TimeNET: a toolkit for evaluating non-Markovian stochastic Petri nets
Performance Evaluation - Special issue: performance modeling tools
Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
A Feasibility Study for Power Management in LAN Switches
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
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
Queue - Multiprocessors
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
Computer Architecture Techniques for Power-Efficiency
Computer Architecture Techniques for Power-Efficiency
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
PowerNap: eliminating server idle power
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
Optimality, fairness, and robustness in speed scaling designs
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Performance Evaluation
Optimality analysis of energy-performance trade-off for server farm management
Performance Evaluation
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
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Server farms are playing an important role in the Internet infrastructure today. However, the increasing power consumption of server farms makes them expensive to operate. Thus, how to reduce the power consumed by server farms has become a important research topic. Power can be thought as a resource of system, just like traditional resources, and we can manage power via improved resource management strategies. In recent studies on power management, the system is attached with multiple states of different power consumption, and by switching among these states, power consumption can be made proportional to the work load. As different job scheduling policies will result in different performance and power consumption, an optimized policy with power as a factor can achieve a better tradeoff between performance and power consumption. In this paper, we summarize some familiar power management policies and propose a novel model using Stochastic Reward Nets(SRN). Based on this model, we analyze the performance and power consumption of different power management policies, and propose a novel cost-aware job scheduling algorithm.