Modelling multi-cell edge video analytics

TL;DR

This paper develops a mathematical framework for modeling multi-cell edge video analytics, accounting for fading and interference, and evaluates system performance metrics like coverage, capacity, and delay.

Contribution

It introduces the first comprehensive mathematical model for edge video analytics in multi-cell cellular networks, considering fading and interference effects.

Findings

Derived expressions for coverage probability and ergodic capacity.

Analyzed the impact of system parameters on detection accuracy and fairness.

Evaluated the probability of completing video analytics within delay constraints.

Abstract

Edge intelligence is a scalable solution for analyzing distributed data, but it cannot provide reliable services in large-scale cellular networks unless the inherent aspects of fading and interference are also taken into consideration. In this paper, we present the first mathematical framework for modelling edge video analytics in multi-cell cellular systems. We derive the expressions for the coverage probability, the ergodic capacity, the probability of successfully completing the video analytics within a target delay requirement, and the effective frame rate. We also analyze the effect of the system parameters on the accuracy of the detection algorithm, the supported frame rate at the edge server, and the system fairness.