Our analysis of the electricity intensity of networks came out in printed form in August 2018, now with a full reference

In September 2017 I posted on our analysis of the trends in the electricity intensity of network data flows, which was placed online in August 2017. The journal finally put the article in a printed edition in August 2018 and I wanted to re-up this post (with minor updates) to reflect the actual pub date and the complete reference (see below).

Our previous work on trends in the efficiency of computing showed that computations per kWh at peak output doubled every 1.6 years from the mid 1940s to around the year 2000, then slowed to a doubling time of 2.6 years after 2000 (Koomey et al. 2011, Koomey and Naffziger 2016).   These analyses examined discrete computing devices, and showed the effect (mainly) of progress in hardware.

The slowing in growth of peak output efficiency after 2000 was the result of the end of the voltage reductions inherent in Dennard scaling, which the chip manufacturers used to keep power use down as clock rates increased (Bohr 2007, Dennard et al. 1974) until about that time. When voltages couldn’t be lowered any more, they turned to other tricks (like multiple cores) but they still couldn’t continue improving performance and efficiency at the historical rate, because of the underlying physics.

Unlike that for computing devices, the literature on the electricity intensity and efficiency of network data flows has been rife with inconsistent comparisons, unjustified assumptions, and a general lack of transparency.  Our attempt to remedy these failings was just published in the Journal of Industrial Ecology in August 2018 (Aslan et al. 2018).  The focus is on the electricity intensity of data transfers over the core network and the access networks (like DSL and cable).

Here’s the summary of the article:

In order to understand the electricity use of Internet services, it is important to have accurate estimates for the average electricity intensity of transmitting data through the Internet (measured as kilowatt-hours per gigabyte [kWh/GB]). This study identifies representative estimates for the average electricity intensity of fixed-line Internet transmission networks over time and suggests criteria for making accurate estimates in the future. Differences in system boundary, assumptions used, and year to which the data apply significantly affect such estimates. Surprisingly, methodology used is not a major source of error, as has been suggested in the past. This article derives criteria to identify accurate estimates over time and provides a new estimate of 0.06 kWh/GB for 2015. By retroactively applying our criteria to existing studies, we were able to determine that the electricity intensity of data transmission (core and fixed-line access networks) has decreased by half approximately every 2 years since 2000 (for developed countries), a rate of change comparable to that found in the efficiency of computing more generally.

The rate of improvement is actually faster than in computing devices, but this result shouldn’t be surprising, because the aggregate rates of improvement in data transfer speeds and total data transferred are dependent on progress in both hardware and software.   Koomey and Naffziger (2016) and Koomey (2015) showed that other metrics for efficiency can improve more rapidly than peak output efficiency if the right tools are brought to bear on those problems.

Email me if you’d like a copy of the article, or any of the others listed below.

References

Aslan, Joshua, Kieren Mayers, Jonathan G Koomey, and Chris France. 2018. “Electricity Intensity of Internet Data Transmission: Untangling the Estimates.” The Journal of Industrial Ecology. vol. 22, no. 4. August. pp. 785-798. [https://doi.org/10.1111/jiec.12630]

Bohr, Mark. 2007. “A 30 Year Retrospective on Dennard’s MOSFET Scaling Paper.”  IEEE SSCS Newsletter.  vol. 12, no. 1. Winter. pp. 11-13.

Dennard, Robert H., Fritz H. Gaensslen, Hwa-Nien Yu, V. Leo Rideout, Ernest Bassous, and Andre R. Leblanc. 1974. “Design of Ion-Implanted MOSFET’s with Very Small Physical Dimensions.”  IEEE Journal of Solid State Circuits.  vol. SC-9, no. 5. October. pp. 256-268.

Koomey, Jonathan G., Stephen Berard, Marla Sanchez, and Henry Wong. 2011. “Implications of Historical Trends in The Electrical Efficiency of Computing”.  IEEE Annals of the History of Computing.  vol. 33, no. 3. July-September. pp. 46-54. [http://doi.ieeecomputersociety.org/10.1109/MAHC.2010.28]

Koomey, Jonathan. 2015. “A primer on the energy efficiency of computing.”  In Physics of Sustainable Energy III:  Using Energy Efficiently and Producing it Renewably (Proceedings from a Conference Held March 8-9, 2014 in Berkeley, CA). Edited by R. H. Knapp Jr., B. G. Levi and D. M. Kammen. Melville, NY: American Institute of Physics (AIP Proceedings). pp. 82-89.

Koomey, Jonathan, and Samuel Naffziger. 2016. “Energy efficiency of computing:  What’s next?” In Electronic Design. November 28. [http://electronicdesign.com/microprocessors/energy-efficiency-computing-what-s-next]


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Koomey researches, writes, and lectures about climate solutions, critical thinking skills, and the environmental effects of information technology.

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