VirtualPower: coordinated power management in virtualized enterprise systems
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Power-aware dynamic placement of HPC applications
Proceedings of the 22nd annual international conference on Supercomputing
pMapper: power and migration cost aware application placement in virtualized systems
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Profiling and modeling resource usage of virtualized applications
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Workload Analysis and Demand Prediction of Enterprise Data Center Applications
IISWC '07 Proceedings of the 2007 IEEE 10th International Symposium on Workload Characterization
Coupled placement in modern data centers
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
A cost-sensitive adaptation engine for server consolidation of multitier applications
Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
WattApp: an application aware power meter for shared data centers
Proceedings of the 7th international conference on Autonomic computing
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
A comparison of high-level full-system power models
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
Server workload analysis for power minimization using consolidation
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
BrownMap: enforcing power budget in shared data centers
Proceedings of the ACM/IFIP/USENIX 11th International Conference on Middleware
| Hi-index | 0.00 |
Data center consolidation has emerged as an important tool to improve the hardware utilization of data centers and reduce delivery costs. Consolidation has traditionally used virtualization to consolidate multiple workloads as different virtual machines running on a shared physical server. Consolidation leads to reduction in the hardware and the facilities cost (e.g., space and energy) but does not reduce software maintenance cost, which is often proportional to the number of instances of the software. The ever-increasing proportion of software cost (labour and license) in data center operations make software consolidation an important tool in data centers. In this work, we investigate the problem of data center consolidation with the goal of minimizing the total costs in running a data center. We build on existing work on virtualization-driven hardware consolidation and software consolidation to design CloudBridge that reduces total data center cost. CloudBridge uses an algorithm for finding the optimal software consolidation level for workloads consolidated on a physical server. Further, it intelligently optimizes the tradeoff between hardware and software consolidation to identify suitable workloads that should be co-located on a shared physical server. We present both theoretical and experimental evidence that establishes the effectiveness of CloudBridge.