Cooling-Efficient Job Scheduling in a Heterogeneous Grid Environment

Electricity consumption typically forms the biggest portion of a Data Centre's operational cost, with the biggest consumers, in roughly equal proportion, being the servers and the cooling units. In an effort to reduce electricity consumption, in this paper, we propose a grid scheduling algorithm that takes advantage of a prior Gas-District Cooling Data Centre model to reduce the cooling energy consumption. The scheduling algorithm is an extension of a prior version that has been shown to perform with competitive average turnaround time, waiting time and maximum tardiness in heterogeneous grid environments. Experimental analysis shows that the proposed method was able to reduce cooling electricity consumption by 20%. Further, by increasing the maximum allowable temperature by 1 degree, the proposed method was able to save an additional 3%. (C) 2015 The Authors. Published by Elsevier B.V.