Internet-Draft CNN Terminology April 2022
Bormann, et al. Expires 7 October 2022 [Page]
LWIG Working Group
Intended Status:
C. Bormann
Universität Bremen TZI
M. Ersue
A. Keranen
C. Gomez
Universitat Politecnica de Catalunya

Terminology for Constrained-Node Networks


The Internet Protocol Suite is increasingly used on small devices with severe constraints on power, memory, and processing resources, creating constrained-node networks. This document provides a number of basic terms that have been useful in the standardization work for constrained-node networks.

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This Internet-Draft will expire on 7 October 2022.

1. Introduction

Small devices with limited CPU, memory, and power resources, so-called "constrained devices" (often used as sensors/actuators, smart objects, or smart devices) can form a network, becoming "constrained nodes" in that network. Such a network may itself exhibit constraints, e.g., with unreliable or lossy channels, limited and unpredictable bandwidth, and a highly dynamic topology.

Constrained devices might be in charge of gathering information in diverse settings, including natural ecosystems, buildings, and factories, and sending the information to one or more server stations. They might also act on information, by performing some physical action, including displaying it. Constrained devices may work under severe resource constraints such as limited battery and computing power, little memory, and insufficient wireless bandwidth and ability to communicate; these constraints often exacerbate each other. Other entities on the network, e.g., a base station or controlling server, might have more computational and communication resources and could support the interaction between the constrained devices and applications in more traditional networks.

Today, diverse sizes of constrained devices with different resources and capabilities are becoming connected. Mobile personal gadgets, building-automation devices, cellular phones, machine-to-machine (M2M) devices, and other devices benefit from interacting with other "things" nearby or somewhere in the Internet. With this, the Internet of Things (IoT) becomes a reality, built up out of uniquely identifiable and addressable objects (things). Over the next decade, this could grow to large numbers of Internet-connected constrained devices ([IoT-2025] predicts that by, 2025, more than 2500 devices will be connected to the Internet per second), greatly increasing the Internet's size and scope.

The present document provides a number of basic terms that have been useful in the standardization work for constrained environments. The intention is not to exhaustively cover the field but to make sure a few core terms are used consistently between different groups cooperating in this space.

The present document is a revision of [RFC7228].

In this document, the term "byte" is used in its now customary sense as a synonym for "octet". Where sizes of semiconductor memory are given, the prefix "kibi" (1024) is combined with "byte" to "kibibyte", abbreviated "KiB", for 1024 bytes [ISQ-13]. Powers of 10 are given as 10100 where 100 is the exponent.

In computing, the term "power" is often used for the concept of "computing power" or "processing power", as in CPU performance. In this document, the term stands for electrical power unless explicitly stated otherwise. "Mains-powered" is used as a shorthand for being permanently connected to a stable electrical power grid.

2. Core Terminology

There are two important aspects to scaling within the Internet of Things:

  • scaling up Internet technologies to a large number [IoT-2025] of inexpensive nodes, while
  • scaling down the characteristics of each of these nodes and of the networks being built out of them, to make this scaling up economically and physically viable.

The need for scaling down the characteristics of nodes leads to "constrained nodes".

2.1. Constrained Nodes

The term "constrained node" is best defined by contrasting the characteristics of a constrained node with certain widely held expectations on more familiar Internet nodes:

Constrained Node:

A node where some of the characteristics that are otherwise pretty much taken for granted for Internet nodes at the time of writing are not attainable, often due to cost constraints and/or physical constraints on characteristics such as size, weight, and available power and energy. The tight limits on power, memory, and processing resources lead to hard upper bounds on state, code space, and processing cycles, making optimization of energy and network bandwidth usage a dominating consideration in all design requirements. Also, some layer-2 services such as full connectivity and broadcast/multicast may be lacking.

While this is not a rigorous definition, it is grounded in the state of the art and clearly sets apart constrained nodes from server systems, desktop or laptop computers, powerful mobile devices such as smartphones, etc. There may be many design considerations that lead to these constraints, including cost, size, weight, and other scaling factors.

(An alternative term, when the properties as a network node are not in focus, is "constrained device".)

There are multiple facets to the constraints on nodes, often applying in combination, for example:

  • constraints on the maximum code complexity (ROM/Flash),
  • constraints on the size of state and buffers (RAM),
  • constraints on the amount of computation feasible in a period of time ("processing power"),
  • constraints on the available power, and
  • constraints on user interface and accessibility in deployment (ability to set keys, update software, etc.).

Section 3 defines a number of interesting classes ("class-N") of constrained nodes focusing on relevant combinations of the first two constraints. With respect to available power, [RFC6606] distinguishes "power-affluent" nodes (mains-powered or regularly recharged) from "power-constrained nodes" that draw their power from primary batteries or by using energy harvesting; more detailed power terminology is given in Section 4.

The use of constrained nodes in networks often also leads to constraints on the networks themselves. However, there may also be constraints on networks that are largely independent of those of the nodes. We therefore distinguish "constrained networks" from "constrained-node networks".

2.2. Constrained Networks

We define "constrained network" in a similar way:

Constrained Network:

A network where some of the characteristics pretty much taken for granted with link layers in common use in the Internet at the time of writing are not attainable.

Constraints may include:

  • low achievable bitrate/throughput (including limits on duty cycle),
  • high packet loss and high variability of packet loss (delivery rate),
  • highly asymmetric link characteristics,
  • severe penalties for using larger packets (e.g., high packet loss due to link-layer fragmentation),
  • limits on reachability over time (a substantial number of devices may power off at any point in time but periodically "wake up" and can communicate for brief periods of time), and
  • lack of (or severe constraints on) advanced services such as IP multicast.

More generally, we speak of constrained networks whenever at least some of the nodes involved in the network exhibit these characteristics.

Again, there may be several reasons for this:

  • cost constraints on the network,
  • constraints posed by the nodes (for constrained-node networks),
  • physical constraints (e.g., power constraints, environmental constraints, media constraints such as underwater operation, limited spectrum for very high density, electromagnetic compatibility),
  • regulatory constraints, such as very limited spectrum availability (including limits on effective radiated power and duty cycle) or explosion safety, and
  • technology constraints, such as older and lower-speed technologies that are still operational and may need to stay in use for some more time.

2.2.1. Challenged Networks

A constrained network is not necessarily a "challenged network" [FALL]:

Challenged Network:

A network that has serious trouble maintaining what an application would today expect of the end-to-end IP model, e.g., by:

  • not being able to offer end-to-end IP connectivity at all,
  • exhibiting serious interruptions in end-to-end IP connectivity, or
  • exhibiting delay well beyond the Maximum Segment Lifetime (MSL) defined by TCP [RFC0793].

All challenged networks are constrained networks in some sense, but not all constrained networks are challenged networks. There is no well-defined boundary between the two, though. Delay-Tolerant Networking (DTN) has been designed to cope with challenged networks [RFC4838].

2.3. Constrained-Node Networks

Constrained-Node Network:

A network whose characteristics are influenced by being composed of a significant portion of constrained nodes.

A constrained-node network always is a constrained network because of the network constraints stemming from the node constraints, but it may also have other constraints that already make it a constrained network.

The rest of this subsection introduces two additional terms that are in active use in the area of constrained-node networks, without an intent to define them: LLN and (6)LoWPAN.

2.3.1. LLN

A related term that has been used to describe the focus of the IETF ROLL working group is "Low-Power and Lossy Network (LLN)". The ROLL (Routing Over Low-Power and Lossy) terminology document [RFC7102] defines LLNs as follows:

  • LLN: Low-Power and Lossy Network. Typically composed of many embedded devices with limited power, memory, and processing resources interconnected by a variety of links, such as IEEE 802.15.4 or low-power Wi-Fi. There is a wide scope of application areas for LLNs, including industrial monitoring, building automation (heating, ventilation, and air conditioning (HVAC), lighting, access control, fire), connected home, health care, environmental monitoring, urban sensor networks, energy management, assets tracking, and refrigeration.

Beyond that, LLNs often exhibit considerable loss at the physical layer, with significant variability of the delivery rate, and some short-term unreliability, coupled with some medium-term stability that makes it worthwhile to both (1) construct directed acyclic graphs that are medium-term stable for routing and (2) do measurements on the edges such as Expected Transmission Count (ETX) [RFC6551]. Not all LLNs comprise low-power nodes [I-D.hui-vasseur-roll-rpl-deployment].

LLNs typically are composed of constrained nodes; this leads to the design of operation modes such as the "non-storing mode" defined by RPL (the IPv6 Routing Protocol for Low-Power and Lossy Networks [RFC6550]). So, in the terminology of the present document, an LLN is a constrained-node network with certain network characteristics, which include constraints on the network as well.

2.3.2. LoWPAN, 6LoWPAN

One interesting class of a constrained network often used as a constrained-node network is "LoWPAN" [RFC4919], a term inspired from the name of an IEEE 802.15.4 working group (low-rate wireless personal area networks (LR-WPANs)). The expansion of the LoWPAN acronym, "Low-Power Wireless Personal Area Network", contains a hard-to-justify "Personal" that is due to the history of task group naming in IEEE 802 more than due to an orientation of LoWPANs around a single person. Actually, LoWPANs have been suggested for urban monitoring, control of large buildings, and industrial control applications, so the "Personal" can only be considered a vestige. Occasionally, the term is read as "Low-Power Wireless Area Networks" [WEI]. Originally focused on IEEE 802.15.4, "LoWPAN" (or when used for IPv6, "6LoWPAN") also refers to networks built from similarly constrained link-layer technologies [RFC7668] [RFC8105] [RFC7428] [RFC9159].

2.3.3. LPWAN

An overview over Low-Power Wide Area Network (LPWAN) technologies is provided by [RFC8376].

3. Classes of Constrained Devices

Despite the overwhelming variety of Internet-connected devices that can be envisioned, it may be worthwhile to have some succinct terminology for different classes of constrained devices.

Before we get to that, let's first distinguish two big rough groups of devices based on their CPU capabilities:

  • Microcontroller-class devices (sometimes called "M-class"). These often (but not always) include RAM and code storage on chip and would struggle to support more powerful general-purpose operating systems, e.g., they do not have an MMU (memory management unit). They use most of their pins for interfaces to application hardware such as digital in/out (the latter often Pulse Width Modulation (PWM)-controllable), ADC/DACs (analog-to-digital and digital-to-analog converters), etc. Where this hardware is specialized for an application, we may talk about "Systems on a Chip" (SOC). These devices often implement elaborate sleep modes to achieve microwatt- or at least milliwatt-level sustained power usage (Ps, see below).
  • General-purpose-class devices (sometimes called "A-class"). These usually have RAM and Flash storage on separate chips (not always separate packages), and offer support for general-purpose operating systems such as Linux, e.g. an MMU. Many of the pins on the CPU chip are dedicated to interfacing with RAM and other memory. Some general-purpose-class devices integrate some application hardware such as video controllers, these are often also called "Systems on a Chip" (SOC). While these chips also include sleep modes, they are usually more on the watt side of sustained power usage (Ps).

If the distinction between these groups needs to be made in this document, we distinguish group "M" (microcontroller) from group "J" (general purpose).

In this document, the class designations in Table 1 may be used as rough indications of device capabilities. Note that the classes from 10 upwards are not really constrained devices in the sense of the previous section; they may still be useful to discuss constraints in larger devices:

Table 1: Classes of Constrained Devices (KiB = 1024 bytes)
Group Name data size (e.g., RAM) code size (e.g., Flash) Examples
M Class 0, C0 << 10 KiB << 100 KiB ATtiny
M Class 1, C1 ~ 10 KiB ~ 100 KiB STM32F103CB
M Class 2, C2 ~ 50 KiB ~ 250 KiB STM32F103RC
M Class 3, C3 ~ 100 KiB ~ 500..1000 KiB STM32F103RG
M Class 4, C4 ~ 300..1000 KiB ~ 1000..2000 KiB "Luxury"
J Class 10, C10 (16..)32..64..128 MiB 4..8..16 MiB OpenWRT routers
J Class 15, C15 0.5..1 GiB (lots) Raspberry PI
J Class 16, C16 1..4 GiB (lots) Smartphones
J Class 17, C17 4..32 GiB (lots) Laptops
J Class 19, C19 (lots) (lots) Servers

As of the writing of this document, these characteristics correspond to distinguishable clusters of commercially available chips and design cores for constrained devices. While it is expected that the boundaries of these classes will move over time, Moore's law tends to be less effective in the embedded space than in personal computing devices: gains made available by increases in transistor count and density are more likely to be invested in reductions of cost and power requirements than into continual increases in computing power. (This effect is less pronounced in the multi-chip J-group architectures; e.g., class 10 usage for OpenWRT has started at 4/16 MiB Flash/RAM, with an early lasting minimum at 4/32, to now requiring 8/64 and preferring 16/128 for modern software releases [W432].)

Class 0 devices are very constrained sensor-like motes. They are so severely constrained in memory and processing capabilities that most likely they will not have the resources required to communicate directly with the Internet in a secure manner (rare heroic, narrowly targeted implementation efforts notwithstanding). Class 0 devices will participate in Internet communications with the help of larger devices acting as proxies, gateways, or servers. Class 0 devices generally cannot be secured or managed comprehensively in the traditional sense. They will most likely be preconfigured (and will be reconfigured rarely, if at all) with a very small data set. For management purposes, they could answer keepalive signals and send on/off or basic health indications.

Class 1 devices are quite constrained in code space and processing capabilities, such that they cannot easily talk to other Internet nodes employing a full protocol stack such as using HTTP, Transport Layer Security (TLS), and related security protocols and XML-based data representations. However, they are capable enough to use a protocol stack specifically designed for constrained nodes (such as the Constrained Application Protocol (CoAP) over UDP [RFC7252]) and participate in meaningful conversations without the help of a gateway node. In particular, they can provide support for the security functions required on a large network. Therefore, they can be integrated as fully developed peers into an IP network, but they need to be parsimonious with state memory, code space, and often power expenditure for protocol and application usage.

Class 2 devices are less constrained and fundamentally capable of supporting most of the same protocol stacks as used on notebooks or servers. However, even these devices can benefit from lightweight and energy-efficient protocols and from consuming less bandwidth. Furthermore, using fewer resources for networking leaves more resources available to applications. Thus, using the protocol stacks defined for more constrained devices on Class 2 devices might reduce development costs and increase the interoperability.

Constrained devices with capabilities significantly beyond Class 2 devices exist. They are less demanding from a standards development point of view as they can largely use existing protocols unchanged. The previous version of the present document therefore did not make any attempt to define constrained classes beyond Class 2. These devices, and to a certain extent even J-group devices, can still be constrained by a limited energy supply. Class 3 and 4 devices are less clearly defined than the lower classes; they are even less constrained. In particular Class 4 devices are powerful enough to quite comfortably run, say, JavaScript interpreters, together with elaborate network stacks. Additional classes may need to be defined based on protection capabilities, e.g., an MPU (memory protection unit; true MMUs are typically only found in J-group devices).

With respect to examining the capabilities of constrained nodes, particularly for Class 1 devices, it is important to understand what type of applications they are able to run and which protocol mechanisms would be most suitable. Because of memory and other limitations, each specific Class 1 device might be able to support only a few selected functions needed for its intended operation. In other words, the set of functions that can actually be supported is not static per device type: devices with similar constraints might choose to support different functions. Even though Class 2 devices have some more functionality available and may be able to provide a more complete set of functions, they still need to be assessed for the type of applications they will be running and the protocol functions they would need. To be able to derive any requirements, the use cases and the involvement of the devices in the application and the operational scenario need to be analyzed. Use cases may combine constrained devices of multiple classes as well as more traditional Internet nodes.

3.1. Firmware/Software upgradability

Platforms may differ in their firmware or software upgradability. The below is a first attempt at classifying this.

Table 2: Levels of software update capabilities
Name Firmware/Software upgradability
F0 no (discard for upgrade)
F1 replaceable, out of service during replacement, reboot
F2 patchable during operation, reboot required
F3 patchable during operation, restart not visible externally
F9 app-level upgradability, no reboot required ("hitless")

3.2. Isolation functionality

TBD. This section could discuss the ability of the platform to isolate different components. The categories below are not mutually exclusive; we need to build relevant clusters.

Table 3: Levels of isolation capabilities
Name Isolation functionality
Is0 no isolation
Is2 MPU (memory protection unit), at least boundary registers
Is5 MMU with Linux-style kernel/user
Is7 Virtualization-style isolation
Is8 Secure enclave isolation

3.3. Shielded secrets

[Need to identify clusters]

Some platforms can keep shielded secrets (usually in conjunction with secure enclave functionality).

Table 4: Levels of secret shielding capabilities
Name Secret shielding functionality
Sh0 no secret shielding
Sh1 some secret shielding
Sh9 perfect secret shielding

4. Power Terminology

Devices not only differ in their computing capabilities but also in available power and/or energy. While it is harder to find recognizable clusters in this space, it is still useful to introduce some common terminology.

4.1. Scaling Properties

The power and/or energy available to a device may vastly differ, from kilowatts to microwatts, from essentially unlimited to hundreds of microjoules.

Instead of defining classes or clusters, we simply state, using the International System of Units (SI units), an approximate value for one or both of the quantities listed in Table 5:

Table 5: Quantities Relevant to Power and Energy
Name Definition SI Unit
Ps Sustainable average power available for the device over the time it is functioning W (Watt)
Et Total electrical energy available before the energy source is exhausted J (Joule)

The value of Et may need to be interpreted in conjunction with an indication over which period of time the value is given; see Section 4.2.

Some devices enter a "low-power" mode before the energy available in a period is exhausted or even have multiple such steps on the way to exhaustion. For these devices, Ps would need to be given for each of the modes/steps.

4.2. Classes of Energy Limitation

As discussed above, some devices are limited in available energy as opposed to (or in addition to) being limited in available power. Where no relevant limitations exist with respect to energy, the device is classified as E9. The energy limitation may be in total energy available in the usable lifetime of the device (e.g., a device that is discarded when its non-replaceable primary battery is exhausted), classified as E2. Where the relevant limitation is for a specific period, the device is classified as E1, e.g., a solar-powered device with a limited amount of energy available for the night, a device that is manually connected to a charger and has a period of time between recharges, or a device with a periodic (primary) battery replacement interval. Finally, there may be a limited amount of energy available for a specific event, e.g., for a button press in an energy-harvesting light switch; such devices are classified as E0. Note that, in a sense, many E1 devices are also E2, as the rechargeable battery has a limited number of useful recharging cycles.

Table 6 provides a summary of the classifications described above.

Table 6: Classes of Energy Limitation
Name Type of energy limitation Example Power Source
E0 Event energy-limited Event-based harvesting
E1 Period energy-limited Battery that is periodically recharged or replaced
E2 Lifetime energy-limited Non-replaceable primary battery
E9 No direct quantitative limitations to available energy Mains-powered

4.3. Strategies for Using Power for Communication

Especially when wireless transmission is used, the radio often consumes a big portion of the total energy consumed by the device. Design parameters, such as the available spectrum, the desired range, and the bitrate aimed for, influence the power consumed during transmission and reception; the duration of transmission and reception (including potential reception) influence the total energy consumption.

Different strategies for power usage and network attachment may be used, based on the type of the energy source (e.g., battery or mains-powered) and the frequency with which a device needs to communicate.

The general strategies for power usage can be described as follows:


This strategy is most applicable if there is no reason for extreme measures for power saving. The device can stay on in the usual manner all the time. It may be useful to employ power-friendly hardware or limit the number of wireless transmissions, CPU speeds, and other aspects for general power-saving and cooling needs, but the device can be connected to the network all the time.


Under this strategy, the device sleeps such long periods at a time that once it wakes up, it makes sense for it to not pretend that it has been connected to the network during sleep: the device reattaches to the network as it is woken up. The main optimization goal is to minimize the effort during the reattachment process and any resulting application communications.

If the device sleeps for long periods of time and needs to communicate infrequently, the relative increase in energy expenditure during reattachment may be acceptable.


This strategy is most applicable to devices that need to operate on a very small amount of power but still need to be able to communicate on a relatively frequent basis. This implies that extremely low-power solutions need to be used for the hardware, chosen link-layer mechanisms, and so on. Typically, given the small amount of time between transmissions, despite their sleep state, these devices retain some form of attachment to the network. Techniques used for minimizing power usage for the network communications include minimizing any work from re-establishing communications after waking up and tuning the frequency of communications (including "duty cycling", where components are switched on and off in a regular cycle) and other parameters appropriately.

Table 7 provides a summary of the strategies described above.

Table 7: Strategies of Using Power for Communication
Name Strategy Ability to communicate
P0 Normally-off Reattach when required
P1 Low-power Appears connected, perhaps with high latency
P9 Always-on Always connected

Note that the discussion above is at the device level; similar considerations can apply at the communications-interface level. This document does not define terminology for the latter.

A term often used to describe power-saving approaches is "duty-cycling". This describes all forms of periodically switching off some function, leaving it on only for a certain percentage of time (the "duty cycle").

[RFC7102] only distinguishes two levels, defining a Non-Sleepy Node as a node that always remains in a fully powered-on state (always awake) where it has the capability to perform communication (P9) and a Sleepy Node as a node that may sometimes go into a sleep mode (a low-power state to conserve power) and temporarily suspend protocol communication (P0); there is no explicit mention of P1.

4.4. Strategies of Keeping Time over Power Events

Many applications for a device require it to keep some concept of time.

Time-keeping can be relative to a previous event (last packet received), absolute on a device-specific scale (e.g., last reboot), or absolute on a world-wide scale ("wall-clock time").

Some devices lose the concept of time when going to sleep: after wakeup, they don't know how long they slept. Some others do keep some concept of time during sleep, but not precise enough to use as a basis for keeping absolute time. Some devices have a continuously running source of a reasonably accurate time (often a 32,768 Hz watch crystal). Finally, some devices can keep their concept of time even during a battery change, e.g., by using a backup battery or a supercapacitor to power the real-time clock (RTC).

The actual accuracy of time may vary, with errors ranging from tens of percent from on-chip RC oscillators (not useful for keeping absolute time, but still useful for, e.g., timing out some state) to approximately 10-4 to 10-5 ("watch crystal") of error. More precise timing is available with temperature compensated crystal oscillators (TCXO). Further improvement requires significantly higher power usage, bulk, fragility, and device cost, e.g. oven-controlled crystal oscillators (OCXO) can reach 10-8 accuracy, and Rubidium frequency sources can reach 10-11 over the short term and 10-9 over the long term.

A device may need to fire up a more accurate frequency source during wireless communication, this may also allow it to keep more precise time during the period.

The various time sources available on the device can be assisted by external time input, e.g. via the network using the NTP protocol [RFC5905]. Information from measuring the deviation between external input and local time source can be used to increase the accuracy of maintaining time even during periods of no network use.

Errors of the frequency source can be compensated if known (calibrated against a known better source, or even predicted, e.g., in a software TCXO). Even with errors partially compensated, an uncertainty remains, which is the more fundamental characteristic to discuss.

Battery solutions may allow the device to keep a wall-clock time during its entire life, or the wall-clock time may need to be reset after a battery change. Even devices that have a battery lasting for their lifetime may not be set to wall-clock time at manufacture time, possibly because the battery is only activated at installation time where time sources may be questionable or because setting the clock during manufacture is deemed too much effort.

Devices that keep a good approximation of wall-clock time during their life may be in a better position to securely validate external time inputs than devices that need to be reset episodically, which can possibly be tricked by their environment into accepting a long-past time, for instance with the intent of exploiting expired security assertions such as certificates.

From a practical point of view, devices can be divided at least on the two dimensions proposed in Table 8 and Table 9. Corrections to the local time of a device performed over the network can be used to improve the uncertainty exhibited by these basic device classes.

Table 8: Strategies of Keeping Time over Power Events
Name Type Uncertainty (roughly)
T0 no concept of time infinite
T1 relative time while awake (usually high)
T2 relative time (usually high during sleep)
T3 relative time 10-4 or better
T5 absolute time (e.g., since boot) 10-4 or better
T7 wall-clock time 10-4 or better
T8 wall-clock time 10-5 or better
T9 wall-clock time 10-6 or better (TCXO)
T10 wall-clock time 10-7 or better (OCXO or Rb)
Table 9: Permanency of Keeping Time
Name Permanency (from type T5 upwards): Uncertainty
TP0 time needs to be reset on certain occasions  
TP1 time needs to be set during installation (possibly reduced...
TP9 reliable time is maintained during lifetime using external input)

Further parameters that can be used to discuss clock quality can be found in Section 3.5 of [I-D.ietf-cbor-time-tag].

5. Classes of Networks

5.2. Class of Internet Integration

The term "Internet of Things" is sometimes confusingly used for connected devices that are not actually employing Internet technology. Some devices do use Internet technology, but only use it to exchange packets with a fixed communication partner ("device-to-cloud" scenarios, see also Section 2.2 of [RFC7452]). More general devices are prepared to communicate with other nodes in the Internet as well.

We define the following classes of Internet technology level:

Table 11
Name Internet technology
I0 none (local interconnect only)
I1 device-to-cloud only
I9 full Internet connectivity supported

5.3. Classes of physical layer bit rate

[This section is a trial balloon. We could also talk about burst rate, sustained rate; bits/s, messages/s, ...]

Physical layer technologies used by constrained devices can be categorized on the basis of physical layer (PHY) bit rate. The PHY bit rate class of a technology has important implications with regard to compatibility with existing protocols and mechanisms on the Internet, responsiveness to frame transmissions and need for header compression techniques.

We define the following classes of PHY bit rate:

Table 12
Name PHY bit rate (bit/s) Comment
B0 < 10 Transmission time of 150-byte frame > MSL
B1 10 -- 103 Unresponsiveness if human expects reaction to sent frame (frame size > 62.5 byte)
B2 103 -- 106 Responsiveness if human expects reaction to sent frame, but header compression still needed
B3 > 106 Header compression yields relatively low performance benefits

(note: 'Bx' stands for 'Bit rate x')

B0 technologies lead to very high transmission times, which may be close to or even greater than the Maximum Segment Lifetime (MSL) assumed on the Internet [RFC0793]. Many Internet protocols and mechanisms will fail when transmit times are greater than the MSL. B0 technologies lead to a frame transmission time greater than the MSL for a frame size greater than 150 bytes.

B1 technologies offer transmission times which are lower than the MSL (for a frame size greater than 150 bytes). However, transmission times for B1 technologies are still significant if a human expects a reaction to the transmission of a frame. With B1 technologies, the transmission time of a frame greater than 62.5 bytes exceeds 0.5 seconds, i.e. a threshold time beyond which any response or reaction to a frame transmission will appear not to be immediate [RFC5826].

B2 technologies do not incur responsiveness problems, but still benefit from using header compression techniques (e.g. [RFC6282]) to achieve performance improvements.

Over B3 technologies, the relative performance benefits of header compression are low. For example, in a duty-cycled technology offering B3 PHY bit rates, energy consumption decrease due to header compression may be comparable with the energy consumed while in a sleep interval. On the other hand, for B3 PHY bit rates, a human user will not be able to perceive whether header compression has been used or not in a frame transmission.

6. IANA Considerations

This document makes no requests to IANA.

7. Security Considerations

This document introduces common terminology that does not raise any new security issues. Security considerations arising from the constraints discussed in this document need to be discussed in the context of specific protocols. For instance, Section 11.6 of [RFC7252], "Constrained node considerations", discusses implications of specific constraints on the security mechanisms employed. [RFC7416] provides a security threat analysis for the RPL routing protocol. Implementation considerations for security protocols on constrained nodes are discussed in [RFC7815] and [I-D.ietf-lwig-tls-minimal]. A wider view of security in constrained-node networks is provided in [RFC8576].

8. Informative References

Fall, K., "A Delay-Tolerant Network Architecture for Challenged Internets", SIGCOMM 2003, DOI 10.1145/863955.863960, , <>.
Vasseur, J., Hui, J., Dasgupta, S., and G. Yoon, "RPL deployment experience in large scale networks", Work in Progress, Internet-Draft, draft-hui-vasseur-roll-rpl-deployment-01, , <>.
Bormann, C., Gamari, B., and H. Birkholz, "Concise Binary Object Representation (CBOR) Tags for Time, Duration, and Period", Work in Progress, Internet-Draft, draft-ietf-cbor-time-tag-00, , <>.
Kumar, S. S., Keoh, S. L., and H. Tschofenig, "A Hitchhiker's Guide to the (Datagram) Transport Layer Security Protocol for Smart Objects and Constrained Node Networks", Work in Progress, Internet-Draft, draft-ietf-lwig-tls-minimal-01, , <>.
Rosen, M. and IDC, "Driving the Digital Agenda Requires Strategic Architecture", , <>. Slide 11
International Electrotechnical Commission, "International Standard -- Quantities and units -- Part 13: Information science and technology", IEC 80000-13, .
Postel, J., "Transmission Control Protocol", STD 7, RFC 793, DOI 10.17487/RFC0793, , <>.
Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst, R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant Networking Architecture", RFC 4838, DOI 10.17487/RFC4838, , <>.
Kushalnagar, N., Montenegro, G., and C. Schumacher, "IPv6 over Low-Power Wireless Personal Area Networks (6LoWPANs): Overview, Assumptions, Problem Statement, and Goals", RFC 4919, DOI 10.17487/RFC4919, , <>.
Montenegro, G., Kushalnagar, N., Hui, J., and D. Culler, "Transmission of IPv6 Packets over IEEE 802.15.4 Networks", RFC 4944, DOI 10.17487/RFC4944, , <>.
Brandt, A., Buron, J., and G. Porcu, "Home Automation Routing Requirements in Low-Power and Lossy Networks", RFC 5826, DOI 10.17487/RFC5826, , <>.
Mills, D., Martin, J., Ed., Burbank, J., and W. Kasch, "Network Time Protocol Version 4: Protocol and Algorithms Specification", RFC 5905, DOI 10.17487/RFC5905, , <>.
Hui, J., Ed. and P. Thubert, "Compression Format for IPv6 Datagrams over IEEE 802.15.4-Based Networks", RFC 6282, DOI 10.17487/RFC6282, , <>.
Winter, T., Ed., Thubert, P., Ed., Brandt, A., Hui, J., Kelsey, R., Levis, P., Pister, K., Struik, R., Vasseur, JP., and R. Alexander, "RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks", RFC 6550, DOI 10.17487/RFC6550, , <>.
Vasseur, JP., Ed., Kim, M., Ed., Pister, K., Dejean, N., and D. Barthel, "Routing Metrics Used for Path Calculation in Low-Power and Lossy Networks", RFC 6551, DOI 10.17487/RFC6551, , <>.
Kim, E., Kaspar, D., Gomez, C., and C. Bormann, "Problem Statement and Requirements for IPv6 over Low-Power Wireless Personal Area Network (6LoWPAN) Routing", RFC 6606, DOI 10.17487/RFC6606, , <>.
Vasseur, JP., "Terms Used in Routing for Low-Power and Lossy Networks", RFC 7102, DOI 10.17487/RFC7102, , <>.
Bormann, C., Ersue, M., and A. Keranen, "Terminology for Constrained-Node Networks", RFC 7228, DOI 10.17487/RFC7228, , <>.
Shelby, Z., Hartke, K., and C. Bormann, "The Constrained Application Protocol (CoAP)", RFC 7252, DOI 10.17487/RFC7252, , <>.
Tsao, T., Alexander, R., Dohler, M., Daza, V., Lozano, A., and M. Richardson, Ed., "A Security Threat Analysis for the Routing Protocol for Low-Power and Lossy Networks (RPLs)", RFC 7416, DOI 10.17487/RFC7416, , <>.
Brandt, A. and J. Buron, "Transmission of IPv6 Packets over ITU-T G.9959 Networks", RFC 7428, DOI 10.17487/RFC7428, , <>.
Tschofenig, H., Arkko, J., Thaler, D., and D. McPherson, "Architectural Considerations in Smart Object Networking", RFC 7452, DOI 10.17487/RFC7452, , <>.
Nieminen, J., Savolainen, T., Isomaki, M., Patil, B., Shelby, Z., and C. Gomez, "IPv6 over BLUETOOTH(R) Low Energy", RFC 7668, DOI 10.17487/RFC7668, , <>.
Kivinen, T., "Minimal Internet Key Exchange Version 2 (IKEv2) Initiator Implementation", RFC 7815, DOI 10.17487/RFC7815, , <>.
Mariager, P., Petersen, J., Ed., Shelby, Z., Van de Logt, M., and D. Barthel, "Transmission of IPv6 Packets over Digital Enhanced Cordless Telecommunications (DECT) Ultra Low Energy (ULE)", RFC 8105, DOI 10.17487/RFC8105, , <>.
Farrell, S., Ed., "Low-Power Wide Area Network (LPWAN) Overview", RFC 8376, DOI 10.17487/RFC8376, , <>.
Garcia-Morchon, O., Kumar, S., and M. Sethi, "Internet of Things (IoT) Security: State of the Art and Challenges", RFC 8576, DOI 10.17487/RFC8576, , <>.
Minaburo, A., Toutain, L., Gomez, C., Barthel, D., and JC. Zuniga, "SCHC: Generic Framework for Static Context Header Compression and Fragmentation", RFC 8724, DOI 10.17487/RFC8724, , <>.
Gomez, C., Darroudi, S.M., Savolainen, T., and M. Spoerk, "IPv6 Mesh over BLUETOOTH(R) Low Energy Using the Internet Protocol Support Profile (IPSP)", RFC 9159, DOI 10.17487/RFC9159, , <>.
"Warning about 4/32 devices", OpenWRT wiki, last accessed 2021-12-01, <>.
Shelby, Z. and C. Bormann, "6LoWPAN: the Wireless Embedded Internet", Wiley-Blackwell monograph, DOI 10.1002/9780470686218, ISBN 9780470747995, , <>.

Authors' Addresses

Carsten Bormann
Universität Bremen TZI
Postfach 330440
D-28359 Bremen
Mehmet Ersue
Ari Keranen
Hirsalantie 11
FI-02420 Jorvas
Carles Gomez
Universitat Politecnica de Catalunya
C/Esteve Terradas, 7
08860 Castelldefels