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[tor-commits] [torspec/master] Add proposal 182 ("Credit Bucket") by Tschorsch and Scheuermann
commit 1413093be9d575a4b0805e0328e2867319a543ae
Author: Nick Mathewson <nickm@xxxxxxxxxxxxxx>
Date: Mon Jun 27 15:58:45 2011 -0400
Add proposal 182 ("Credit Bucket") by Tschorsch and Scheuermann
---
proposals/000-index.txt | 2 +
proposals/182-creditbucket.txt | 181 ++++++++++++++++++++++++++++++++++++++++
2 files changed, 183 insertions(+), 0 deletions(-)
diff --git a/proposals/000-index.txt b/proposals/000-index.txt
index 06e97b5..43502ec 100644
--- a/proposals/000-index.txt
+++ b/proposals/000-index.txt
@@ -102,6 +102,7 @@ Proposals by number:
179 TLS certificate and parameter normalization [DRAFT]
180 Pluggable transports for circumvention [OPEN]
181 Optimistic Data for Tor: Client Side [OPEN]
+182 Credit Bucket [DRAFT]
Proposals by status:
@@ -114,6 +115,7 @@ Proposals by status:
144 Increase the diversity of circuits by detecting nodes belonging the same provider
175 Automatically promoting Tor clients to nodes
179 TLS certificate and parameter normalization [for 0.2.3.x]
+ 182 Credit Bucket
NEEDS-REVISION:
118 Advertising multiple ORPorts at once
131 Help users to verify they are using Tor
diff --git a/proposals/182-creditbucket.txt b/proposals/182-creditbucket.txt
new file mode 100644
index 0000000..8796bd1
--- /dev/null
+++ b/proposals/182-creditbucket.txt
@@ -0,0 +1,181 @@
+Filename: 182-creditbucket.txt
+Title: Credit Bucket
+Author: Florian Tschorsch and Björn Scheuermann
+Created: 22 Jun 2011
+Status: Draft
+
+Overview:
+
+ The following proposal targets the reduction of queuing times in onion
+ routers. In particular, we focus on the token bucket algorithm in Tor and
+ point out that current usage unnecessarily locks cells for long time spans.
+ We propose a non-intrusive change in Tor's design which overcomes the
+ deficiencies.
+
+Motivation and Background:
+
+ Cell statistics from the Tor network [1] reveal that cells reside in
+ individual onion routers' cell queues for up to several seconds. These
+ queuing times increase the end-to-end delay very significantly and are
+ apparently the largest contributor to overall cell latency in Tor.
+
+ In Tor there exist multiple token buckets on different logical levels. They
+ all work independently. They are used to limit the up- and downstream of an
+ onion router. All token buckets are refilled every second with a constant
+ amount of tokens that depends on the configured bandwidth limits. For
+ example, the so-called RelayedTokenBucket limits relay traffic only. All
+ read data of incoming connections are bound to a dedicated read token
+ bucket. An analogous mechanism exists for written data leaving the onion
+ router. We were able to identify the specific usage and implementation of
+ the token bucket algorithm as one cause for very high (and unnecessary)
+ queuing times in an onion router.
+
+ We observe that the token buckets in Tor are (surprisingly at a first
+ glance) allowed to take on negative fill levels. This is justified by the
+ TLS connections between onion routers where whole TLS records need to be
+ processed. The token bucket on the incoming side (i.e., the one which
+ determines at which rate it is allowed to read from incoming TCP
+ connections) in particular often runs into non-negligible negative fill
+ levels. As a consequence of this behavior, sometimes slightly more data is
+ read than it would be admissible upon strict interpretation of the token
+ bucket concept.
+
+ However, the token bucket for limiting the outgoing rate does not take on
+ negative fill levels equally often. Consequently, it regularly happens
+ that somewhat more data are read on the incoming side than the outgoing
+ token bucket allows to be written during the same cycle, even if their
+ configured data rates are the same. The respective cells will thus not be
+ allowed to leave the onion router immediately. They will thus necessarily
+ be queued for at least as long as it takes until the token bucket on the
+ outgoing side is refilled again. The refill interval currently is, as
+ mentioned before, one second -- so, these cells are delayed for a very
+ substantial time. In summary, one could say that the two buckets, on the
+ incoming and outgoing side, work like a double door system and frequently
+ lock cells for a full token bucket refill interval length.
+
+General Design:
+
+ In order to overcome the described problem, we propose the following
+ changes related to the token bucket algorithm.
+
+ We observe that the token bucket on the outgoing connections with its
+ current design is contra productive in the sense of queuing times. We
+ therefore propose modifications to the token bucket algorithm that will
+ eliminate the "double door effect" discussed above.
+
+ Let us start from Tor's current approach: Thus, we have a regular token
+ bucket on the reading side with a certain rate and a certain burst size.
+ Let x denote the current amount of tokens in the bucket. On the outgoing
+ side we need something appropriate that monitors and constrains the
+ outgoing rate, but at the same time avoids holding back cells (cf. double
+ door effects) whenever possible.
+
+ Here we propose something that adopts the role of a token bucket, but
+ realizes this functionality in a slightly different way. We call it a
+ "credit bucket". Like a token bucket, the credit bucket also has a current
+ fill level, denoted by y. However, the credit bucket is refilled in a
+ different way.
+
+ To understand how it works, let us look at the possible operations:
+
+ As said, x is the fill level of a regular token bucket on the incoming
+ side and thus gets incremented periodically according to the configured
+ rate. No changes here.
+
+ If x<=0, we are obviously not allowed to read. If x>0, we are allowed to
+ read up to x bytes of incoming data. If k bytes are read (k<=x), then we
+ update x and y as follows:
+
+ x = x - k (1)
+ y = y + k (2)
+
+ (1) is the standard token bucket operation on the incoming side. Whenever
+ data is admitted in, though, an additional operation is performed: (2)
+ allocates the same number of bytes on the outgoing side, which will later
+ on allow the same number of bytes to leave the onion router without any
+ delays.
+
+ If y + x > -M, we are allowed to write up to y + x + M bytes on the
+ outgoing side, where M is a positive constant. M specifies a burst size for
+ the outgoing side. M should be higher than the number of tokens that get
+ refilled during a refill interval, we would suggest to have M in the order
+ of a few seconds "worth" of data. Now if k bytes are written on the
+ outgoing side, we proceed as follows:
+
+ If k <= y then y = y - k
+
+ In this case we use "saved" credits, previously allocated on the incoming
+ side when incoming data has been processed.
+
+ If k > y then y = 0 and x = x - (k-y)
+
+ We generated additional traffic in the onion router, so that more data is
+ to be sent than has been read (the credit is not sufficient). We therefore
+ "steal" tokens from the token buffer on the incoming side to compensate for
+ the additionally generated data. This will result in correspondingly less
+ data being read on the incoming side subsequently. As a result of such an
+ operation, the token bucket fill level x on the incoming side may become
+ negative (but it can never fall below -M).
+
+ If y + x <= -M then outgoing data will be held back. This may lead to
+ double-door effects, but only in extreme cases where the outgoing traffic
+ largely exceeds the incoming traffic, so that the outgoing bursts size M is
+ exceeded.
+
+ Aside from short-term bursts of configurable size (as with every token
+ bucket), this procedure guarantees that the configured rate may never be
+ exceeded (on the application layer, that is; as with the current
+ implementation, an attacker may easily cause the onion router to
+ arbitrarily exceed the limits on the lower layers). Over time, we never
+ send more data than the configured rate: every sent byte needs a
+ corresponding token on the incoming side; this token must either have been
+ consumed by an incoming byte before (it then became a "credit"), or it is
+ "stolen" from the incoming bucket to compensate for data generated within
+ the onion router.
+
+Specific Design Changes:
+
+ In the following we briefly point out the specific changes that need to be
+ done in Tor's source code. By doing so one can see how non intrusive our
+ modifications are.
+
+ First we need to address the bucket increment and decrement operations.
+ According to the described logic above, this should be done in the methods
+ connection_bucket_refill and connection_buckets_decrement respectively. In
+ particular allocating, saving and "stealing" of tokens need to be
+ considered here.
+
+ Second the rate limiting, i.e. the amount we are allowed to write
+ (connection_bucket_write_limit) needs to be adapted in lines of the credit
+ bucket logic. Meaning in order to avoid the here identified unnecessary
+ queuing of cells, we need to consider the new burst parameter M. Here we
+ also need to take non rate limited connections such as from the localhost
+ into account. The rate limiting on the reading side remains the same.
+
+ At last we need to find good values/ ratios for the parameter M such that
+ the trade off between avoiding "double door effects" and maintaining
+ strict rate limits work as expected. As future work and after insights
+ about the performance gain of the here described proposal we need to find a
+ way to implement this both using bufferevent rate limiting with libevent
+ 2.3.x and Tor's rate limiting code.
+
+Conclusion:
+
+ This proposal can be implemented with moderate effort and requires changes
+ only at the points where currently the token bucket operations are
+ performed.
+
+ We feel that this is not the be-all and end-all solution, because it again
+ introduces a feedback loop between the incoming and the outgoing side. We
+ therefore still hope that we will be able to come to a both simpler and
+ more effective design in the future. However, we believe that what we
+ proposed here is a good compromise between avoiding double-door effects to
+ the furthest possible extent, strictly enforcing an application-layer data
+ rate, and keeping the extent of changes to the code small.
+
+ Feedback is highly appreciated.
+
+References:
+
+ [1] Karsten Loesing. Analysis of Circuit Queues in Tor. August 25, 2009.
+ [2] https://trac.torproject.org/projects/tor/wiki/sponsors/SponsorD/June2011
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