Modeling and understanding burst transmission algorithms for energy efficient ethernet

Recently, the energy consumption of Ethernet has become one of the hottest topics focused by both academic committee and industry, especially with the increase of the link speed from 1Gbps to 10Gbps nowadays or even 40/100/200Gbps in the near future. To save the energy consumed by the Ethernet, the Energy Efficient Ethernet (EEE) is developed and standardized by the IEEE 802.3az work group. When there is no incoming traffic, the EEE can saves 90 % of its energy consumption by entering into the Low Power Idle (LPI) mode. To maximize the energy saving of Ethernet, the Burst TRansmission (BTR) algorithm, which defines a new way to utilize the LPI mode, is developed as a policy for EEE. Prior work theoretically shows that the BTR algorithm makes a tradeoff between the energy saving and the queuing delay. However, the traffic pattern, on which the performance of EEE greatly depends, is assumed to be deterministic in their analyses. Besides, their models made estimation for many situations. In this paper, assuming that the arrival time of packets can be modeled by Poisson process, we build Markov model for EEE with the BTR algorithm and provide analytical understanding on the BTR algorithm. We propose two actual models: one focuses on the buffer size limit, the other concentrates on tolerable packet delay additionally. We draw some guidelines of parameter selection and policy design for EEE from combination of theory conclusions and simulation results. The results show that the saved energy can be constrained by link occupancy even though the buffer size is variational. The other policy buffer full triggered wake-up can achieve ideal ratio of energy consumption and arrival rate within the scope of the buffer as well. However, the tolerable delay can not be guaranteed by any policies. The buffer size is even fixed, which affects the flexibility of demanded delay for different business. The policy considering tolerable delay is supposed to be a little better than the other- policy, with a little more complicated design. Thus we design an adaptive policy: detect the load utilization, apply the buffer full triggered wake-up policy for higher load utilization link, while applying the buffer full and timeout triggered wakeup policy for the delay sensitive business and tiny arrival rate.