Distributed Dynamic Speed Scaling

In recent years we have witnessed a great interest in large distributed computing platforms, also known as clouds. While these systems offer enormous computing power, they are however major energy consumers. In the existing data centers CPUs are responsible for approximately half of the energy consumed by the servers. A promising technique for saving CPU energy consumption is dynamic speed scaling, in which the speed at which the processor is ran is adjusted based on demand and performance constraints. In this paper we look at the problem of allocating the demand in the network of processors (each being capable to perform dynamic speed scaling) to minimize the global energy consumption/cost. The nonlinear dependence between the energy consumption and the performance as well as the high variability in the energy prices result in a nontrivial allocation. The problem can be abstracted as a fully distributed convex optimization with a linear constraint. On the theoretical side, we propose ...

• Type: Journal
• Year: 2010
• Where: INFOCOM
• Authors: Rade Stanojevic, Robert Shorten
• Keywords: Communications, Dynamic Speed, Energy Consumption, Energy Prices, INFOCOM 2010