Data networks
The Power of Two Choices in Randomized Load Balancing
IEEE Transactions on Parallel and Distributed Systems
Globally Distributed Content Delivery
IEEE Internet Computing
Cloud control with distributed rate limiting
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Decentralized detection of global threshold crossings using aggregation trees
Computer Networks: The International Journal of Computer and Telecommunications Networking
Fully decentralized emulation of best-effort and processor sharing queues
SIGMETRICS '08 Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Control Techniques for Complex Networks
Control Techniques for Complex Networks
Designing a predictable internet backbone with valiant load-balancing
IWQoS'05 Proceedings of the 13th international conference on Quality of Service
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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.