The cost of a cloud: research problems in data center networks
ACM SIGCOMM Computer Communication Review
Cutting the electric bill for internet-scale systems
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
SHIP: Scalable Hierarchical Power Control for Large-Scale Data Centers
PACT '09 Proceedings of the 2009 18th International Conference on Parallel Architectures and Compilation Techniques
Joint optimization of idle and cooling power in data centers while maintaining response time
Proceedings of the fifteenth edition of ASPLOS on Architectural support for programming languages and operating systems
INFOCOM'10 Proceedings of the 29th conference on Information communications
GreenWare: greening cloud-scale data centers to maximize the use of renewable energy
Middleware'11 Proceedings of the 12th ACM/IFIP/USENIX international conference on Middleware
GreenWare: greening cloud-scale data centers to maximize the use of renewable energy
Proceedings of the 12th International Middleware Conference
Greening the compute cloud's pricing plans
Proceedings of the Workshop on Power-Aware Computing and Systems
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In this paper, we propose a novel electricity cost capping algorithm that not only minimizes the electricity cost of operating cloud-scale data centers, but also enforces a cost budget on the monthly electricity bill. Our solution first explicitly models the impacts of power demands on electricity prices and the power consumption of cooling and networking in the minimization of electricity cost. In the second step, if the electricity cost exceeds a desired monthly budget due to unexpectedly high workloads, our solution guarantees the quality of service for premium customers and trades off the request throughput of ordinary customers. We formulate electricity cost capping as two related constrained optimization problems and propose an efficient algorithm based on mixed integer programming. Simulation results show that our solution outperforms the state-of-the-art solutions by having lower electricity costs and achieves desired cost capping with maximized request throughput.