Optimizing cost and performance for multihoming
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
A Distributed Throttling Approach for Handling High Bandwidth Aggregates
IEEE Transactions on Parallel and Distributed Systems
Cloud control with distributed rate limiting
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Speed scaling for weighted flow time
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
ECHOS: edge capacity hosting overlays of nano data centers
ACM SIGCOMM Computer Communication Review
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
Reducing network energy consumption via sleeping and rate-adaptation
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Energy-aware server provisioning and load dispatching for connection-intensive internet services
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
A case for adapting channel width in wireless networks
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Fully Distributed Algorithms for Convex Optimization Problems
DISC '07 Proceedings of the 21st international symposium on Distributed Computing
The cost of a cloud: research problems in data center networks
ACM SIGCOMM Computer Communication Review
Optimal power allocation in server farms
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Energy aware consolidation for cloud computing
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
Energy-Efficient algorithms for flow time minimization
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Greening geographical load balancing
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Minimizing energy cost for internet-scale datacenters with dynamic traffic
Proceedings of the Nineteenth International Workshop on Quality of Service
Greening geographical load balancing
ACM SIGMETRICS Performance Evaluation Review - Performance evaluation review
Server selection for carbon emission control
Proceedings of the 2nd ACM SIGCOMM workshop on Green networking
Dynamic provisioning in next-generation data centers with on-site power production
Proceedings of the fourth international conference on Future energy systems
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In recent years we have witnessed a great interest in large distributed computing platforms, also known as clouds. While these systems offer enormous computing power, they are major energy consumers. In existing data centers CPUs are responsible for approximately half of the energy consumed by the servers. A promising technique for saving CPU energy consumption is dynamic speed scaling, in which the speed at which the processor is run is adjusted based on demand and performance constraints. In this paper we look at the problem of allocating the demand in the network of processors (each being capable to perform dynamic speed scaling) to minimize the global energy consumption/cost subject to a performance constraint. The nonlinear dependence between the energy consumption and the performance as well as the high variability in the energy prices result in a nontrivial resource allocation. The problem can be abstracted as a fully distributed convex optimization with a linear constraint. On the theoretical side, we propose two low-overhead fully decentralized algorithms for solving the problem of interest and provide closed-form conditions that ensure stability of the algorithms. Then we evaluate the efficacy of the optimal solution using simulations driven by the real-world energy prices. Our findings indicate a possible cost reduction of 10-40% compared to power-oblivious 1/N load balancing, for a wide range of load factors.