  Fog computing is a promising computing paradigm in which IoT data can be
processed near the edge to support time-sensitive applications. However, the
availability of the resources in the computation device is not stable since
they may not be exclusively dedicated to the processing in the Fog environment.
This, combined with dynamic user behaviour, can affect the execution of
applications. To address dynamic changes in user behaviour in a resource
limited Fog device, this paper proposes a Multi-Criteria-based resource
allocation policy with resource reservation in order to minimise overall delay,
processing time and SLA violation which considers Fog computing-related
characteristics, such as device heterogeneity, resource constraint and
mobility, as well as dynamic changes in user requirements. We employ multiple
objective functions to find appropriate resources for execution of
time-sensitive tasks in the Fog environment. Experimental results show that our
proposed policy performs better than the existing one, reducing the total delay
by 51%. The proposed algorithm also reduces processing time and SLA violation
which is beneficial to run time-sensitive applications in the Fog environment.
