[Make-wifi-fast] Re: [Codel] Re: [Bloat] Re: [Rpm] Re: Re: [Cake] "Fi-Wi is a new forwarding plane for wireless" - Bob McMahon

[bob.mcmahon@umbernetworks.com]

> 
> I believe you've just described a load-dependent queuing center. I 
> don't /personally/ know what to do to mitigate them, but the 
> queuing-networks mathies do.
> 
Dave,

Queuing theory describes the symptom, but MCS selection is a 
feedback-control problem.

Every AP is running a hidden controller with a small local state vector. 
When loss occurs, that controller cannot reliably distinguish weak 
signal, hidden-node collision, OBSS interference, aggregation cost, or 
airtime overload. Those are different failure modes, but they can 
collapse to the same local observation: retries, missed ACKs, and 
degraded service time.

The wrong control action can make the system worse. Lowering MCS may be 
correct for weak signal, but it is harmful when the real problem is 
hidden-node collision or airtime saturation. Lower MCS increases airtime 
occupancy, longer airtime increases collision exposure, and more 
collisions drive more retries and more fallback. That is an unstable 
discrete-time control loop: a pole near or outside the unit circle in 
the z-plane.

There are also two different control objectives. A capacity-optimized 
controller maximizes delivered bits per second over an averaging window. 
A latency-optimized controller minimizes service-time variance and tail 
delay under load. Those optima are not the same. Larger aggregates, 
aggressive MCS selection, and retry persistence can improve average 
throughput while worsening tail latency. The AP firmware may be doing 
exactly what it was designed to do, but it is optimizing the wrong cost 
function for user experience.

So yes, there is a load-dependent service center, but the service 
function is being created by an opaque feedback controller inside the 
AP. Queueing math can characterize the result. Control theory explains 
why the service center becomes unstable.

Fi-Wi changes the control problem by increasing observability and 
changing the objective function. The concentrator has a richer state 
vector: per-STA PHY state, per-RRH receive visibility, retry 
probability, SINR, service-time history, aggregation cost, and WAN/WLAN 
congestion state. That lets the controller distinguish the cause of 
service-time variance before choosing the control action.

An autonomous AP cannot expand its state vector or change the 
building-wide cost function without a fronthaul. The observability 
constraint is architectural.

Bob