  We propose an asynchronous iterative scheme which allows a set of
interconnected nodes to distributively reach an agreement to within a
pre-specified bound in a finite number of steps. While this scheme could be
adopted in a wide variety of applications, we discuss it within the context of
task scheduling for data centers. In this context, the algorithm is guaranteed
to approximately converge to the optimal scheduling plan, given the available
resources, in a finite number of steps. Furthermore, being asynchronous, the
proposed scheme is able to take in account the uncertainty that can be
introduced from straggler nodes or communication issues in the form of latency
variability while still converging to the target objective. In addition, by
using extensive empirical evaluation through simulations we show that the
proposed method exhibits state-of-the-art performance.
