A futures market in computer time
Communications of the ACM
Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Managing server energy and operational costs in hosting centers
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Combinatorial Auctions
A comparison between mechanisms for sequential compute resource auctions
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A taxonomy of market-based resource management systems for utility-driven cluster computing
Software—Practice & Experience
Achieving Self-Management via Utility Functions
IEEE Internet Computing
T-Alloc: A practical energy efficient resource allocation algorithm for traditional data centers
Future Generation Computer Systems
Proactive dynamic resource management in virtualized data centers
Proceedings of the 2nd International Conference on Energy-Efficient Computing and Networking
Market mechanisms for managing datacenters with heterogeneous microarchitectures
ACM Transactions on Computer Systems (TOCS)
REF: resource elasticity fairness with sharing incentives for multiprocessors
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
Price theory based power management for heterogeneous multi-cores
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
| Hi-index | 0.00 |
As data-center energy consumption continues to rise, efficient power management is becoming increasingly important. In this work, we examine the use of a novel market mechanism for finding the right balance between power and performance. The market enables a separation between a 'buyer side' that strives to maximize performance and a 'seller side' that strives to minimize power and other costs. A concise and scalable description language is defined for agent preferences that admits a mixedinteger program for computing optimal allocations. Experimental results demonstrate the robustness, flexibility, practicality and scalability of the architecture.