Incentives Build Robustness in BitTorrent
Bram Cohen
May 22, 2003
Abstract
The BitTorrent file distribution system uses tit-for-
tat as a method of seeking pareto efficiency. It
achieves a higher level of robustness and resource uti-
lization than any currently known cooperative tech-
nique. We explain what BitTorrent does, and how
economic methods are used to achieve that goal.
1 What BitTorrent Does
When a file is made available using HTTP, all upload
cost is placed on the hosting machine. With BitTor-
rent, when multiple people are downloading the same
file at the same time, they upload pieces of the file
to each other. This redistributes the cost of upload
to downloaders, (where it is often not even metered),
thus making hosting a file with a potentially unlim-
ited number of downloaders affordable.
Researchers have attempted to find practical tech-
niqes to do this before[3]. It has not been previously
deployed on a large scale because the logistical and
robustness problems are quite difficult. Simply figur-
ing out which peers have what parts of the file and
where they should be sent is difficult to do without
incurring a huge overhead. In addition, real deploy-
ments experience very high churn rates. Peers rarely
connect for more than a few hours, and frequently
for only a few minutes [4]. Finally, there is a gen-
eral problem of fairness [1]. The total download rate
across all downloaders must, of mathematical neces-
sity, be equal to the total upload rate. The strategy
for allocating upload which seems most likely to make
peers happy with their download rates is to make
each peer’s download rate be proportional to their
upload rate. In practice it’s very difficult to keep peer
download rates from sometimes dropping to zero by
chance, much less make upload and download rates
be correlated. We will explain how BitTorrent solves
all of these problems well.
1.1 BitTorrent Interface
BitTorrent’s interface is almost the simplest possi-
ble. Users launch it by clicking on a hyperlink to the
file they wish to download, and are given a standard
“Save As” dialog, followed by a download progress
dialog which is mostly notable for having an upload
rate in addition to a download rate. This extreme
ease of use has contributed greatly to BitTorrent’s
adoption, and may even be more important than,
although it certainly complements, the performance
and cost redistribution features which are described
in this paper.
1.2 Deployment
The decision to use BitTorrent is made by the pub-
lisher of a file. Downloaders use BitTorrent because
it’s the only way to get the file they want. Fre-
quently downloaders cease uploading as soon as their
download completes, although it is considered polite
to leave the client uploading for a while after your
download completes. The standard implementation
continues to upload until the window is closed, which
frequently results in uploads continuing until the user
gets back to their machine.
In a typical deployment, the number of incomplete
downloaders, (meaning ones which do not have the
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whole file), increases very rapidly after the file is
made available. It eventually peaks and then falls off
at a roughly exponential rate. The number of com-
plete downloaders increases slowly, peaks some time
after the number of incomplete downloaders does,
then also falls off exponentially. The peak of incom-
plete downloaders passes as downloaders complete.
The peak of incomplete downloaders passes as fin-
ished downloaders stop uploading. The exponential
falloff of both reflects the rate of new downloaders
joining after the initial rush is over.
file made available by host, downloaders use BT
because they want the file.downloaders upload while
downloading, then leave.
2 Technical Framework
2.1 Publishing Content
To start a BitTorrent deployment, a static file with
the extension .torrent is put on an ordinary web
server. The .torrent contains information about the
file, its length, name, and hashing information, and
the url of a tracker. Trackers are responsible for help-
ing downloaders find each other. They speak a very
simple protocol layered on top of HTTP in which
a downloader sends information about what file it’s
downloading, what port it’s listening on, and similar
information, and the tracker responds with a list of
contact information for peers which are downloading
the same file. Downloaders then use this information
to connect to each other. To make a file available, a
’downloader’ which happens to have the complete file
already, known as a seed, must be started. The band-
width requirements of the tracker and web server are
very low, while the seed must send out at least one
complete copy of the original file.
2.2 Peer Distribution
All logistical problems of file downloading are han-
dled in the interactions between peers. Some infor-
mation about upload and download rates is sent to
the tracker, but that’s just for statistics gathering.
The tracker’s responsibilities are strictly limited to
helping peers find each other.
Although trackers are the only way for peers to
find each other, and the only point of coordination
at all, the standard tracker algorithm is to return
a random list of peers. Random graphs have very
good robustness properties [2]. Many peer selection
algorithms result in a power law graph, which can
get segmented after only a small amount of churn.
Note that all connections between peers can transfer
in both directions.
In order to keep track of which peers have what,
BitTorrent cuts files into pieces of fixed size, typi-
cally a quarter megabyte. Each downloader reports
to all of its peers what pieces it has. To verify data in-
tegrity, the SHA1 hashes of all the pieces are included
in the .torrent file, and peers don’t report that they
have a piece until they’ve checked the hash. Era-
sure codes have been suggested as a technique which
might help with file distribution [3], but this much
simpler approach has proven to be workable.
Peers continuously download pieces from all peers
which they can. They of course cannot download
from peers they aren’t connected to, and sometimes
peers don’t have any pieces they want or won’t cur-
rently let them download. Strategies for peers dis-
allowing downloading from them, known as chok-
ing, will be discussed later. Other suggested ap-
proaches to file distribution have generally involved
a tree structure, which doesn’t utilize the upload ca-
pacity of leaves. Simply having peers announce what
they have results in less than a tenth of a percent
bandwidth overhead and reliably utilizes all available
upload capacity.
2.3 Pipelining
When transferring data over TCP, like BitTorrent
does, it is very important to always have several re-
quests pending at once, to avoid a delay between
pieces being sent, which is disastrous for transfer
rates. BitTorrent facilitates this by breaking pieces
further into sub-pieces over the wire, typically sixteen
kilobytes in size, and always keeping some number,
typically five, requests pipelined at once. Every time
a sub-piece arrives a new request is sent. The amount
of data to pipeline has been selected as a value which
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can reliably saturate most connections.
2.4 Piece Selection
Selecting pieces to download in a good order is very
important for good performance. A poor piece se-
lection algorithm can result in having all the pieces
which are currently on offer or, on the flip side, not
having any pieces to upload to peers you wish to.
2.4.1 Strict Priority
BitTorrent’s first policy for piece selection is that
once a single sub-piece has been requested, the re-
maining sub-pieces from that particular piece are re-
quested before sub-pieces from any other piece. This
does a good job of getting complete pieces as quickly
as possible.
2.4.2 Rarest First
When selecting which piece to start downloading
next, peers generally download pieces which the
fewest of their own peers have first, a technique we
refer to as ’rarest first’. This technique does a good
job of making sure that peers have pieces which all
of their peers want, so uploading can be done when
wanted. It also makes sure that pieces which are
more common are left for later, so the likelihood that
a peer which currently is offering upload will later
not have anything of interest is reduced.
Information theory dictates that no downloaders
can complete until every part of the file has been up-
loaded by the seed. For deployments with a single
seed whose upload capacity is considerably less than
that of many downloaders, performance is much bet-
ter if different downloaders get different pieces from
the seed, since redundant downloads waste the op-
portunity for the seed to get more information out.
Rarest first does a good job of only downloading new
pieces from the seed, since downloaders will be able
to see that their other peers have pieces the seed has
uploaded already.
For some deployments the original seed is eventu-
ally taken down for cost reasons, leaving only current
downloaders to upload. This leads to a very signifi-
cant risk of a particular piece no longer being avail-
able from any current downloaders. Rarest first again
handles this well, by replicating the rarest pieces as
quickly as possible thus reducing the risk of them get-
ting completely lost as current peers stop uploading.
2.4.3 Random First Piece
An exception to rarest first is when downloading
starts. At that time, the peer has nothing to upload,
so it’s important to get a complete piece as quickly
as possible. Rare pieces are generally only present
on one peer, so they would be downloaded slower
than pieces which are present on multiple peers for
which it’s possible to download sub-pieces from dif-
ferent places. For this reason, pieces to download are
selected at random until the first complete piece is
assembled, and then the strategy changes to rarest
first.
2.4.4 Endgame Mode
Sometimes a piece will be requested from a peer with
very slow transfer rates. This isn’t a problem in the
middle of a download, but could potentially delay a
download’s finish. To keep that from happening, once
all sub-pieces which a peer doesn’t have are actively
being requested it sends requests for all sub-pieces to
all peers. Cancels are sent for sub-pieces which arrive
to keep too much bandwidth from being wasted on
redundant sends. In practice not much bandwidth is
wasted this way, since the endgame period is very
short, and the end of a file is always downloaded
quickly.
3 Choking Algorithms
BitTorrent does no central resource allocation. Each
peer is responsible for attempting to maximize its
own download rate. Peers do this by downloading
from whoever they can and deciding which peers to
upload to via a variant of tit-for-tat. To cooper-
ate, peers upload, and to not cooperate they ’choke’
peers. Choking is a temporary refusal to upload; It
stops uploading, but downloading can still happen
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and the connection doesn’t need to be renegotiated
when choking stops.
The choking algorithm isn’t technically part of the
BitTorrent wire protocol, but is necessary for good
performance. A good choking algorithm should uti-
lize all available resources, provide reasonably consis-
tent download rates for everyone, and be somewhat
resistant to peers only downloading and not upload-
ing.
3.1 Pareto Efficiency
Well known economic theories show that systems
which are pareto efficient, meaning that no two coun-
terparties can make an exchange and both be hap-
pier, tend to have all of the above properties. In
computer science terms, seeking pareto efficiency is a
local optimization algorithm in which pairs of coun-
terparties see if they can improve their lot together,
and such algorithms tend to lead to global optima.
Specifically, if two peers are both getting poor recip-
rocation for some of the upload they are providing,
they can often start uploading to each other instead
and both get a better download rate than they had
before.
BitTorrent’s choking algorithms attempt to achieve
pareto efficiency using a more fleshed out version of
tit-for-tat than that used to play prisoner’s dilemma.
Peers reciprocate uploading to peers which upload to
them, with the goal of at any time of having several
connections which are actively transferring in both
directions. Unutilized connections are also uploaded
to on a trial basis to see if better transfer rates could
be found using them.
3.2 BitTorrent’s Choking Algorithm
On a technical level, each BitTorrent peer always un-
chokes a fixed number of other peers (default is four),
so the issue becomes which peers to unchoke. This
approach allows TCP’s built-in congestion control to
reliably saturate upload capacity.
Decisions as to which peers to unchoke are based
strictly on current download rate. Calculating cur-
rent download rate meaningfully is a surprisingly dif-
ficult problem; The current implementation essen-
tially uses a rolling 20-second average. Former chok-
ing algorithms used information about long-term net
transfer amounts, but that performed poorly because
the value of bandwidth shifts rapidly over time as re-
sources go away and become available.
To avoid situations in which resources are wasted
by rapidly choking and unchoking peers, BitTorrent
peers recalculate who they want to choke once every
ten seconds, and then leave the situation as is until
the next ten second period is up. Ten seconds is a
long enough period of time for TCP to ramp up new
transfers to their full capacity.
3.3 Optimistic Unchoking
Simply uploading to the peers which provide the best
download rate would suffer from having no method of
discovering if currently unused connections are bet-
ter than the ones being used. To fix this, at all times
a BitTorrent peer has a single ‘optimistic unchoke’,
which is unchoked regardless of the current download
rate from it. Which peer is the optimistic unchoke is
rotated every third rechoke period (30 seconds). 30
seconds is enough time for the upload to get to full
capacity, the download to reciprocate, and the down-
load to get to full capacity. The analogy with tit-
for-tat here is quite remarkable; Optimistic unchokes
correspond very strongly to always cooperating on
the first move in prisoner’s dilemma.
3.4 Anti-snubbing
Occasionally a BitTorrent peer will be choked by all
peers which it was formerly downloading from. In
such cases it will usually continue to get poor down-
load rates until the optimistic unchoke finds better
peers. To mitigate this problem, when over a minute
goes by without getting a single piece from a par-
ticular peer, BitTorrent assumes it is ’snubbed’ by
that peer and doesn’t upload to it except as an opti-
mistic unchoke. This frequently results in more than
one concurrent optimistic unchoke, (an exception to
the exactly one optimistic unchoke rule mentioned
above), which causes download rates to recover much
more quickly when they falter.
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3.5 Upload Only
Once a peer is done downloading, it no longer has
useful download rates to decide which peers to up-
load to. The current implementation then switches
to preferring peers which it has better upload rates
to, which does a decent job of utilizing all available
upload capacity and preferring peers which noone else
happens to be uploading to at the moment.
Figure 1: The number of complete downloaders
(‘seeders’) and incomplete downloaders (‘leechers’) of
a large deployment of an over 400 megabyte file over
time. There must have been at least 1000 successful
downloads, since at one time there were that many
complete downloaders. The actual number of down-
loads completed during this period was probably sev-
eral times that.
4 Real World Experience
BitTorrent not only is already implemented, but is al-
ready widely deployed. It routinely serves files hun-
dreds of megabytes in size to hundreds of concur-
rent downloaders. The largest known deployments
have had over a thousand simultaneous downloaders.
The current scaling bottleneck (which hasn’t actually
been reached) appears to be the bandwidth overhead
of the tracker. Currently that’s about a thousandth
the total amount of bandwidth used, and some minor
protocol extensions will probably get it down to a ten
thousandth.
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