  This paper investigates the role and the impact of control operations for
dynamic mobile edge computing (MEC) empowered by Reconfigurable Intelligent
Surfaces (RISs), in which multiple devices offload their computation tasks to
an access point (AP) equipped with an edge server (ES), with the help of the
RIS. While usually ignored, the control aspects related to channel estimation
(CE), resource allocation (RA), and control signaling play a fundamental role
in the user-perceived delay and energy consumption. In general, the higher the
resources involved in the control operations, the higher their reliability;
however, this introduces an overhead, which reduces the number of resources
available for computation offloading, possibly increasing the overall latency
experienced. Conversely, a lower control overhead translates to more resources
available for computation offloading but impacts the CE accuracy and RA
flexibility. This paper establishes a basic framework for integrating the
impact of control operations in the performance evaluation of the RIS-aided MEC
paradigm, clarifying their trade-offs through theoretical analysis and
numerical simulations.
