-such as time are available in the current \gls{iTasks} implementation}.
-However, this
-requires a very specific adapter to be written for every device and function.
-This forces a fixed logic in the device that is set at compile time. Many
-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 that is also runnable on small
-devices such as those powered by \gls{ARM}~\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 have only \gls{LTN} communication with low bandwidth
-and a very limited amount of processing power and are therefore not suitable to
-run an entire \gls{iTasks} core.
+such as time are available in the current \gls{iTasks} implementation.}.
+However, this requires a very specific adapter to be written for every device
+and function. This forces a fixed logic in the device that is set at compile
+time. Many small \gls{IoT} devices have limited processing power but are still
+powerful enough for decision making. Recompiling the code for a small
+\gls{IoT} device is expensive and therefore it is difficult to use a device
+dynamically for multiple purposes. Oortgiese et al.\ lifted \gls{iTasks} from a
+single server model to a distributed server architecture that is also runnable
+on small devices such as those powered by
+\gls{ARM}~\cite{oortgiese_distributed_2017}. However, this is limited to
+fairly high performance devices that are equipped with high speed communication
+channels because it requires the device to run the entire \gls{iTasks} core.
+Devices in \gls{IoT} often have only Low Throughput Network communication with
+low bandwidth and a very limited amount of processing power and are therefore
+not suitable to run an entire \gls{iTasks} core.