Energy Efficient Ethernet was a recent development in the field of computer networks which aims at minimizing the use of energy over networks. The idea for saving energy in communication systems was proposed as early as 2003 and its implementation in Ethernet links was officially made as a standard by IEEE 802.3az task force. It is estimated that the internet core is consuming about 6 TWh power each year and it keeps growing. One of the major power consumption is in Ethernet links. Since links can be physically long significant power would be needed to transmit information through the wires. IEEE standard defines a low power mode for idle links and thereby encourages saving energy.
EEE concept is described in figure (1) as seen in the Reviriego et al. 2009. The link is made active when a packet arrives and when no packets are left link enters into a low power mode. Periodically link is made active for a short time to make sure that it is working. This is denoted as a refresh cycle in the figure. Table (1) shows the proposed mean sleep time, wake-up time from Reviriego et al 2009.
Simulation of EEE was done using the CSIM. CSIM is a simulation library from Mesquisite software. It provides the facility for simulating queues. It is believed that the arrival of packets in Ethernet networks follows an exponential distribution and therefore EEE can be simulated as a Poisson process. Coincidentally packet arrivals and leaving on Ethernet links can be modeled as an M/M/1 queue. Service center would be link and queue will be packets arrived on the link. The simulation was done with 5000 packets each for 100Mbps, 1Gbps, and 10 Gbps. Energy consumption for the link was calculated using the following known formula.
Plow power is the power consumed in low power mode and Pactive is the power consumed when the link is active. The load was increased from 0 to 100 at intervals of 5. It is assumed that both forward and backward packet transfer between the links are independent of each other. I also neglected refresh cycle since it has little effect on performance. Further bulk arrivals were simulated using geometric distribution with their means equivalent to the desired burst length. In this experiment, I used mean burst lengths of 2, 5 and 10 to find its effect on power consumption. Finally, I did experiments on real-world packet traces collected from a personal computer. Trace files used in this experiment were collected from a 100 Mbps Ethernet link. Trace files were collected when the user did a typical browsing, downloading and surfing on the internet.
Results of the simulation on the regular EEE model is plotted in the graphs shown in figures (2), (3) and (5).
Results for the simulation on regular EEE was as expected. For burst arrivals, we notice that the performance is improved when the burst length is increased. Table II shows results for real-world packet trace analysis.
Graphs for regular EEE at various loads show that performance is as expected. Energy consumption is proportional to the traffic of the packets as inferred from results. In 100Mbps, results are close to proportional (ideal) case. However, in 1Gbps and 10 Gbps links, results are not good especially when traffic is high. It appears that the link is spending more time sleeping and waking up at higher traffic.
When packets appear as burst, performance is improved as expected. This is because the link is made to wake up and sleep only for whole burst packet length. More the burst arrivals, more the performance getting close to the ideal case.
For real-world data, power consumption in EEE looks very low when compared to that of normal Ethernet. This might be because packet arrival rate in the real world is higher than that of in simulation models and hence link is in sleep most of the time.
However, before making any judgments it is better to analyze the proposed model using simulation.
Experiments were conducted for the proposed enhancement method using CSIM Software. When each packet is leaving the system we check if the queue is empty. If the queue is empty we next verify that the mean delay for past packet arrivals is less than sleep time. If that is the case then we continue without sleeping, otherwise, we would sleep. If a packet arrives before the predicted mean delay we gain a power loss for the time equivalent to the difference between sleep time and mean packet delay time. If a packet did not arrive before the predicted mean delay time we incur the penalty described above.
The result of the proposed simulation model is shown in figure (8), (9) & (10).
The simulation results of the proposed model show that it could improve the performance without losing any packets. It also shows that the proposed method would work better for 100Mbps. The graph gets skewed toward the ideal case. Notice that a slight variation could produce increased cost benefits, and therefore this method looks better than the original proposal theoretically. There is no packet loss in this suggested improvement.
In this post we reproduced the results of EEE simulation. We found that when burst arrivals are high performance in EEE is enhanced. It is also noteworthy that given the round trip time on typical internet servers are in milliseconds, the small delay in terms of micro seconds in the Ethernet links is negligible when compared with the significant economic benefit. We also proposed a method to improve the performance of EEE without packet loss. However we need more testing of the proposed system using real data before assuring its enhanced performance.