Network Working Group                                           J. Arkko
Internet-Draft                                               H. Rissanen
Intended status: Informational                                 S. Loreto
Expires: January 5, 2012                                      Z. Turanyi
                                                                 O. Novo
                                                            July 4, 2011

                     Implementing Tiny COAP Sensors


   The authors are developing COAP and IPv6-based sensor networks for
   environments where lightweight implementations, long battery
   lifetimes, and minimal management burden are important.  The memo
   shows how different communication models supported by COAP affect
   implementation complexity and energy consumption, far more so than
   mere changes in message syntax.  Our prototype implements a
   multicast-based IPv6, UDP, COAP, and XML protocol stack in less than
   50 assembler instructions.  While this extremely minimal
   implementation is suitable only for limited applications and makes a
   number of assumptions, the general conclusions point to need for
   further work in developing the COAP multicast and observation

Status of this Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
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   Drafts is at

   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."

   This Internet-Draft will expire on January 5, 2012.

Copyright Notice

   Copyright (c) 2011 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   ( in effect on the date of
   publication of this document.  Please review these documents
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   described in the Simplified BSD License.

Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
   2.  Goals  . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4
   3.  Implementing Tiny COAP-Based Sensors . . . . . . . . . . . . .  5
     3.1.  Sleeping Nodes and Energy Use  . . . . . . . . . . . . . .  5
     3.2.  Address Autoconfiguration  . . . . . . . . . . . . . . . .  6
     3.3.  Using Multicast  . . . . . . . . . . . . . . . . . . . . .  7
     3.4.  Using COAP . . . . . . . . . . . . . . . . . . . . . . . .  8
     3.5.  Power Usage Calculation  . . . . . . . . . . . . . . . . .  8
     3.6.  Software Construction  . . . . . . . . . . . . . . . . . .  9
     3.7.  UDP Checksums  . . . . . . . . . . . . . . . . . . . . . . 10
     3.8.  Evaluation . . . . . . . . . . . . . . . . . . . . . . . . 11
   4.  Choosing a Communication Model . . . . . . . . . . . . . . . . 12
     4.1.  End-to-End Communication and Intermediaries  . . . . . . . 13
     4.2.  COAP Messaging . . . . . . . . . . . . . . . . . . . . . . 15
       4.2.1.  Client Model . . . . . . . . . . . . . . . . . . . . . 15
       4.2.2.  Server Model . . . . . . . . . . . . . . . . . . . . . 17
       4.2.3.  Observer Model . . . . . . . . . . . . . . . . . . . . 18
     4.3.  Resources and Data Formats . . . . . . . . . . . . . . . . 20
     4.4.  Configuration  . . . . . . . . . . . . . . . . . . . . . . 21
   5.  Security Considerations  . . . . . . . . . . . . . . . . . . . 22
   6.  Conclusions  . . . . . . . . . . . . . . . . . . . . . . . . . 22
   7.  References . . . . . . . . . . . . . . . . . . . . . . . . . . 23
     7.1.  Normative References . . . . . . . . . . . . . . . . . . . 23
     7.2.  Informative References . . . . . . . . . . . . . . . . . . 23
   Appendix A.  Acknowledgments . . . . . . . . . . . . . . . . . . . 25
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 25

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1.  Introduction

   The authors are developing COAP [I-D.ietf-core-coap] and IPv6-based
   [RFC2460] sensor networks for home, building, and other consumer
   environments.  These environments demand solutions where the sensors
   are physically small, inexpensive, have long battery lifetimes, and
   require minimal amount of management effort.  Our prototype sensor
   implementation requires no configuration and runs a multicast-based
   IPv6, UDP, COAP, and XML protocol stack and an application with
   implementation size under 50 assembler instructions.

   Small devices are naturally preferred in most applications, but for
   some applications small enough size is a critical concern, for
   instance, to make devices embedded in our clothing practical, to fit
   within the space available in buildings or everyday objects, or to
   ensure that the devices do not cause a visual distraction.  Another
   key concern is device and battery lifetime.  Sufficient battery
   lifetime in an application with a large number of devices can be
   surprisingly long.  A home with hundred devices with ten year battery
   lifetimes will result in a battery change operation every month.

   The practical challenge is to increase battery lifetimes of small
   devices by several orders of magnitude, and to enable pinhead size
   devices connected to the Internet.  These are not unattainable goals,
   as legacy sensor networking technology can in some cases reach these
   goals.  For instance, networked 1-Wire temperature sensors are the
   size of a packaged transistor.  Our aim is to replicate this model or
   even improve it for IP-based sensors.

   Another challenge is to ensure that COAP-based networks are
   interoperable in a multi-vendor environment.  For instance, it is
   important that proxies and servers can perform all the necessary
   tasks without being programmed to support a sensor node manufactured
   by a particular vendor, or perhaps even without being programmed to
   support a particular class of a sensor.

   This memo describes implementation experiences, open questions that
   we have encountered, and areas where COAP makes it difficult to make
   very low power implementations.  The memo discusses implementation
   techniques that are useful in these environments and what is needed
   for fully interoperable solutions based on COAP.

   The goals for our work are described in Section 2.  Before we can
   dwell into the high-level networking design choices, we highlight
   some of the implications of detailed implementation strategies
   through an example.  Section 3 discusses our specific implementation
   strategies, and describes our experiences with these choices.  This
   example is an extreme case, an attempt to minimize as much as

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   possible for a limited set of applications.  However, some general
   conclusions can still be seen.  The more general discussion of the
   different high-level approaches to communications models can be found
   in Section 4.  Different communication models supported by COAP
   affect implementation complexity and energy consumption, far more so
   than mere changes in message syntax.  The required configuration
   effort is also directly affected by the choice of the communications
   model.  Finally, the concluding recommendations point to need for
   further work in developing COAP and its multicast and observation
   frameworks [I-D.ietf-core-coap] [I-D.ietf-core-observe], as discussed
   in Section 6.

2.  Goals

   The main focus of this draft is sensors that are deployed in large
   quantities and have specific physical requirements.  There are
   similar issues with other nodes such as servers and proxies, but in
   general these nodes have better access to power and other resources,
   and typically can also be more easily configured by humans.

   As discussed in the introduction, for sensors the overall
   requirements revolve around minimizing physical size, cost,
   management effort and maximizing battery lifetimes.  More
   specifically, we believe the following goals are key in achieving
   fulfilling these requirements:

   o  Natural support for sleeping nodes.  There are many aspects to
      power usage in small devices, but we believe this one is the most
      significant one in terms of minimizing power usage.  Many of the
      other aspects are either dictated by the environment (such as
      choice of radio technology in a given network) or have a
      relatively small impact (small variations in message size, for

   o  Communication models that fit the problem at hand.  It is
      essential that the small nodes can engage in communication
      exchanges that suit their needs.  Having to employ multiple
      roundtrips, wait for nodes they have no control over, and so on
      can have a large negative effect on the amount of power that the
      node has to spend.

   o  Good design from user perspective.  It is obviously undesirable to
      require a lot of per-device configuration effort when deploying a
      large set of small devices.  In addition, direct configuration
      efforts with the device itself may be problematic, given that
      there is no room for any type of a user interface.  For instance,
      some of the legacy sensor devices in existing networks are just a

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      few millimeters across.  It is natural that some information needs
      to be configured, but configuration should be minimized and
      whatever configuration is necessary should take place in nodes
      that have the necessary user interfaces and capabilities.

3.  Implementing Tiny COAP-Based Sensors

   We have implemented prototypes of small sensors and a sensor gateway
   to pass the information onwards.  The main target of these
   implementations is temperature, humidity, and other measurements in
   home environments.  Our focus is primarily in sensing.  Actuators and
   other more complex functions are outside the scope of our analysis.

   Our prototype sensor implementation requires no configuration and
   simply runs based on its own identity burned in the hardware.  The
   complete functionality requires only a small amount of code.  Our
   prototype platform uses a 32-bit processor architecture and the
   hardware provides an underlying capability to send a link layer
   frame.  In this platform, our implementation is under 50 assembler
   instructions.  The implementation consists of a Ethernet, IPv6, UDP,
   COAP, and XML protocol stack and the sensor application.  The sensor
   application is based on values provided by an A/D converter; any
   analog value can be measured.

   Even this size of the implementation is not the absolute minimum.
   One quarter of the code in our implementation relates to specific
   initializations required for the A/D converter that we used.  Another
   quarter relates to binary to decimal conversions on the chosen XML-
   based payload.  On a different platform and with binary data, 25
   instructions would be achievable.  Of course, with different link
   layers and platforms an implementation might have to be arbitrarily
   complex to support the intricacies of the link layer in question.

   The following subsections outline the design choices that were taken
   to create the small implementation we have.

3.1.  Sleeping Nodes and Energy Use

   As discussed earlier, choosing the right communication model is what
   drives a good design from a power conservation perspective.

   In our implementation, we chose to use a send-only model where the
   device only sends messages, but never receives one.  This model can
   be applied in specialized applications under some assumptions that
   will be discussed further later in this memo.  In our case, the
   sensor will periodically take a reading and send a COAP message to
   the network with that reading.  In order to eliminate potential

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   waiting periods where the device has to stay on, we needed to
   eliminate the following:

   o  DHCP request - response process [RFC2131].

   o  Router Discovery process [RFC4861].

   o  Duplicate Address Detection process [RFC4862].

   o  Acting as a COAP server [I-D.ietf-core-coap].

   o  Waiting for COAP observation subscriptions

3.2.  Address Autoconfiguration

   Eliminating DHCP is easy, as we can simply use IPv6 and stateless
   address autoconfiguration.  Eliminating router discovery is harder,
   however.  To avoid having to wait for a Router Advertisement to carry
   a prefix, we chose to employ a link-local source adress.  These
   addresses can be constructed from the well-known prefix FE80::0 and a
   link layer hardware address burned to the hardware [RFC4862].

   Eliminating Duplicate Address Detection is a matter of choice.  We
   chose to behave as if DupAddrDetectTransmits had been set to zero, in
   other words not performing any Duplicate Address Detection.  It may
   be debatable whether this is a violation of [RFC4862], but it is
   certainly against its spirit.  This choice seems to be the right
   technical action, however, on a number of grounds:

   o  As the node is not receiving any packets, nor sending Neighbor
      Advertisement messages, any effects of possible duplication would
      be limited to some additional traffic in the network.  No other
      traffic would be impacted.  Application-level collection of sensor
      information can proceed even in this situation.

   o  [RFC4862] requires that upon detecting a duplicated address,
      "autoconfiguration stops and manual configuration of the interface
      is required".  However, it is obvious that no such action is
      possible on a small device.  The device has no user interface.
      The only interface that the device has is the network, and if the
      network cannot be brought up, there's very little that can be
      done.  As a result, the ability to not stop in a duplication case
      may actually be better than what is recommended by [RFC4862].

   o  These devices are manufactured with hardware identities that are
      expected to be unique.  There are obviously no guarantees about
      this succeeding in all cases, but non-unique identifiers would

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      represent a major failure of the manufacturing process.

   Elimination of Duplicate Address Detection also eliminates the need
   for the node to implement Multicast Listener Detection (MLD) protocol
   [RFC2710] [RFC3810].  This is because it now no longer needs to
   listen for messages to the solicited node multicast address, so there
   is no need to send out MLD messages.

3.3.  Using Multicast

   To further eliminate configuration or protocol exchanges for
   discovery, we chose to employ a multicast model where the sensor
   sends COAP POST requests to a well-known multicast address.  While
   the type of sensors targeted here send information very infrequently,
   one of our goals was to ensure that the architecture would scale to
   more frequent information distribution and far larger groups of
   sensors.  As a result, it was important to ensure that the multicast
   messages do not lead to multicast storms or unnecessary waking up
   many nodes due to frequent messages.

   We chose to employ an interest-based generated multicast group
   address.  These addresses are similar to those used in IPv6 Neighbor
   Discovery [RFC4861] for sending messages to solicited node addresses
   (FF02:0:0:0:0:1:FFXX:XXXX) [RFC4291].  The idea is that some bits
   from the object of interest are reflected in the multicast address,
   making it statistically likely that someone interested in a specific
   object only has to receive packets relating to that object, and not
   all packets.

   We employ FF02:0:0:0:1:FEXX:XXXX, where XX:XXXX is a 6-byte value
   representing the type of sensor.  (This address is currently reserved
   by IANA, but could be allocated for this purpose if needed.)  The
   sensor type represents a classification of different sensor to types.
   For instance, we could let 00:0001 stand for temperature sensors.
   Each temperature sensor would send information to the multicast
   address FF02:0:0:0:1:FE00:0001, and only those devices that are
   interested in temperature measurements would subscribe to this
   multicast group.  Techniques such as MLD/IGMP snooping can be used in
   the network to ensure that multicast messages are physically
   transmitted only in those parts of the network that actually care
   about those messages [RFC4541].  In practice, this would mean that in
   a star topology network with a large number of sensors and a few
   central nodes, none of the sensors would receive any messages from
   each other.

   Finally, randomization of actual transmission times for the periodic
   transmissions ensures that transmissions from different sensors are
   not synchronized.

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   When sensors send multicast messages with link-local source and
   destination addresses, all communication is confined to a single
   network.  We expect that there is a node in the network that listens
   to the multicast messages, collects the data from them, and is
   capable of relaying the information to other parties.  Such a node
   might store the latest information related to each sensor, and allow
   other nodes in the Internet to query the latest information on a per-
   sensor or an aggregate basis.

3.4.  Using COAP

   Our implementation uses non-confirmable requests at the messaging
   layer of COAP, and sends a POST message that carries an XML payload
   for a well-known URI.  The implementation sends a message and does
   not wait for a message at this layer.  We have used a gateway to
   store the information received from the sensors, making the gateway
   act as a server, storing everything posted to it.  The stored
   information can be fetched from the gateway, for instance, with a

   Per Section 2.8.2 of [I-D.ietf-core-coap], POST methods normally
   generate a response at the request/response layer.  If the server
   sends a response, the sensor is already asleep and will not respond
   to Neighbor Discovery messages or receive the actual message.  The
   message is therefore lost, but it is fine in our case given that the
   information was already stored in the server.

   Reliable transmission is achieved through assuming a sufficiently
   high periodic transmission rate to account for randomly occurring
   message loss.

   There are several areas of concern with the above arrangements,
   discussed further in Section 3.8 and Section 4.2.

3.5.  Power Usage Calculation

   Our communication model is now complete.  Its effectiveness can be
   calculated by determining what fraction of time the device would have
   to be awake.  Lets assume periodic messages once per minute, a 10
   Mbit/s link layer interface, and a CPU running at 1 Mhz. With the
   given link layer, sending one message takes theoretically 100
   microseconds.  Constructing the message takes 50 instructions and if
   we for simplicity assume that each instruction takes two clock
   cycles, the CPU needs to run for an additional 100 microseconds.
   Since our device is only sending messages, it only has to wake up to
   send the message.  Ratio of sleeping versus being awake is now 200
   microseconds versus 60 seconds, i.e., 300.000.  Even if we assume
   that it takes an additional 800 microseconds to power the device up

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   and let the A/D converter stabilize, the ratio is still 1000
   microseconds vs. 60 seconds, i.e., 60.000.

   We can compare this to some other possible implementations.  A node
   that stays awake and participates in Neighbor Discovery, Duplicate
   Address Detection, and ARP processes would consume 60.000 times more
   energy.  One could assume that listening is less power consuming than
   sending, however.  On some link layers today this ratio can be as
   high as listening consuming 2.500 time less power, though practical
   implementations (talk vs. standby times) seem to be more in the range
   of a 100-fold difference.  If we assume an optimistic 1.000 time
   difference, our implementation would still consume 60 times less
   energy than one that stays on all the time.

   Another possible implementation is that a node stays awake for a
   short period of time to listen for possible messages.  Some COAP
   implementations do this to enable discovery and observe subscriptions
   to work.  If we assume one second awake time during one minute, then
   the power consumption difference to our implementation is somewhere
   between 1.000 and 2 times, depending on whether send/receive power
   requirements differences are factored in.

   While these comparisons have produced wildly different numbers, it is
   clear that our implementation strategy is far superior to the
   simplistic always-on model.  The situation is less clear with the
   comparison to the periodically listening approach, but even there it
   is clear that not listening consumes less energy than listening.
   While the actual numbers depend highly on the characteristics of the
   link layer, even with the most optimistic assumptions for the
   alternative approach it uses twice as much energy.  This may not
   sound like a significant difference, but if it means a ten year
   battery lifetime instead of five year battery lifetime, it can make
   or break a business case for building some types of sensors.

3.6.  Software Construction

   When memory and processing power is at a premium, the detailed
   software design approach needs to suit the platform that the software
   runs on.  That being said, for simple send-only applications we have
   found that a packet template-based approach works well.  In this
   approach an image of the message sent by the application is burned
   into the read-only memory of the device, as a part of the overall
   software image.  When the device powers up, the message image is
   copied to random access memory, necessary changes are applied, and
   the underlying link layer hardware or the CPU emits it on the
   outgoing interface bit by bit.

   In case of COAP and simple sensors that output a numerical value

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   transmitted in an XML [W3C.REC-xml-19980210] or JSON [RFC4627]
   payload, only the following changes are applicable:

   o  16-bit COAP Message ID field (see Section 3.1 in
      [I-D.ietf-core-coap]).  This field should be set to a random
      value, a rarely repeating value.  We have found that using a
      suitably shifted value of a real-time clock is the most convenient
      way to generate a good value for this field.  On many small
      platforms, a real-time clock can be kept counting with a very
      small amount of power.  Note that it does not matter what value
      the real-time clock is initially initialized to; the only thing
      that matters for the Message ID field is that it keeps changing.
      If a sensor sends a value every minute, shifting a seconds-from-
      epoch counter by five bit positions is a good way to generate a
      unique value.

      Note that using a different value may not actually be required,
      though it is certainly helpful for understanding network traces
      and debugging.  According to Section 4.1 of [I-D.ietf-core-coap],
      Message IDs only have to be unique within RESPONSE_TIMEOUT *
      RESPONSE_RANDOM_FACTOR * (2 ^ MAX_RETRANSMIT - 1) or 45 seconds,
      so a sensor sending messages every minute would be allowed to send
      them with the same Message ID.

   o  The actual sensor reading.  In both XML and JSON, values can be
      padded with leading zeros or spaces, so the overall size of the
      packet can be kept the same in all circumstances.  This greatly
      simplifies the construction of the packet.

      Note that binary or hexadecimal formats would make this even
      simpler, but the savings are in the order of few instructions; the
      difference is not big.  Of course, a message that carries a text
      is longer than a pure binary message.  However, the format is not
      so important as is avoiding including a lot of extraneous
      information.  Some XML schemas can be problematic.  We advocate
      simplicity and restraint in XML schema design for sensor data.

   o  16-bit UDP checksum field.  For computing this field, see
      Section 3.7.

   Note this small set of changes is only applicable when it can be
   assumed that both source and destination IP addresses are known

3.7.  UDP Checksums

   Both IPv4 and IPv6 have some form of mandatory checksums, either in
   the IP header (IPv4) or as part of upper layer protocols such as UDP

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   (IPv6).  Computing the checksum is not difficult, but requires
   looping through all the 16-bit words in a packet.  Fortunately, for a
   simple application the checksum calculation is actually very simple.
   Following the algorithm in [RFC1624], there is no need to calculate
   the checksum for the entire packet.  The checksum can be precomputed
   on the packet template with zero words filled in for the variable
   parts.  Lets call this precomputed checksum value C. Let NC be its
   negation, i.e.,

     NC = ~C

   Once the actual values are filled in the packet, the true checksum C'
   needs to be calculated as follows:

     T = NC + W1 + W2 + ... + Wn
     C' = ~(T + (T >> 16))

   where T is a temporary variable and Wi, i = 0, 1, ..., n are the
   words that got changed from the template.  Naturally, this approach
   makes sense only when the number of changed words is small.  We have
   found that suitable placement of spaces and string values in an XML
   object, for instance, is helpful in aligning the changed parts to
   word boundaries, and in sensor implementations n = 3.

3.8.  Evaluation

   This type of an implementation is obviously an extreme example.  This
   level of optimization may not be needed in all cases.  Nevertheless,
   it is interesting to see that COAP can be used in such small

   In general, our implementation satisfies the requirements set for the
   special environment that it was designed for: power usage is
   minimized, individual sensor devices do not require configuration,
   existing legacy networks can migrate to general-purpose IP-based
   networks, and all the necessary information can be passed in the

   That being said, there are also some issues with this implementation
   approach.  The first issue is that information delivery frequency is
   hardwired into the sensors.  The chosen frequency may be sufficient
   for a given application, but the same sensors cannot be used by
   another application that would require a faster delivery of

   Related but more serious concern is that reliability is achieved
   through randomized message intervals and multiple transmissions; it
   is considered unlikely that a very large number of messages in

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   sequence are lost from the same sensor.  The message transmission
   frequency needs to be set high enough to accommodate some packet
   loss.  There is no way to actively request retransmission.  We
   believe that this is a small problem in well-designed networks and
   for most applications that are not real-time critical, such as home,
   weather, maintenance, and energy monitoring.  However, this approach
   may not be suitable for real-time or safety-critical applications.

   The third and obvious limitation is that there is an assumption of a
   network node in the same network that is capable of storing
   information.  We believe that there is little that can be done about
   this assumption; it is fundamental for the nature of low-power
   devices that they have to be able to sleep periodically, and there
   are very few other options beyond implementing a time-shifting device
   such as a cache.  The location of the cache node could be outside the
   sensor network in some other designs, however.

4.  Choosing a Communication Model

   COAP is a specialized web transfer protocol designed to be used in
   various ways.  The communication model of COAP is flexible and the
   application developer has to decide the best way to use it.  This

   o  deciding which parties are in server/client roles,

   o  determining whether to use end-to-end communication or employ
      intermediary nodes,

   o  deciding whether to use base COAP operations or the observation

   o  deciding whether a discovery process is required,

   o  specifying how COAP maps to lower layers, including choice of
      source and destination addresses, and

   o  agreeing about commonly understood methods, resource identifiers
      and data representation.

   Note that the number of these choices alone makes it hard to achieve
   interoperability, as we should strive for application
   interoperability at the semantic level [arkko.iab], rather than mere
   ability to transport correctly formed COAP packets.

   Nevertheless, the main focus of this memo is to determine the power
   efficiency implications for the different communications models, and

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   to identify areas where COAP limits this efficiency.  The rest of
   this section is structured as follows.  Section 4.1 discusses which
   nodes are involved.  Section 4.2 discusses the specific COAP
   messaging alternatives.  Section 4.3 discusses resources and data
   formats.  Section 4.4 discusses configuration issues.

4.1.  End-to-End Communication and Intermediaries

   In most applications, user interactions and information requests can
   come at any time.  Some form of an intermediary that can buffer such
   requests between a possibly sleeping device and the end user seems
   therefore useful to provide "time-shifting" capability.  Similarly,
   an intermediary can be useful to reduce the number of transactions
   that one has to do with the low-power device to a minimum; the
   intermediary can answer on behalf of the device should a large number
   of information requests be placed.

   In its simplest form, the intermediary is a part of the application
   server.  For instance, a web-based application server is capable of
   serving web clients at any time, but will only place a periodic
   request to the sensor in order to take a reading.  There are
   virtually no downsides to this arrangement, and it is generally
   recommended practice.

   What is perhaps more controversial and interesting is the placement
   of intermediaries elsewhere, such as requiring an intermediary in the
   same network as the sensor devices are in.  In our example
   implementation, such an intermediary was used for both time-shifting
   purposes and to bridge the gap between addressing domains, as the
   sensor was only capable of sending messages to nearby devices with
   link-local multicast addressing.  For obvious reasons, sending
   traffic to well-known multicast groups works only on the local scale.
   Other possible reasons for using a local intermediary include
   protocol conversion and providing TCP-based congestion control for
   traffic passing through the Internet.  Where mechanisms for dealing
   with packet loss are limited, such as in the case of our
   implementation, an intermediary can also shield the sensors from
   having to deal with networks that have not been engineered for this

   There are also downsides to having to place a local intermediary.
   The obvious downside is that such a device must now exist in the
   local network.

   The use of COAP intermediaries is not fully specified, however.  Some
   of the issues we have encountered include:

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   o  COAP defines the roles for clients, servers, caches, and proxies,
      but while the specification allows an intermediary to act as
      server that stores all information sent to it, it is by no means
      specified as something that all implementations should do.  The
      desirable behavior from the point of low-power sensors would be
      that the local server would store the information from every POST
      sent to it for a period of time specified in the Max-Age option
      [I-D.ietf-core-coap], and then be able provide access to the
      information using GET and HTTP/COAP.  It would be useful to define
      such a new server role, along with specifying the necessary
      security and operational conditions for this practice.

   o  If designed badly, the intermediary may also limit the type of
      communications it can relay.  For instance, a gateway that is only
      built for a particular types of sensors might only accept very
      specific COAP messages.  In particular, intermediaries need to
      support any type of resource identifiers and data formats.
      Further discussion of this can be found in Section 4.3.

   o  In several CoAP applications the user is interested in the latest
      value of a resource, but historical values are also interesting in
      several use cases, e.g. tracking the movements of a truck during
      the day.  Thus, the information stored in the cache/gateway should
      not expire.  Even if a new value is received every minute, old
      values should be accessible and new value should not overwrite the
      old value.  For this kind of cases, schemas for representing also
      historical values of the sensor would be useful for
      interoperability.  Of course, simple schemas are easy to implement
      even if there did not exist any standards or recommendations, but
      again, there will not be interoperability.

   o  If the information is such that it should expire after some time,
      Max-Age option can be used as defined [I-D.ietf-core-coap].
      However, [I-D.ietf-core-coap] discusses Max-Age option only in the
      context of responses.  In the multicast use case (sensor the one
      sending requests), Max-Age option would be needed to be supported
      in requests, too.

   o  Multicast requests, particiularly GETs, might be forwarded by
      several proxies and possibly even to further multicast addresses,
      causing a storm of messages.  The COAP specification does not
      describe when the forwarding of multicast requests is appropriate
      and when it is not.

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4.2.  COAP Messaging

   The interaction model of COAP is similar to the client/server model
   in HTTP.  A sensor can act either as a client that sends requests
   containing updated measurement information to a server, or as a
   server that responds to requests from others.  If the sensor is a
   server, it can either employ the basic communication model from
   [I-D.ietf-core-coap] or use the observation framework
   [I-D.ietf-core-observe].  This section looks at the energy efficiency
   implications of these models.

   It is important to make this analysis not merely based on the data
   transmission phase, but also based on what discovery actions and
   related signaling may be necessary.

4.2.1.  Client Model

   In this model, a sensor acts as a client that periodically sends POST
   requests containing updated measurement information to a server.
   This is the model that we used in our example implementation.

      User or                Sensor
    Intermediary            (Client)
      (Server)                 .
         |                     .
         |                     .
         |                  wake-up
         |                     |
         |     NON/POST        |
         |     content         |
         |                     |
         |                power-down
         |                     .
         |     NON/RSP         .
         |----------------/    .
         |                     .

    Figure 1. Send-only client model

   In its simplest form, this model can be reduced to sending a single
   message per observation period, however this comes at the cost of:

   o  Limited support for reliable transmission.  Messages may arrive
      out of order and they may go missing without notice.  While
      periodic retransmissions do provide a statistical likelihood that
      the transmission eventually succeeds, they do not guarantee it.

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   o  Possible spurious diagnostic or other problems caused by not being
      able to receive the REST level response to the POST message that
      the server will send (see Section 3.4).

   Both of these problems can be addressed by forcing the device to wait
   for a response, incurring the cost of having to be awake for 1 RTT
   for each observation period.  Using the assumptions from Section 3.5
   and a 2 ms RTT for a local intermediary to respond, the power usage
   of this model would be either two times more or 0.2% more, depending,
   again, on whether the send/receive power differences are factored in.

      User or                Sensor
    Intermediary            (Client)
      (Server)                 .
         |                     .
         |                     .
         |                  wake-up
         |                     |
         |     CON/POST        |
         |     content         |
         |                     |
         |     ACK/RSP         |
         |                     |
         |                power-down
         |                     .
         |                     .

   Figure 2. Send-and-confirm client model

   (Interestingly, a similar model could be implemented even with HTTP.
   With TCP, one additional roundtrip and one additional message would
   be necessary to start the communications.  This model would be
   roughly twice as power hungry as the COAP alternative.  Note at least
   in the implementation strategy that was used in our example
   implementation, the format differences between COAP and HTTP would
   make little difference for implementation complexity, as messages are
   created based on pre-filled packet templates.  Supporting TCP would
   require some complexity, however.)

   In addition, there is an added factor, having to discover the right
   peer to send messages to.  In our example implementation this was
   simply a well-known multicast address, in which case no additional
   power is spent.  The downside is that this can easily be done only
   with local multicast, necessitating the existence of suitable
   intermediary in the same network.  Alternatively, the sensor could

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   run a discovery phase at installation time to find the addresses of
   the peers wishing to receive the information.  This discovery would
   have to repeated in order to account for changes and new equipment.
   Nevertheless, if discovery is run once a day and uses the same amount
   of power as sending one data observation, the increased power
   requirements are in the order of 0.1%, i.e., negligible.

4.2.2.  Server Model

   In the basic server model as defined in [I-D.ietf-core-coap], the
   sensor waits for requests from a client.  The power requirements for
   this model have been analyzed in Section 3.5 and are substantially
   higher than in any other model, even if one takes into account that
   listening is less power intensive than sending.

      User or                Sensor
    Intermediary            (Server)
         |                     |
         |     CON/GET         |
         |                     |
         |     ACK/RSP         |
         |     content         |
         |                     |

         Figure 3. Server model.

   There may be an additional discovery exchange where the sensor
   responds to requests sent for the well-known resources defined in
   [I-D.ietf-core-link-format].  However, these additional exchanges do
   not change power requirements significantly, as the sensor already
   has to be awake at all times.  A more relevant concern is perhaps
   unwanted or accidental traffic to the sensor or one of the multicast
   addresses it belongs to (such as all-nodes [RFC4291]).  Such traffic
   may have to be replied to or ICMP error messages may have to be sent,
   consuming additional energy.

   The server model is not recommended.  Variations of the model may be
   a little bit more efficient, however.  For instance, a local server
   could send multiple requests in an effort to randomly hit a period
   when the sensor is powered up.  However, such practices would still
   generate a lot of traffic in the network, which might not be
   desirable.  For instance, if the network involves low-powered RPL
   routers [I-D.ietf-roll-rpl], extra traffic would be harmful.

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4.2.3.  Observer Model

   The observer model [I-D.ietf-core-observe] allows clients to decide
   what information they want and servers to decide when to send that
   information.  The model involves an initial registration, followed by
   the server sending periodic notifications.  These notifications can
   be timed appropriately, so that the sensor only needs to wake up at
   suitable times.

      User or                  Sensor
    Intermediary              (Server)
         |                       |
         |  NON/GET              |
         |  observe registration |
         |                       |
         |                  power-down
         |                       .
         |                       .
         |                       .
         |  NON/RSP           wake-up
         |  content              |
         |                       |
         |                  power-down
         |                       .
         |                       .
         |                       .
         |  NON/RSP           wake-up
         |  content              |
         |                       |
         |                  power-down
         |                       .
         |                       .

        Figure 4. Observer model.

   On the face of it, this is a very efficient model.  Unfortunately,
   one has to take into account the registration phase.  For this model
   to work, the sensor has to first be able to receive a registration
   request, and later be able to receive further requests in case there
   are changes or additional clients that want information.  As a
   result, a straightforward implementation of the observe framework
   would appear to save no energy at all compared to the server model.
   The sensor would still have to stay awake all the time.  Again, this

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   model is not recommended.

   Optimizations of the observer model are of course possible.
   Transmitting multiple registration requests is less damaging than
   transmitting multiple data requests, as the registration is only a
   one-time event.  Nevertheless, for interoperability, it would be
   useful to understand what timelines and retransmission counts should
   be followed by both servers and clients.  For instance, a sensor
   could assume that it has to be up one second out of every minute.
   This would increase power consumption compared to the send-only model
   as described in Section 3.5.  Users or intermediaries interested in
   subscribing to the information from the sensor would on the average
   have to re-transmit registration requests thirty times to randomly
   hit the period that a particular sensor is awake.

   Another possible optimization would be the definition of implicit
   subscriptions where for some application a certain subscription would
   always be assumed so that a sensor can start sending periodic
   notifications immediately to a well-known address.  With such a model
   the notifications are carried as responses and an intermediary can
   act as a COAP cache, avoiding most of the issues from the above

   In addition, we have found a few more specific issues with the
   observer model:

   o  There is no well-defined termination period.  The consumer of the
      information can observe that information is still flowing to it as
      expected.  However, when non-confirmable messages are used, the
      sensor sending the notifications has no knowledge if the receiver
      is still even in the network.  As a result, a simple
      implementation that keeps sending information until an explicit
      unsubscription is not desirable, as the sensor may have to send
      more messages than is necessary.

   o  Section 3.2 of [I-D.ietf-core-observe] specifies that a
      registration request from the same source address but a different
      port is considered a new, additional request.  This can be
      problematic if the client reboots and assigns a different port
      number for its communication with the server.

   o  Section 3.3 of [I-D.ietf-core-observe] makes it optional for a
      server to terminate the observation request when a GET request is
      sent without the Observe option.  This makes it hard for a client
      to indicate to the server that it is no longer interested in the

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   o  Section 3.3 of [I-D.ietf-core-observe] specifies that a
      subscription can be terminated using a RST message.  This makes it
      impossible to know if the receiver rejects a confirmable
      notification because some context was missing or because the
      receiver wants to terminate the subscription.

4.3.  Resources and Data Formats

   The choice of resource identifiers (URIs) and data formats is
   important to achieve semantic interoperability between a sensor and
   an application using it.  It is not enough to transport some data for
   some object, the parties involved in the application have to
   understand that the information comes from, say, a particular
   temperature sensor and that the information contains a temperature
   value encoded in a particular way.

   The choice of URIs is clear as far as COAP transport is concerned in
   the server model.  Here the Link Format [I-D.ietf-core-link-format]
   can be used by clients to find out what URIs exist.  Nevertheless,
   there are two remaining concerns:

   o  The authors of this memo found it desirable to implement a new URI
      type to represent device identities, such as MAC addresses or
      1-wire device identifiers.  While UUIDs [RFC4122] can also be used
      for this purpose, they are more complex for no additional value
      from the point of view of our application.  UUIDs are required to
      contain a time component, which would cause both additional
      implementation complexity, as well as make it more difficult to
      correlate identifiers from a manufacturer's list or printed on the
      outside of the sensor to the ones actually sent in the network.
      (Such correlation is often required in order to configure the
      real-world location of various sensors.).  The new URI type is
      simply of the form "device:ID", where ID is the hardware address
      associated with the device.  Such an URI could have uses not only
      in sensor networks, but also in cataloging network equipment, etc.

   o  While the Link Format provides a way to determine what resources
      exist, the semantics of those resources and data formats still
      require standardization.  Some work regarding such standardization
      is ongoing, e.g. in ZigBee IP Smart Energy 2.0 Profile, but it
      remains to be seen how much work is needed overall.  This problem
      might become even more real when sensors from particular
      application areas, such as electrical cars or lightning, are being
      implemented.  Without any common schemas or data models no
      interoperability can be provided.

   o  It is also important to care about the size and complexity of the
      data models developed for low-power applications.  Even if moving

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      from HTTP to COAP and some form of compression saves some number
      of bytes, complicated XML models can easily consume the savings
      and more.  The authors have found [I-D.jennings-senml] a workable,
      simple model.

   In addition, in the client model it becomes important that the server
   (local intermediary) is capable of storing information about any
   resource when it receives a POST request.  This is not necessarily
   the case.  First, it is unclear what resource identifiers the client
   should use, particularly when multicast is used.  Our example
   implementation employed a well-known URI "/publish" and placed the
   identity of the device sending the request inside the payload part of
   the request along with the sensor readings.  But it is not clear that
   this is the best approach, and furthermore, such an approach has not
   been standardized so it may not work with all devices.  As an
   example, in one of the COAP stacks that we tried, it is only possible
   to generate resources by a user under a root resource called
   "storage".  This requirement makes it incompatible with other
   implementations we tried.

4.4.  Configuration

   One overriding concern in networks with large number of sensors is
   configuration effort.  In addition, the sensors are typically
   deployed in homes and other environments where the necessary skills
   for installation and operational tasks cannot be assumed.  As a
   result, it is important that at installation of individual sensors
   leads to little or no configuration effort.  Furthermore, given the
   small physical size and lack of user interfaces, it is essential that
   any configuration be doable on other devices on behalf of the

   A good model for configuration is that the sensors are fully factory-
   configured with respect to their identities and capable of operating
   autonomously in any IP network with suitable network interfaces.
   Typically, some configuration information is required but this can be
   provided as additional information associated with a particular
   sensor identity, and configured in the application server or
   intermediary.  For instance, the physical location of a sensor can be
   configured in this manner.

   From the point of view of the COAP protocol and its communication
   model, this means that the sensors should operate as much as possible
   based on autoconfigured addresses, well-known destinations and/or
   resource discovery [I-D.ietf-core-link-format]
   [I-D.shelby-core-resource-directory].  COAP should also allow
   configuration and passing of additional information in

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5.  Security Considerations

   Support for authentication of sensors, integrity of messages sent by
   sensors, or protection of the data objects carried by the messages
   would be useful in some environments, while physical security and
   link-layer protection may be sufficient in others.  Mechanisms for
   these security mechanisms are for further study.

6.  Conclusions

   This memo has analyzed the power requirements for sensor applications
   through an example implementation that runs on absolute minimum power
   and through an analysis of various different more general
   communications models.

   The general conclusion is that the chosen communications model and
   overall system and network architecture is far more important for low
   power usage than details of the message formats.  Much of the work in
   COAP has focused on the latter rather than the former.  Even the
   difference between COAP and HTTP transactions is small compared to
   the difference between choosing the optimal and worst communications

   In particular, we would like to draw attention to system-level
   analysis to ensure that nodes can stay asleep for as long as
   necessary.  This is particularly important when designing power-
   efficient data transmission models such as the observe framework.  It
   is not enough for the data transmission itself to be efficient if the
   device needs to stay awake or communicate for other reasons
   (Section 4.2.3).  Several other more detailed observations about the
   COAP specifications were also noted in Section 3.3, Section 4.1,
   Section 4.2, Section 4.3, and Section 4.4.

   The communication model is also not just about finding the most
   efficient sequence of messages.  It is very much also an
   architectural decision.  The authors believe that an information-
   centric or delay-tolerant networking model is appropriate for
   collecting information from sensor networks.  These models allow
   communications based on identities, support intermittent
   connectivity, focus on data rather than the location of the data, and
   have the natural ability for nodes to aggregate, store, and process
   data.  Some of the tasks for ensuring that such models can be
   employed with COAP include

   o  Definition of URI types suitable to be used in sensor networks.

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   o  Accurate specification of multicast support.

   o  Specifications for intermediary behavior so that they can store
      and process data from sensors.

   o  Further standardization of data formats and application semantics.

   Finally, it should be noted that the conclusions in this memo should
   not be interpreted to apply too widely.  Actuators and other, non-
   sensor low-power device implementations have likely very different
   requirements and may require different solutions.

7.  References

7.1.  Normative References

              Shelby, Z., Hartke, K., Bormann, C., and B. Frank,
              "Constrained Application Protocol (CoAP)",
              draft-ietf-core-coap-06 (work in progress), May 2011.

              Shelby, Z., "CoRE Link Format",
              draft-ietf-core-link-format-05 (work in progress),
              May 2011.

              Hartke, K. and Z. Shelby, "Observing Resources in CoAP",
              draft-ietf-core-observe-02 (work in progress), March 2011.

   [RFC1624]  Rijsinghani, A., "Computation of the Internet Checksum via
              Incremental Update", RFC 1624, May 1994.

   [RFC2460]  Deering, S. and R. Hinden, "Internet Protocol, Version 6
              (IPv6) Specification", RFC 2460, December 1998.

   [RFC4291]  Hinden, R. and S. Deering, "IP Version 6 Addressing
              Architecture", RFC 4291, February 2006.

7.2.  Informative References

   [RFC2131]  Droms, R., "Dynamic Host Configuration Protocol",
              RFC 2131, March 1997.

   [RFC2710]  Deering, S., Fenner, W., and B. Haberman, "Multicast
              Listener Discovery (MLD) for IPv6", RFC 2710,
              October 1999.

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   [RFC3810]  Vida, R. and L. Costa, "Multicast Listener Discovery
              Version 2 (MLDv2) for IPv6", RFC 3810, June 2004.

   [RFC4122]  Leach, P., Mealling, M., and R. Salz, "A Universally
              Unique IDentifier (UUID) URN Namespace", RFC 4122,
              July 2005.

   [RFC4541]  Christensen, M., Kimball, K., and F. Solensky,
              "Considerations for Internet Group Management Protocol
              (IGMP) and Multicast Listener Discovery (MLD) Snooping
              Switches", RFC 4541, May 2006.

   [RFC4627]  Crockford, D., "The application/json Media Type for
              JavaScript Object Notation (JSON)", RFC 4627, July 2006.

   [RFC4861]  Narten, T., Nordmark, E., Simpson, W., and H. Soliman,
              "Neighbor Discovery for IP version 6 (IPv6)", RFC 4861,
              September 2007.

   [RFC4862]  Thomson, S., Narten, T., and T. Jinmei, "IPv6 Stateless
              Address Autoconfiguration", RFC 4862, September 2007.

              Sperberg-McQueen, C., Bray, T., and J. Paoli, "XML 1.0
              Recommendation", World Wide Web Consortium
              FirstEdition REC-xml-19980210, February 1998,

              Shelby, Z. and S. Krco, "CoRE Resource Directory",
              draft-shelby-core-resource-directory-00 (work in
              progress), June 2011.

              Winter, T., Thubert, P., Brandt, A., Clausen, T., Hui, J.,
              Kelsey, R., Levis, P., Pister, K., Struik, R., and J.
              Vasseur, "RPL: IPv6 Routing Protocol for Low power and
              Lossy Networks", draft-ietf-roll-rpl-19 (work in
              progress), March 2011.

              Jennings, C., "Media Type for Sensor Markup Language
              (SENML)", draft-jennings-senml-05 (work in progress),
              March 2011.

              Arkko, J., "Interoperability Concerns in the Internet of
              Things", Position paper at the IAB workshop on Smart

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              Objects , March 2011, <

Appendix A.  Acknowledgments

   The authors would like to thank to Magnus Westerlund, Ari Keranen,
   Stig Venaas, Zach Shelby, Cullen Jennings, Vlasios Tsiatsis, Jan
   Holler, Anders Eriksson, and Joel Halpern for their help and for
   interesting discussions in this problem space.

Authors' Addresses

   Jari Arkko
   Jorvas  02420


   Heidi-Maria Rissanen
   Jorvas  02420


   Salvatore Loreto
   Jorvas  02420


   Zoltan Turanyi
   Irinyi Jozsef u. 4-20.


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   Oscar Novo
   Jorvas  02420


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