Abstract
In this paper, we address the problem of power-aware Virtual Machines (VMs) consolidation considering resource contention. Deployment of VMs can greatly influence host performance, especially, if they compete for resources on insufficient hardware. Performance can be drastically reduced and energy consumption increased. We focus on a bi-objective experimental evaluation of scheduling strategies for CPU and memory intensive jobs regarding the quality of service (QoS) and energy consumption objectives. We analyze energy consumption of the IBM System x3650 M4 server, with optimized performance for business-critical applications and cloud deployments built on IBM X-Architecture. We create power profiles for different types of applications and their combinations using SysBench benchmark. We evaluate algorithms with workload traces from Parallel Workloads and Grid Workload Archives and compare their non-dominated Pareto optimal solutions using set coverage and hyper volume metrics. Based on the presented case study, we show that our algorithms can provide the best energy and QoS trade-offs. © Springer International Publishing AG 2018.
Original language | English |
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Number of pages | 15 |
Volume | 796 |
DOIs | |
Publication status | Published - 2018 |
Event | 4th Latin American Conference on High Performance Computing - , Argentina Duration: 20 Sept 2017 → 22 Sept 2017 http://carla2017.ccarla.org/ |
Keywords
- Consolidation
- Energy aware scheduling
- Green cloud
- SLA violations
- Virtual machine
- Benchmarking
- Cloud computing
- Economic and social effects
- Energy utilization
- Network security
- Pareto principle
- Power management
- Quality control
- Quality of service
- Scheduling
- Virtual addresses
- Critical applications
- Energy-aware scheduling
- Experimental evaluation
- Green Clouds
- Optimized performance
- Pareto optimal solutions
- Scheduling strategies
- Green computing