  We consider the problem of simultaneous scheduling and resource allocation of
an incoming flow of requests to a set of computing units. By representing each
computing unit as a node, we model the overall system as a multi-queue scheme.
Inspired by congestion control approaches in communication networks, we propose
an AIMD-like (additive increase multiplicative decrease) admission control
policy that is stable irrespective of the total number of nodes and AIMD
parameters. The admission policy allows us to establish an event-driven
discrete model, triggered by a locally identifiable enabling condition.
Subsequently, we propose a decentralized resource allocation strategy via a
simple nonlinear state feedback controller, guaranteeing global convergence to
a bounded set in finite time. Last, we reveal the connection of these
properties with Quality of Service specifications, by calculating local queuing
time via a simple formula consistent with Little's Law.
