Decision Support in Data Centers for Sustainability

In this paper, we propose a decision support system (DSS) for the greening of data centers to help the environment, hence promoting sustainability. As society continues the relentless shift towards electronic communications there is a growing demand for greater storage and processing on data centers. A potential area of improvement is to gain greater server utilization rates since traditionally the phenomenon of "server sprawl" occurs where more servers are added to the data center without seeking greater utilization rates on existing servers first. This implies maintaining more servers than actually needed that translates to greater carbon dioxide emissions causing potential environmental problems. Presently, average server utilization rates in most data centers are rather low, and we make the claim that utilization rates should be increased so that we can lower the number of servers for enhanced sustainability. A shift to the cloud could potentially be useful here. Some servers can be phased out with their operations being hosted on the cloud instead. We propose an approach based on data mining using CBR and decision trees to build a DSS that would help make decisions pertaining to issues such as server sprawl and migration to the cloud in order to promote data center sustainability. We provide recommendations based on our DSS that would be useful to data center operators in academia and industry.