A Policy-Making Approach for Offloading Data in the Fog Computing Context
Fog computing; Data offloading; Taxonomy.
Currently, the most varied objects are connected to the Internet and, at the same time,
generating massive amounts of data. Linked to this fact, the internet of things applications
are increasingly complex and with more responsibilities. Storing, processing, managing, and
analyzing this amount of data are challenging processes. The execution of these processes
is commonly performed in external services through cloud computing, however, a paradigm
called fog computing enables such execution directly at the edge of the network, serving
as a support for the agile and efficient functioning of the internet of things. However,
when fog computing does not have enough resources to perform these actions, the data is
transferred to entities with higher computational capabilities, which is a practice known
as offloading. In this regard, this research explore the use of policies that guide the process
of data offloading in the context of fog computing. The objective of this work is to define
and organize strategies to guide the development of policies for data offloading in fog
computing. For this, the concrete results of the work were: the survey of policies for data
offloading proposed by the literature; the development of a taxonomy that meets the main
aspects used in the data offloading process; the development of a guide that recommends
practices for policy making for data offloading; a demonstration of the instantiation of
the approach, through case studies and the implementation of reference prototypes to the
proposed approach. Finally, this research identifies that the use of such policies has much
to contribute to fog-based applications as it improves the data offloading process.