  The weighted-workload-task-allocation (WWTA) load-balancing policy is known
to be throughput optimal for parallel server systems with heterogeneous
servers. This work concerns the heavy traffic approximation of steady-state
performance for parallel server systems operating under WWTA policy. Under a
relaxed complete-resource-pooling condition, we prove that WWTA achieves a
"strong form" of state-space collapse in heavy traffic and that the scaled
workload for each server converges in distribution to an exponential random
variable, whose parameter is explicitly given by system primitives. Various
steady-state performance measures are shown to be approximated from this
exponential random variable. Instead of proving a stochastic process limit
followed by an interchange of limits - a method that dominates the literature,
our method works directly with a pre-limit basic adjoint relationship (BAR)
that characterizes the stationary distribution of each pre-limit system.
