JET: Electricity cost-aware dynamic workload management in geographically distributed datacenters

The ever-increasing operational cost of geographically distributed datacenters has become a critical issue for cloud service providers. In order to cut the electricity cost of geographically distributed datacenters, several workload management schemes have been proposed, such as Electricity price-aware InteR-datacenter load balancing (EIR), which reduces the electricity cost of active servers by dispatching workload to datacenters with lower electricity prices, and Cooling-aware IntrA-datacenter load balancing (CIA), which decreases the power consumption of a datacenter by consolidating workload on servers with high cooling efficiency. However, these existing schemes could incur some undesired results. For example, EIR may result in high electricity cost of cooling systems due to random workload distribution in datacenters. CIA could lead to high electricity cost of active servers since it does not consider the variation of electricity prices. In this paper, we propose a joint interand intra-datacenter workload management scheme, Joint ElectriciTy price-aware and cooling efficiency-aware load balancing (JET), to cut the electricity cost of geographically distributed datacenters. JET uses a short processing time to calculate the optimal workload distribution, which trades off the electricity cost of active servers and cooling systems by alternately selecting the electricity prices or the efficiency of a cooling system as the dominator factor to the electricity cost of geographically distributed datacenters. Extensive evaluations show that JET outperforms the existing schemes and achieves substantial reduction on the electricity cost of geographically distributed datacenters.