process entirely. They use a system
called “proof-of-stake.” These cryptocurrencies, which include DASH and
PIVX, don’t use Po W at all since it consumes too much energy, says Malone.
Instead, users lock up quantities of
cryptocurrency for periods of time,
which secures the blockchain used by
that currency. In return, they receive
cryptocurrency rewards, as if they had
mined cryptocurrency themselves.
The result is, potentially, a middle
path: cryptocurrency projects can still
incentivize people to secure their networks, without requiring the energy
needs of a small country to do so.
Is Bitcoin Mining Profitable in 2018?,
99Bitcoins, Jan. 2, 2018,
Bitcoin Energy Consumption Index,
The Hard Math Behind Bitcoin’s
Global Warming Problem,
WIRED, Dec. 15, 2017,
Sompolinsky, Y. and Zohar, A.
Bitcoin’s Underlying Incentives
Communications, March 2018
Logan Kugler is a freelance technology writer based in
Tampa, FL. He has written for over 60 major publications.
© 2018 ACM 0001-0782/18/7 $15.00
These systems may circumvent
the energy consumption concerns
that arise with bitcoin, but may offer
something fundamentally different
from the value propositions of existing Po W cryptos.
Though cryptos like Ethereum
use PoW, says Bonneau, some people
might argue for it being a greener option, since Ethereum mining is typically performed on general-purpose
graphics processing units (GPUs) that
you can find in everyday computers.
These are, theoretically, “greener because the hardware could be repurposed for other things if the currency
dies out,” Bonneau says. Bitcoin mining’s specialized ASICs, on the other
hand, would have zero practical value
if bitcoin disappeared tomorrow.
Yet the real problem is the mining
process itself, no matter how green
it gets. Bitcoin and other PoW mining schemes are incentivized to consume energy.
“Bitcoin is currently valuable, so
people want to earn bitcoins,” says
Malone. Miners use their computing power to add blocks of transaction data to the bitcoin blockchain;
miners that do so are rewarded with
“The way to earn bitcoins is to take
part in adding blocks to the block-
chain, as the bitcoin designers decided
to reward this activity to incentivize
people to maintain the blockchain,”
He explains that cryptocurrency
mining is “difficult by design to ensure
that blocks are found at a certain rate,
and money is created at a certain rate.
If you designed a new chip that was
twice as efficient, the puzzles would
simply become twice as hard and there
would be no benefit.”
Mining, at the end of the day, is the
work that ends up consuming most of
the energy on any given crypto network.
In the case of bitcoin, says Bonneau,
No matter how
the energy costs are related “almost en-
tirely to mining; that is, to solving com-
putational puzzles. There are other
energy costs of the system, like main-
taining the system history, broadcast-
ing and verifying new transactions, but
those energy costs are trivial compared
to the mining.”
Some cryptocurrency developers
have tried to circumvent the mining
green the mining
based on proof-
are incentivized to
WITH REAL-TIME DATA
“My career has
on the problem
of parallel and
Regents Professor at the
School of Computational
Science & Engineering of the
Georgia Institute of
Technology (Georgia Tech).
Fujimoto earned his
master’s degree and doctorate
in Computer Science and
Electrical Engineering from
the University of California,
Berkeley. He received two
separate bachelor degrees,
one in computer science, the
other in computer engineering,
from the University of Illinois,
His Ph. D. training began
with an emphasis on computer
hardware and architecture.
During his studies, Fujimoto
became interested in creating
simulations and modeling. He has
been more focused on software
methods ever since, particularly
on executing event simulations on
Fujimoto worked at the
University of Utah for several
years before joining Georgia
Tech in 1989.
Much of his work now
simulations with real-time data.
He describes using live data
streams of traffic conditions to
drive simulation models, which
then make predictions about
One area in which Fujimoto
is particularly interested is
mobile computing devices,
particularly with regard to the
amount of energy consumed
by simulation computation,
which affects battery life. He
anticipates putting considerable
effort into research on the
energy consumption properties
of distributed simulation
algorithms on mobile devices.
Fujimoto also is passionate
about promoting the stature
of modeling simulation as a
field in its own right, instead of
merely as an application area.