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. Status of this Memo This Internet-Draft is submitted to IETF in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet- Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." The list of current Internet-Drafts can be accessed at http://www.ietf.org/ietf/1id-abstracts.txt. The list of Internet-Draft Shadow Directories can be accessed at http://www.ietf.org/shadow.html. Levis, et al. Expires January 7, 2011 [Page 1] Internet-Draft draft-ietf-roll-trickle-02 July 2010 This Internet-Draft will expire on January 7, 2011. Copyright Notice Copyright (c) 2010 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (http://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Simplified BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the BSD License. Levis, et al. Expires January 7, 2011 [Page 2] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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 Levis, et al. Expires January 7, 2011 [Page 3] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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 Levis, et al. Expires January 7, 2011 [Page 4] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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. Levis, et al. Expires January 7, 2011 [Page 5] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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: Levis, et al. Expires January 7, 2011 [Page 6] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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 Levis, et al. Expires January 7, 2011 [Page 7] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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 Levis, et al. Expires January 7, 2011 [Page 8] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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. Levis, et al. Expires January 7, 2011 [Page 9] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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, . [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, . 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 Levis, et al. Expires January 7, 2011 [Page 10] Internet-Draft draft-ietf-roll-trickle-02 July 2010 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 Levis, et al. Expires January 7, 2011 [Page 11]