Name
Abstract | ||
|---|---|---|
We formulate optimization problems to study how data centers might modulate their power demands for cost-effective operation taking into account various complexities exhibited by real-world electricity pricing schemes. For computational tractability reasons, we work with a fluid model for power demands which we imagine can be modulated using two abstract knobs of demand dropping and demand delaying (each with its associated penalties or costs). We consider both stochastically known and completely unknown inputs, which are likely to capture different data center scenarios. Using empirical evaluation with both real-world and synthetic power demands and real-world prices, we demonstrate the efficacy of our techniques. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/UCC.2013.52 | UCC |
Keywords | Field | DocType |
optimisation,power aware computing,computer centres,data center power cost,associated penalty,real-world electricity pricing scheme,power demand,abstract knob,fluid model,cost-effective operation,data center,real-world price,computational tractability,real-world prices,real-world power demands,workload modulation,demand dropping,data centers,real-world electricity pricing schemes,power cost optimization,synthetic power demand,optimization problems,demand delaying,power demands modulation,different data center scenario,synthetic power demands,power markets,account various complexity,pricing,demand side management | Mathematical optimization,Computer science,Electricity,Simulation,Workload,Modulation,Dynamic demand,Prediction algorithms,Data center,Optimization problem,Electricity pricing | Conference |
Citations | PageRank | References |
8 | 0.53 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Wang | 1 | 8 | 1.88 |
| Bhuvan Urgaonkar | 2 | 2309 | 158.10 |
| Qian Wang | 3 | 84 | 27.81 |
| George Kesidis | 4 | 293 | 38.77 |
| Anand Sivasubramaniam | 5 | 4485 | 291.86 |