Wang et al., 2016
ViewPDF| Publication | Publication Date | Title |
|---|---|---|
| Buyya et al. | Energy‐efficiency and sustainability in new generation cloud computing: a vision and directions for integrated management of data centre resources and workloads | |
| Wang et al. | Increasing large-scale data center capacity by statistical power control | |
| Askarizade Haghighi et al. | An energy-efficient dynamic resource management approach based on clustering and meta-heuristic algorithms in cloud computing IaaS platforms: Energy efficient dynamic cloud resource management | |
| Lo et al. | Heracles: Improving resource efficiency at scale | |
| Guenter et al. | Managing cost, performance, and reliability tradeoffs for energy-aware server provisioning | |
| Goudarzi et al. | SLA-based optimization of power and migration cost in cloud computing | |
| Gandhi et al. | Autoscale: Dynamic, robust capacity management for multi-tier data centers | |
| Moreno et al. | Customer-aware resource overallocation to improve energy efficiency in realtime cloud computing data centers | |
| Deng et al. | Reliability‐aware server consolidation for balancing energy‐lifetime tradeoff in virtualized cloud datacenters | |
| Sakamoto et al. | Production hardware overprovisioning: Real-world performance optimization using an extensible power-aware resource management framework | |
| Udayasankaran et al. | Energy efficient resource utilization and load balancing in virtual machines using prediction algorithms | |
| Al-Dulaimy et al. | Power management in virtualized data centers: state of the art | |
| Jin et al. | Energy-efficient task scheduling for CPU-intensive streaming jobs on Hadoop | |
| Kulshrestha et al. | An efficient host overload detection algorithm for cloud data center based on exponential weighted moving average | |
| Islam et al. | Distributed temperature-aware resource management in virtualized data center | |
| Ruan et al. | Performance-to-power ratio aware virtual machine (VM) allocation in energy-efficient clouds | |
| Zakarya | Energy and performance aware resource management in heterogeneous cloud datacenters | |
| Zhou et al. | An experience-based scheme for energy-SLA balance in cloud data centers | |
| Zhang et al. | Trapped capacity: Scheduling under a power cap to maximize machine-room throughput | |
| Pore et al. | Techniques to achieve energy proportionality in data centers: A survey | |
| Choi et al. | Task Classification Based Energy‐Aware Consolidation in Clouds | |
| Lent | Analysis of an energy proportional data center | |
| Arroba et al. | Heuristics and metaheuristics for dynamic management of computing and cooling energy in cloud data centers | |
| Kaushar et al. | Comparison of SLA based energy efficient dynamic virtual machine consolidation algorithms | |
| Li et al. | Negotiation-based resource provisioning and task scheduling algorithm for cloud systems |