A Scalable WSN Based Data Center Monitoring Solution with Probabilistic Event Prediction

Abstract

The two most important objectives of the data center operators are to reduce operating cost and minimize carbon emission. Consolidation of data centers is not always possible and big enterprise end up having data centers in multiple locations across different cities and countries. In such a diverse deployment manual monitoring is not a cost effective solution. ASHRAE [1] suggested considering the energy efficiency as key factor in data center design. Our initial experiments reveal that a reduction in one degree Celsius of data center room temperature results in 4% excess consumption of electricity. We developed a WSN based data center monitoring (DCM) solution which includes the hardware system and an enterprise application. We deployed the hardware system in hundreds of location at 7 different cities and monitored them from a central enterprise application dashboard. In this paper, we describe the system architecture and analyzed data that was captured for nine months. This is one of the largest real life WSN deployment and based on the result we argue that the manual monitoring cost of data centers is reduced by 80%. This deployment also helped in avoiding a significant amount of carbon emission. DCM also provides a mechanism to predict events in real time.

DOI: 10.1109/AINA.2012.94

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Cite this paper

@article{Vuppala2012ASW, title={A Scalable WSN Based Data Center Monitoring Solution with Probabilistic Event Prediction}, author={Sunil Kumar Vuppala and Animikh Ghosh and Ketan A. Patil and Kumar Padmanabh}, journal={2012 IEEE 26th International Conference on Advanced Information Networking and Applications}, year={2012}, pages={446-453} }