This paper proposes a traffic-driven optical IP networking architecture for service provider networks. Its design is derived from the optical GMPLS architecture, which provides high performance but is not scalable since both optical paths and IP routes need to be arranged in a mesh topology. To improve scalability, we first modified the configuration so that paths and routes can be arranged in a tree topology. However, this approach may degrade performance due to traffic concentration at each tree's root. To prevent such performance degradation, we further modified the architecture so that both cut-through optical paths and cut-through IP routes can be assigned reactively, according to traffic demand, and these can work together in cooperation. As a result, our architecture achieves both high performance and scalability, in that the whole network performance can be maintained without a massive increase in the number of optical paths and IP routes, even if the number of customer networks grows.

In this paper, we propose a workload assignment policy for reducing power consumption by air conditioners in data centers. In the proposed policy, to reduce the air conditioner power consumption by raising the temperature set points of the air conditioners, the temperatures of all server back-planes are equalized by moving workload from the servers with the highest temperatures to the servers with the lowest temperatures. To evaluate the proposed policy, we use a computational fluid dynamics simulator for obtaining airflow and air temperature in data centers, and an air conditioner model based on experimental results from actual data center. Through evaluation, we show that the air conditioners' power consumption is reduced by 10.4% in a conventional data center. In addition, in a tandem data center proposed in our research group, the air conditioners' power consumption is reduced by 53%, and the total power consumption of the whole data center is exhibited to be reduced by 23% by reusing the exhaust heat from the servers.