Energy-Optimal Sampling of Edge-Based Feedback Systems
Author(s)
Champati, Jaya PrakashDate
2021-06Abstract
We study a problem of optimizing the sampling
interval in an edge-based feedback system, where sensor samples
are offloaded to a back-end server which process them and
generates a feedback that is fed-back to a user. Sampling the
system at maximum frequency results in the detection of events
of interest with minimum delay but incurs higher energy costs
due to the communication and processing of some redundant
samples. On the other hand, lower sampling frequency results in
a higher delay in detecting an event of interest thus increasing
the idle energy usage and degrading the quality of experience.
We propose a method to quantify this trade-off and compute the
optimal sampling interval, and use simulation to demonstrate the
energy savings.