.
  13 \Glspl{Task} in the \gls{iTasks} system are modelled after real life workflow
  14 tasks but the modelling is applied on a very high level. Therefore it is
  15 difficult to connect \gls{iTasks} tasks to the real world tasks and let them
  16 interact. A lot of the actual tasks can be \emph{performed} by small \gls{IoT}
  17 devices. Nevertheless, adding such devices to the current system is difficult
  18 to say the least as it was not designed to cope with these devices.
  19
  20 In the current system such adapters, in principle, can be written as
  21 \glspl{SDS}\footnote{Similar as to resources such as time are available in
  22 the current \gls{iTasks} implementation} but this requires a very specific
  23 adapter to be written for every device and functionality. However, this forces
  24 a fixed logic in the device that is set at compile time. A lot of the small
  25 \gls{IoT} devices have limited processing power but can still contain decision
  26 making. Oortgiese et al.\ lifted \gls{iTasks} from a single server model to a
  27 distributed server architecture that is also runnable on smaller devices like
  28 \acrshort{ARM} devices\cite{oortgiese_distributed_2017}. However, this is
  29 limited to fairly high performance devices that are equipped with high speed
  30 communication channels. Devices in \gls{IoT} often only have \gls{LTN}
  31 communication with low bandwidth and a very limited amount of processing power
  32 and are therefore not suitable to run an entire \gls{iTasks} core.
  33
  34 \glspl{mTask} will bridge this gap by introducing a new communication protocol,
  35 device application and \glspl{Task} synchronizing the formers.
  36 The system can run on devices as small as Arduino microcontrollers and
  37 operates via the same paradigms and patterns as regular \glspl{Task}.
  38 \glspl{mTask} can run small imperative programs written in a \gls{EDSL} and
  39 have access to \glspl{SDS}. In this way \glspl{Task} can be sent to the device
  40 at runtime and information can be exchanged.
  41
  42 \section{Document structure}
  43 The structure of the thesis is as follows.
  44 Chapter~\ref{chp:introduction} contains the problem statement, motivation and
  45 the structure of the document.
  46 Chapter~\ref{chp:methods} describes the foundations on which the implementation
  47 is built together with the new techniques introduced.
  48 Chapter~\ref{chp:results} shows the results in the form of an example
  49 application accompanied with implementation.
  50 Chapter~\ref{chp:conclusion} concludes by answering the research questions
  51 and discusses future research.
  52 Appendix~\ref{app:communication-protocol} shows the concrete protocol used for
  53 communicating between the server and client.
  54 Appendix~\ref{app:device-interface} shows the concrete interface for the
  55 devices.