Decentralized capacity reallocation for a loss network

Stochastic loss network models have been widely used to study the characteristics of a large class of resource constrained networks in terms of their blocking probability. We consider a distributed capacity allocation problem for a loss network with directed edges. Each infrastructure node (or superpeer) can independently adjust its link-capacity allocations, subject to a constraint on the total amount for each node, so as to minimize its estimate of call blocking rates. We argue via Erlang fixed-point approximation that such decentralized local changes do work to minimize a global measure of weighted call blocking rates.