Networking Working Group P. Levis
Internet-Draft Stanford University
Intended status: Informational T. Clausen
Expires: September 24, 2010 LIX, Ecole Polytechnique
March 23, 2010
The Trickle Algorithm
draft-ietf-roll-trickle-00
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 nechanism and transmission point
selection allows Trickle's communication rate to scale
logarithmically with density. This document describes Trickle and
considerations in its use.
Status of this Memo
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Copyright Notice
Copyright (c) 2010 IETF Trust and the persons identified as the
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document authors. All rights reserved.
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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 . . . . . . . . . . . . . . . . . . . . . . . . . 6
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
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 7
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 7
9. Security Considerations . . . . . . . . . . . . . . . . . . . . 7
10. References . . . . . . . . . . . . . . . . . . . . . . . . . . 7
10.1. Normative References . . . . . . . . . . . . . . . . . . . 7
10.2. Informative References . . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 8
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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 communicationrate exponentially, such that in a stable state
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. For example, routing protocols
such as RPL use Trickle to ensure that nodes in a given neighborhood
have consistent, loop-free routes. When the topology is consistent,
nodes occasionally gossip to check that they still agree, and when
the topology changes they gossip more frequently, until they reach
consistency again.
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
[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 mote transmits
code metadata if it has not heard a few other motes transmit the same
thing. This allows Trickle to scale to thousand-fold variations in
network density, quickly propagate updates, distribute transmission
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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
two possible results to a Trickle broadcast: either every mote 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 mote
hearing someone has new code, or an updated mote hearing someone has
old code. As long as every mote 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 mote, 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:
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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.
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" and I is
greater than Imin, Trickle resets I to Imin, and begins a new
interval.
The terms consistent and inconsistent are in quotes because their
meaning depends on the use of Trickle.
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5. Using Trickle
A protocol specification that uses Trickle should specify:
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.
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 as an educational exercise.
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
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interval size. Hence, mismatched Imin values are usually not a
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 will
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.
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
[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
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