Decay of tails at equilibrium for FIFO join the shortest queue networks
Maury Bramson, Yi Lu, Balaji Prabhakar

TL;DR
This paper analyzes the tail behavior of queue sizes in join the shortest queue networks with FIFO discipline and power-law service times, revealing a phase transition between exponential, power-law, and doubly exponential decay depending on the service time tail exponent.
Contribution
It extends the understanding of tail decay in join the shortest queue networks to nonexponential service times with power-law distributions, identifying different regimes of tail behavior.
Findings
Tail is doubly exponential if /(D-1)
Tail exhibits power law if /(D-1)
Tail is exponential at the critical exponent /(D-1)
Abstract
In join the shortest queue networks, incoming jobs are assigned to the shortest queue from among a randomly chosen subset of queues, in a system of queues; after completion of service at its queue, a job leaves the network. We also assume that jobs arrive into the system according to a rate- Poisson process, , with rate-1 service at each queue. When the service at queues is exponentially distributed, it was shown in Vvedenskaya et al. [Probl. Inf. Transm. 32 (1996) 15-29] that the tail of the equilibrium queue size decays doubly exponentially in the limit as . This is a substantial improvement over the case D=1, where the queue size decays exponentially. The reasoning in [Probl. Inf. Transm. 32 (1996) 15-29] does not easily generalize to jobs with nonexponential service time distributions. A modularized program for treating general service…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
