Data center energy efficient resource scheduling

作者：Shuja Junaid; Bilal Kashif; Madani Sajjad Ahmad; Khan Samee U^*

来源：Cluster Computing, 2014, 17(4): 1265-1277.

DOI：10.1007/s10586-014-0365-0

• Energy efficiency
• Data centers
• Resource scheduling
• Cloud computing
• Data intensive workloads

The information and communication technology (ICT) sector has grown exponentially in the recent years. An essential component of the ICT organizations is constituted by the data centers that are densely populated with redundant servers and communicational links to ensure the provision of 99.99 % availability of services; a fact responsible for the heavy energy consumption by data centers. For energy economy, the redundant elements can be powered off based on the current workload within the data center. We propose a Data Center-wide Energy-Efficient Resource Scheduling framework (DCEERS) that schedules data center resources according to the current workload of the data center. Minimum subset of resources to service the current workload are calculated by solving the Minimum Cost Multi Commodity Flow (MCMCF) using the Benders decomposition algorithm. The Benders decomposition algorithm is scalable: it solves the MCMCF problem in linear time for large data center environments. Our simulated results depict that DCEERS achieves better energy efficiency than the previous data center resource scheduling methodologies.

• 出版日期2014-12