Load balancing vs. distributed rate limiting: an unifying framework for cloud control

With the expansion of cloud-based services, the question as to how to control usage of such large distributed systems has become increasingly important. Load balancing (LB), and recently proposed distributed rate limiting (DRL) have been used independently to reduce costs and to fairly allocate distributed resources. In this paper we propose a new mechanism for cloud control that unifies the use of LB and DRL: LB is used to minimize the associated costs and DRL makes sure that the resource allocation is fair. From an analytical standpoint, modelling the dynamics of DRL in dynamic workloads (resulting from LB cost-minimization scheme) is a challenging problem. Our theoretical analysis yields a condition that ensures convergence to the desired working regime. Analytical results are then validated empirically through several illustrative simulations. The closed- form nature of our result also allows simple design rules which, together with extremely low computational and communication overhead, makes the presented algorithm practical and easy to deploy