Workflow Variability for Autonomic IoT Systems

Damian Arellanes and Kung-Kiu Lau
School of Computer Science
The University of Manchester
Manchester M13 9PL, United Kingdom
{damian.arellanesmolina, kung-kiu.lau}@manchester.ac.uk

Abstract: 

Autonomic IoT systems require variable behaviour
at runtime to adapt to different system contexts. Building suitable
models that span both design-time and runtime is thus essential
for such systems. However, existing approaches separate the
variability model from the behavioural model, leading to syn-
chronization issues such as the need for dynamic reconfiguration
and dependency management. Some approaches define a fixed
number of behaviour variants and are therefore unsuitable for
highly variable contexts. This paper extends the semantics of
the DX-MAN service model so as to combine variability with
behaviour. The model allows the design of composite services
that define an infinite number of workflow variants which can
be chosen at runtime without any reconfiguration mechanism.
We describe the autonomic capabilities of our model by using a
case study in the domain of smart homes.