How to slice the day: Optimal time quantization for energy saving in the internet backbone networks

Load adaptive energy saving (LAES) schemes have been widely considered as a solution to reduce the energy consumption in networks. In LEAS, the time is sliced into time periods according to the daily pattern of traffic loads, such as peak and off-peak traffic, and energy saving operations are typically activated during the off-peak traffic. The effectiveness of LAES depends on the number of time slices precisely. A larger number of small time slices is desirable due to a better adaptiveness to traffic fluctuations. At the same time, energy saving operations should not be too frequent, as they have impact on routing stability and operational procedures. In this paper, we study the effect of nonuniform time quantization on the efficiency of energy saving. We propose a novel time quantization algorithm and show that optimizing time quantization can considerably reduce the number of energy saving operations, while comparably saving the same energy as previously reported.