PROJECT TITLE :
Towards Optimal Electric Demand Management for Internet Data Centers
Electricity cost is becoming a major portion of Internet data center (IDC)'s operation cost and large-scale IDCs are becoming important consumers of regional electricity markets. IDC's energy efficiency is gaining more attention by data center operators and electricity market operators. Effective IDC electric demand management solutions are eagerly sought by all stakeholders. In this paper, a mixed-integer programming model based IDC electric demand management solution is proposed, which integrates both the impacts of locational marginal electricity prices and power management capability of IDC itself. Dynamic voltage/frequency scaling of individual server, cluster server ON/OFF scheduling, and dynamic workload dispatching are optimized while complying with all the IDC system-wide and individual heterogeneous servers' operation constraints according to the IDC applications' temporal variant workload. Reduced electricity cost can be achieved together with guaranteed QoS requirement and reliability consideration by using the proposed model. World Cup '98 data is utilized to evaluate the effectiveness of the proposed solution. According to the experimental evaluation, electricity cost could be cut by more than 20% in a peak workload period and by more than 80% in a light workload period. Besides, more than 6% electricity cost could be cut by considering the impact of electricity price difference. Experimental results also reveal that higher QoS requirement and reliability consideration could result in higher electricity cost.
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