QoS-Aware Task Placement in Geo-distributed Data Centers with Low OPEX Using Dynamic Frequency Scaling

With the rising demands on cloud services, the electricity consumption has been increasing drastically as the main operational expenditure (OPEX) to data center providers. The geographical heterogeneity of electricity prices motivates us to study the task placement problem over geo-distributed data centers. We exploit the dynamic frequency scaling technique and formulate an optimization problem that inimizes OPEX while guaranteeing the quality-of-service, i.e., the expected response time of tasks. The experimental results show that our proposal achieves much higher cost-efficiency than the traditional resizing scheme, i.e., by activating/deactivating certain servers in data centers.