Networking Working Group P. Levis
Internet-Draft Stanford University
Intended status: Informational T. Clausen
Expires: January 7, 2011 LIX, Ecole Polytechnique
J. Hui
Arch Rock Corporation
O. Gnawali
Stanford University
J. Ko
Johns Hopkins University
July 6, 2010
The Trickle Algorithm
draft-ietf-roll-trickle-02
Abstract
The Trickle algorithm allows wireless nodes to exchange information
in a highly robust, energy efficient, simple, and scalable manner.
Dynamically adjusting transmission windows allows Trickle to spread
new information on the scale of link-layer transmission times while
sending only a few messages per hour when information does not
change. A simple suppression mechanism and transmission point
selection allows Trickle's communication rate to scale
logarithmically with density. This document describes Trickle and
considerations in its use.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Trickle Algorithm Overview . . . . . . . . . . . . . . . . . . 3
4. Trickle Algorithm . . . . . . . . . . . . . . . . . . . . . . . 4
4.1. Parameters and Variables . . . . . . . . . . . . . . . . . 4
4.2. Algorithm Description . . . . . . . . . . . . . . . . . . . 5
5. Using Trickle . . . . . . . . . . . . . . . . . . . . . . . . . 5
6. Operational Considerations . . . . . . . . . . . . . . . . . . 6
6.1. Mismatched redundancy constants . . . . . . . . . . . . . . 6
6.2. Mismatched Imin . . . . . . . . . . . . . . . . . . . . . . 6
6.3. Mismatched Imax . . . . . . . . . . . . . . . . . . . . . . 7
6.4. Mismatched definitions . . . . . . . . . . . . . . . . . . 7
6.5. Specifying the constant k . . . . . . . . . . . . . . . . . 7
6.6. Relationship between k and Imin . . . . . . . . . . . . . . 7
6.7. Tweaks and improvements to Trickle . . . . . . . . . . . . 8
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 8
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 8
9. Security Considerations . . . . . . . . . . . . . . . . . . . . 8
10. References . . . . . . . . . . . . . . . . . . . . . . . . . . 8
10.1. Normative References . . . . . . . . . . . . . . . . . . . 8
10.2. Informative References . . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 9
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1. Introduction
The Trickle algorithm is designed for wireless networks. It
establishes a density-aware local broadcast with an underlying
consistency model that guides when a node communicates. When a
node's data does not agree with its neighbors, it communicates
quickly to resolve the inconsistency. When nodes agree, they slow
their communication rate exponentially, such that nodes send at most
a few packets per hour. Instead of flooding a network with packets,
the algorithm controls the send rate so each node hears a small
trickle of packets, just enough to stay consistent. Furthermore, by
relying only on local broadcasts, Trickle handles network re-
population, is robust to network transience, loss, and disconnection,
and requires very little state (implementations use 4-11 bytes).
While Trickle was originally designed for reprogramming protocols
(where the data is the code of the program being updated), experience
has shown it to be a powerful mechanism that can be applied to wide
range of protocol design problems, including control traffic timing,
multicast propagation, and route discovery.
This document describes the Trickle algorithm and provides guidelines
for its use. It also states requirements for protocol specifications
that use Trickle. This document does not provide results on
Trickle's performance or behavior, nor does it explain the
algorithm's design in detail: interested readers should refer to
[Levis04] and [Levis08].
2. Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in RFC
2119 [RFC2119].
3. Trickle Algorithm Overview
Trickle's basic primitive is simple: every so often, a node transmits
code metadata if it has not heard a few other nodes transmit the same
thing. This allows Trickle to scale to thousand-fold variations in
network density, quickly propagate updates, distribute transmission
load evenly, be robust to transient disconnections, handle network
repopulations, and impose a maintenance overhead on the order of a
few packets per hour.
Trickle sends all messages to the local broadcast address. There are
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two possible results to a Trickle broadcast: either every node that
hears the message is up to date, or a recipient detects the need for
an update. Detection can be the result of either an out-of-date node
hearing someone has new code, or an updated node hearing someone has
old code. As long as every node communicates somehow - either
receives or transmits - the need for an update will be detected.
For example, consider a simple case where "up to date" is defined by
version numbers (e.g., network configuration). If node A broadcasts
that it has version V, but B has version V+1, then B knows that A
needs an update. Similarly, if B broadcasts that it has V+1, A knows
that it needs an update. If B broadcasts updates, then all of its
neighbors can receive them without having to advertise their need.
Some of these recipients might not even have heard A's transmission.
In this example, it does not matter who first transmits, A or B;
either case will detect the inconsistency. All that matters is that
some nodes communicate with one another at some nonzero rate. As
long as the network is connected and there is some minimum
communication rate for each node, the network will reach eventual
consistency.
The fact that communication can be either transmission or reception
enables Trickle to operate in sparse as well as dense networks. A
single, disconnected node must transmit at the communication rate.
In a lossless, single-hop network of size n, the sum of transmissions
over the network is the communication rate, so for each node it is
1/n. Sparser networks require more transmissions per node, but
utilization of the radio channel over space will not increase. This
is an important property in wireless networks, where the channel is a
valuable shared resource. Additionally, reducing transmissions in
dense networks conserves system energy.
4. Trickle Algorithm
This section describes the Trickle algorithm.
4.1. Parameters and Variables
A Trickle timer has three configuration parameters: the minimum
interval size Imin, the maximum interval size Imax, and a redundancy
constant k:
o The minimum interval size is defined in units of time (e.g.,
milliseconds, seconds). For example, a protocol might define the
minimum interval as 100 milliseconds.
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o The maximum interval size is described as a number of doublings of
the minimum interval size (the base-2 log(max/min)). For example,
a protocol might define the maximum interval as 16. If the
minimum interval is 100ms, then the maximum interval is 100ms *
65536, 6,553.6 seconds, or approximately 109 minutes.
o The redundancy constant is a natural number (an integer greater
than zero).
In addition to these three parameters, Trickle maintains three
variables:
o I, the current interval size
o t, a time within the current interval, and
o c, a counter.
4.2. Algorithm Description
The Trickle algorithm has five rules:
1. When an interval begins, Trickle resets c to 0 and sets t to a
random point in the interval, taken from the range [I/2, I).
2. Whenever Trickle hears a transmission that is "consistent," it
increments counter c.
3. At time t, Trickle transmits if and only if counter c is less
than the redundancy constant k.
4. When an interval expires, Trickle doubles the interval length.
If this new interval length would be longer than Imax, Trickle
sets the interval length I to be Imax.
5. If Trickle hears a transmission that is "inconsistent," the
Trickle timer resets. If I is greater than Imin, resetting a
Trickle timer sets I to Imin and begins a new interval. If I is
equal to Imin, resetting a Trickle timer does nothing. Trickle
may also reset the timer in response to external "events."
The terms consistent, inconsistent and event are in quotes because
their meaning depends on the use of Trickle.
5. Using Trickle
A protocol specification that uses Trickle MUST specify:
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o Default values for Imin, Imax, and k. Because link layers can
vary widely in their properties, the default value of Imin should
be specified in terms of the worst-case latency of a link layer
transmission. For example, a specification should say "the
default value of Imin is 4 times the worst case link layer
latency" and should not say "the default value of Imin is 500
milliseconds." Worst case latency is the time until the first
link-layer transmission of the frame assuming an idle channel
(does not include backoff, virtual carrier sense, etc.).
o What constitutes a "consistent" transmission.
o What constitutes an "inconsistent" transmission.
o What "events," if any, besides inconsistent transmissions that
reset the Trickle timer.
6. Operational Considerations
It is RECOMMENDED that a protocol which uses Trickle include
mechanisms to inform nodes of configuration parameters at runtime.
However, it is not always possible to do so. In the cases where
different nodes have different configuration parameters, Trickle may
have unintended behaviors. This section outlines some of those
behaviors and operational considerations as educational exercises.
6.1. Mismatched redundancy constants
If nodes do not agree on the redundancy constant k, then nodes with
higher values of k will transmit more often than nodes with lower
values of k. In some cases, this increased load can be independent
of the density. For example, consider a network where all nodes but
one have k=1, and this one node has k=2. The different node can end
up transmitting on every interval: it is maintaining a communication
rate of 2 with only itself. Hence, the danger of mismatched k values
is uneven transmission load that can deplete the energy of some
nodes.
6.2. Mismatched Imin
If nodes do not agree on Imin, then some nodes, on hearing
inconsistent messages, will transmit sooner than others. These
faster nodes will have their intervals grow to similar size as the
slower nodes within a single slow interval time, but in that period
may suppress the slower nodes. However, such suppression will end
after the first slow interval, when the nodes generally agree on the
interval size. Hence, mismatched Imin values are usually not a
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significant concern.
6.3. Mismatched Imax
If nodes do not agree on Imax, then this can cause long-term problems
with transmission load. Nodes with small Imax values will transmit
faster, suppressing those with larger Imax values. The nodes with
larger Imax values, always suppressed, will never transmit. In the
base case, when the network is consistent, this can cause long-term
inequities in energy cost.
6.4. Mismatched definitions
If nodes do not agree on what constitutes a consistent or
inconsistent transmission, then Trickle may fail to operate properly.
For example, if a receiver thinks a transmission is consistent, but
the transmitter (if in the receivers situation) would have thought it
inconsistent, then the receiver will not respond properly and inform
the transmitter. This can lead the network to not reach a consistent
state. For this reason, unlike the configuration constants k, Imin,
and Imax, consistency definitions should be clearly stated in the
protocol and should not be configured at runtime.
6.5. Specifying the constant k
There are some edge cases where a protocol may wish to use Trickle
with its suppression disabled (k is set to infinity). In general,
this approach is highly dangerous and it is NOT RECOMMENDED.
Disabling suppression means that every node will always send on every
interval, and can lead to congestion in dense networks. This
approach is especially dangerous if many nodes reset their intervals
at the same time. In general, it is much more desirable to set k to
a high value (e.g., 5 or 10) than infinity. Typical values for k are
1-5: these achieve a good balance between redundancy and low cost.
Nevertheless, there are situations where a protocol may wish to turn
off Trickle suppression. Because k is a natural number
(Section 4.1), c=0 has no useful meaning. If a protocol allows k to
be dynamically configured, a value of 0 remains unused. For ease of
debugging and packet inspection, having the parameter describe (c-1)
can be counter-productive. Instead, it is RECOMMENDED that protocols
which require turning off suppression reserve c=0 to mean c=infinity.
6.6. Relationship between k and Imin
Finally, a protocol SHOULD set k and Imin such that Imin is at least
two to three as long as it takes to transmit k packets. Otherwise,
if more than k nodes reset their intervals to Imin, the resulting
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communication will lead to congestion and significant packet loss.
Experimental results have shown that packet losses from congestion
reduce Trickle's efficiency [Levis04].
6.7. Tweaks and improvements to Trickle
Trickle is based on a small number of simple, tightly integrated
mechanisms that are highly robust to challenging network
environments. In our experiences using Trickle, attempts to tweak
its behavior are typically not worth the cost. As written, the
algorithm is already highly efficient: further reductions in
transmissions or response time come at the cost of failures in edge
cases. Based on our experiences, we urge protocol designers to
suppress the instinct to tweak or improve Trickle without a great
deal of experimental evidence that the change does not violate its
assumptions and break the algorithm in edge cases.
This warning in mind, Trickle is far from perfect. For example,
Trickle suppression typically leads sparser nodes to transmit more
than denser ones; it is far from the optimal computation of a minimum
cover. However, in dynamic network environments such as wireless,
the coordination needed to compute the optimal set of transmissions
is typically much greater than the benefits it provides. One of the
benefits of Trickle is that it is so simple to implement and requires
so little state yet operates so efficiently. Efforts to improve it
should be weighed against the cost of increased complexity.
7. Acknowledgements
8. IANA Considerations
This document has no IANA considerations.
9. Security Considerations
This document has no security considerations.
10. References
10.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
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10.2. Informative References
[Levis04] Levis, P., Patel, N., Culler, D., and S. Shenker,
"Trickle: A Self-Regulating Algorithm for Code Propagation
and Maintenance in Wireless Sensor Networks"", Proceedings
of the First USENIX/ACM Symposium on Networked Systems
Design and Implementation NSDI 2004, March 2004,
<http://portal.acm.org/citation.cfm?id=1251177>.
[Levis08] Levis, P., Brewer, E., Culler, D., Gay, D., Madden, S.,
Patel, N., Polastre, J., Shenker, S., Szewczyk, R., and A.
Woo, "The Emergence of a Networking Primitive in Wireless
Sensor Networks", Communications of the ACM, v.51 n.7,
July 2008,
<http://portal.acm.org/citation.cfm?id=1364804>.
Authors' Addresses
Philip Levis
Stanford University
358 Gates Hall, Stanford University
Stanford, CA 94305
USA
Phone: +1 650 725 9064
Email: pal@cs.stanford.edu
Thomas Heide Clausen
LIX, Ecole Polytechnique
Phone: +33 6 6058 9349
Email: T.Clausen@computer.org
Jonathan Hui
Arch Rock Corporation
501 Snd St., Suite 410
San Francisco, CA 94107
USA
Email: jhui@archrock.com
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Omprakash Gnawali
Stanford University
S255 Clark Center, 318 Campus Drive
Stanford, CA 94305
USA
Phone: +1 650 725 6086
Email: gnawali@cs.stanford.edu
JeongGil Ko
Johns Hopkins University
3400 N. Charles St., 224 New Engineering Building
Baltimore, MD 21218
USA
Phone: +1 410 516 4312
Email: jgko@cs.jhu.edu
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