Stabilization of an overloaded queueing network using measurement-based admission control

TL;DR

This paper investigates how measurement-based admission control affects the stability of overloaded queueing networks, highlighting the impact of imperfect information and feedback signaling on system performance.

Contribution

It characterizes the stability region of a queueing network under measurement-based admission control with imperfect information and analyzes the sensitivity to feedback parameters.

Findings

Measurement-based admission control can stabilize overloaded networks.

Imperfect measurements significantly influence stability regions.

Feedback signaling increases system sensitivity to parameter variations.

Abstract

Admission control can be employed to avoid congestion in queueing networks subject to overload. In distributed networks the admission decisions are often based on imperfect measurements on the network state. This paper studies how the lack of complete state information affects the system performance by considering a simple network model for distributed admission control. The stability region of the network is characterized and it is shown how feedback signaling makes the system very sensitive to its parameters.