# United States Department of Commerce

# National Institute of Standards and Technology

# National Telecommunications and Information Administration

# 

# [Request for Comments on Deployment of Internet Protocol, Version 6]{.underline}

**Comments Submitted by**

> **Geoff Huston,**
>
> **Research Scientist, Asia Pacific Network Information Centre**

These comments are intended to address the issues raised in Section II
A, regarding estimates of how many IPv4 address have been allocated, how
many are still available, and how long the remaining address space will
continue to meet the needs of users in the United States, as well as
users in other countries around the world.

> The Request for Comment cites in a footnote a presentation I made to
> the APNIC Open Policy Meeting in August 2003. I would like to submit
> the following commentary as an explanation of the methodology used, as
> well as providing an update on the projections of IPv4 consumption
> incorporating data up to the end of February 2004.

### Summary

This study examines the available data concerning the consumption of
IPv4 addresses, looking at the allocation data published by the Internet
Assigned Numbers Authority (IANA), the allocation data published by the
Regional Internet Registries (RIRs) and the address span encompassed by
advertisements within the Internet global routing system.

The study examines the trends of consumption since and examines whether
the current consumption trends are best modeled using an exponential or
a linear growth trend. The study concludes that the best model of the
current consumption rates of address space can be found in an analysis
of the global routing table, and the best fit model is that of linear
growth.

It concludes that the IPv4 world, in terms of address availability,
could continue up to 2030 without reaching any fixed boundary of address
exhaustion. However, in forming this model a number of relatively
sweeping assumptions have been made, and to combine them as is done here
is pushing the predictive exercise to its limits, or possibly beyond
them. Three decades out is way over the event horizon for any form of
useful prediction for the Internet If the question is restricted to the
next decade (i.e. up to 2014), then we can answer with some level of
confidence that there is really no visible evidence of IPv4 exhausting
its address pool based on the available address consumption data.

The conclusion drawn here is that if the prime driver for the adoption
of IPv6 lies in a looming shortage of public IPv4 addresses, then this
is not a near term prospect, and any impetus for the adoption for IPv6
would need to be based on factors other than an imminent exhaustion of
IPv4 address space.

### Introduction

The IPv4 address pool is of finite size, and, as the IPv4 Internet grows
it makes continual demands on previously unallocated address space. It
is possible to pose the question of \"How long can the IPv4 address pool
last in the face of a continual growth in the demand for addresses?\"

This submission looks at one approach to attempt to provide some
indication of when the IPv4 address pool is likely to be exhausted as a
consequence of this continued demand for addresses, and describes the
various assumptions that have been made in order to make this
prediction.

### Predictions of Address Consumption

> Predicting the point of IPv4 address exhaustion was first undertaken
> within the IETF in the early 1990s[^1] as part of an exercise in
> looking at the future requirements of the Internet in terms of both
> address space and routing capabilities. The initial outcomes of the
> consequent IETF activities to alleviate the pressure on the address
> pool were clearly visible by the mid-1990\'s: the Classless address
> architecture (Classless Inter-Domain Routing, or "CIDR") was very
> effective in improving the address utilization efficiency, and the
> pressures of ever-increasing consumption of a visibly finite address
> resource were alleviated. The IETF actions to address the longer term
> requirements of address space was of course IPv6.

### Distributing the Address Space

There are three stages in address distribution. The pool of IP addresses
is managed by the Internet Assigned Numbers Authority (IANA). Blocks of
address space have been defined through standards actions of the IETF
for use as global unicast addresses, private-use unicast addresses,
multicast addresses, reserved for future actions, and other blocks are
marked as reserved, and are not to be used outside of local host
contexts.

Currently there are 3,707,764,736 addresses that are managed as global
unicast addresses. It is probably easier to look at this in terms of the
number of \"/8 blocks\" where each block is the same size as the old
Class A network, namely 16,777,216 addresses. The total global unicast
address pool is 221 /8s, with a further 16 /8s reserved for multicast
use, 16 /8s held in reserve, and 3 /8s are designated as not for use in
the public Internet. (Figure 1)

![](media/image1.wmf){width="4.577083333333333in"
height="2.1243055555555554in"}

Figure 1 -- Breakdown of IPv4 address space

The process of address management is that the IETF defines the global
unicast address pool to the IANA. IANA allocates blocks of global
unicast addresses to Regional Internet Registries (RIRs). The RIRs
allocate address blocks to Local Internet Registries (LIRs) or Internet
Service Providers (ISPs). These address blocks are then advertised in
the Internet's Border Gateway Protocol (BGP) routing table (Figure 2).

![](media/image2.wmf){width="3.3652777777777776in"
height="2.3027777777777776in"}

Figure 2 -- Address Distribution Framework

In looking at futures there are three distinct questions concerning
address consumption:

-   How quickly is the IANA passing address blocks to the RIRs, and when
    will IANA run out?

-   How quickly are the RIRs passing address blocks to LIRs, and when
    will this run out?

-   How much address space is actually used in the global Internet, and
    how quickly is this growing? The related question is when will
    demand for addresses outstrip the available address pool?

### 

### 

### The IANA Registry

The first data set to examine is the [IANA registry
file[^2]](http://www.iana.org/assignments/ipv4-address-space). This
registry indicates that of these 221 /8 blocks 86 /8 blocks are still
held as unallocated by the IANA, 133.9 /8 blocks have been allocated.
(Figure 3).

![](media/image3.wmf){width="4.386111111111111in"
height="2.877083333333333in"}

Figure 3 -- Address Pool with RIR Allocations

The IANA registry also includes the date of allocation of the address
block, so it's possible to construct a time series of IANA allocations.
(Figure 4)

![](media/image4.wmf){width="6.59375in" height="4.036111111111111in"}

Figure 4 - Time Series of IANA Allocations

Interestingly, there is nothing older than 1991 in this registry. This
exposes one of the problems with analyzing registry data, in that there
is a difference between the current status of a registry, and a
time-stamped log of the transactions that were made to the registry over
time. The data published by the IANA is somewhere between the two. The
log of data is incomplete, and the current status of some address blocks
is unclear. It appears that reliable allocation data starts in 1995. So
if we take the data starting from 1995 and perform a linear regression
to find a best fit of an exponential projection, its possible to make
some predictions as to the time it will take to exhaust the remaining
unallocated 89 /8s. (Figure 5).

![](media/image5.wmf){width="6.6in" height="4.55in"}

Figure 5 - Projection of IANA Allocations

It is worth a slight digression into the method of projection being used
here. The technique is one of using a least squares technique to find a
best fit of an exponential growth curve to the data. The underlying
assumption behind such exponential projections is that the growth rate
of the data is proportional to the size of the data, rather than being a
constant rate. In network terms, this assumes that the rate of
consumption of unallocated addresses is some constant proportion of the
number of allocated addresses, or, in other words, the expansion rate of
the network is a proportion of its size, rather than being a constant
value. Such exponential growth models may not necessarily be the best
fit to a network growth model, although the data since 1995 does appear
to correlate reasonably to an underlying exponential growth pattern.
Whether this growth model will continue into the future is an open
issue. It is also possible to fit a linear growth model to the data, in
which case the projected exhaustion point shifts from 2019 to 2027.

The projection of 2019 as the date for exhaustion of the IANA
unallocated address space pool using this exponential growth model is
perhaps surprising, as its seems that the network is bigger now than
ever, yet the amount of additional address space required to fuel
further accelerating growth for a further decade is comparatively small.

There are a number of reasons why this is the case, and the turning
point when these aspects gained traction in the Internet appeared to be
around 1995. They include:

-   The first 1.6 billion addresses (equivalent to some 100 /8 blocks)
    were allocated using the Class-based address architecture. Since
    this date address allocation has used a classless architecture, and
    this has allowed for significantly improved efficiencies to be
    achieved in using the address space.

-   The Regional Internet Registries (RIRs) assumed responsibility for
    address allocation, and started using conservation-based policies in
    determining allocations. The RIR process requires each address
    applicant to demonstrate that they can make efficient and effective
    use of the address space, and this dampened some of the wilder sets
    of expectations about an enterprise's address requirements.

-   Address Compression technologies became widely deployed. Dynamic
    Network Address Translation devices (NATs) have, for better or
    worse, become a common part of the network landscape. NATs allow
    large \'semi-private\' networks to use a very small poll of public
    addresses as the external view of the network, while using private
    address space within the network. Dynamic Host Configuration
    Protocol (DHCP) has allowed networks to recycle a smaller pool of
    addresses across a larger set of intermittently-connected devices.

Whether these factors will continue to operate in the same fashion in
the future is an open question. Whether future growth in the use of
public address space operates from a basis of a steadily accelerating
growth is also an open question. The assumption made in this exercise is
that the projections depend in continuity of effectiveness of the RIR
policies and their application, continuity of technology approaches and
absence of disruptive triggers. While the RIRs have a very well regarded
track record and there are strong grounds for confidence that this will
continue, the latter two assumptions about technology and disruptive
events are not as certain.

### The Regional Internet Registries

The RIRs also publish a registry of their transactions in \"delegated\"
files. For each currently allocated address block the RIR registry
contains the date of the RIR allocation transaction[^3], and the country
or region that was the location of the LIR or ISP. Using this data we
can break up the 133.9 /8 blocks further, and its evident that the
equivalent of 120.8 /8 blocks have been allocated or assigned by the
RIRs, and the remaining space, where there is no RIR allocation or
assignment record is the equivalent of 13.1 /8 blocks. (Figure 6)

![](media/image6.wmf){width="4.7027777777777775in"
height="3.004166666666667in"}

Figure 6 -- RIR Assigned Address Pool

These transactions can again be placed in a time series, as shown below
(Figure 7).

![](media/image7.wmf){width="6.6in" height="4.292361111111111in"}

Figure 7 - Time Series of RIR Assignments

The post-1995 data used to extrapolate forward using the same linear
regression technique described above, to find a curve of best bit using
the same underlying exponential growth model assumptions:

![](media/image8.wmf){width="6.595833333333333in"
height="4.466666666666667in"}

Figure 8 - Projection of RIR Assignments

This form of extrapolation gives a date of 2026 for the time at which
the RIRs will exhaust the global unicast address pool. Again the same
caveats about the use of this approach as a reliable predictor apply
here, and the view forward is based on the absence of large scale
disruptions, or some externally-induced change in the underlying growth
models for address demand.

> It is useful to consider why the IANA consumption rate appears to be
> higher than the RIR consumption rate, and why there is a difference of
> some 7 years in the predicted exhaustion dates between the two data
> sets. There are a number of factors that contribute to this
> difference. The first is that the IANA pool is considered exhausted at
> the point in time when the last available /8 block is allocated to an
> RIR, while the RIR pool is considered to be exhausted at the time when
> the last available address block is allocated to an ISP. This implies
> that the other RIRs would have exhausted their pool at a slightly
> earlier point in time. Secondly the RIR practice of using assignment
> windows to allow subsequent allocations to the same ISP to be
> aggregated into a single routing advertisement implies that the RIR
> address pool is fragmented, leading to a slightly higher rate of draw
> down from the IANA unallocated address pool. Also, as the number of
> RIRs increases (such as with LACNIC in 2003 and the potential
> recognition of AFRINIC in the near future) the total amount of address
> space held in RIR pools increases. However, the most likely reason for
> the difference is to be found in the data sets themselves. The IANA
> data set consists of 129 data points with a date granularity no finer
> than one month, and of this data set, only the most recent 29 points
> (post 1995) are used in the IANA prediction. The RIR delegated files
> span some 30,000 entries, with a granularity of one day. The larger
> data set with a finer level of granularity tends to suggest that a
> slightly higher level of confidence can be ascribed to the predictive
> model of the RIR delegation data as distinct to the relatively sparse
> data set and coarse granularity of the IANA data.

### The BGP Routing Table

> Once addresses are assigned to end networks, the expectation is that
> these addresses will be announced to the network in the form of
> routing advertisements. So some proportion of these addresses is
> announced in the Internet\'s routing table. The next step is to
> establish the trends of the amount address space covered by the
> routing table. The approach used has been to take a single view of the
> address span of the Internet. This is the view from one point, inside
> the AS1221 network operated by Telstra[^4].
>
> The data as of October 2003 shows that some 29% of the total IPv4
> address space is announced in the BGP routing table, while 17% has
> been allocated to an end user or LIR but is not announced on the
> public Internet as being connected and reachable. A total of 5% of the
> address space is held by the RIRs pending assignment or allocation (or
> at least there is no RIR recorded assignment of the space), while 35%
> of the total space remains in the IANA unallocated pool. A further 8%
> of the space is held in reserve (Figure 9).

![](media/image9.wmf){width="4.720138888888889in"
height="3.1729166666666666in"}

Figure 9 - IPv4 Announced Address Space

This BGP data is based on an hourly inspection of the amount of address
space advertised within the Internet\'s routing table. The data
collection commenced in late 1999, and the data gathered so far is shown
in Figure 10.

![](media/image10.png){width="6.595138888888889in"
height="3.8048611111111112in"}

Figure 10 - Advertised Address Space as seen at AS1221

The problem with this data is that there is some considerable amount of
fluctuation in the amount of address space advertised over time. The
major step changes are due to a small number of /8 advertisements that
are periodically announced and withdrawn in BGP. In order to obtain
reasonable data for generating projections some noise reduction on this
data needs to be undertaken. The approached used has been to first
filter the data using a constant value of 18 /8 prefix announcements,
and then use a sliding average function to create a smoothed time
series. This is indicated in Figure 11.

![](media/image11.png){width="5.819444444444445in"
height="4.3694444444444445in"}

Figure 11 Smoothed BGP Data

The critical issue when using this data for projection is to determine
what form of function can provide a best fit to the data. A good
indication of the underlying trends in the data can be found by
analysing the first order differential of the data. An underlying
increasing growth model would have an increasing first order
differential, while a decreasing growth model would have a negatively
inclined differential. Figure 12 shows the first order differential of
the BGP data and the fit of constant growth and exponential growth
models to the data. It appears that the most consistent fit to the data
set is that of a constant growth model.

![](media/image12.png){width="5.946527777777778in"
height="4.459722222222222in"}

Figure 12. First order differential of BGP Data

It is now possible to produce two models, using constant growth and
increasing growth, that extrapolate forward to complete exhaustion of
the IPv4 address space. These models are shown in Figure 13.

![](media/image13.png){width="5.6930555555555555in" height="4.275in"}

Figure 13 IP Address Consumption models based on Routing Advertisements

The constant growth model predicts complete exhaustion in mid 2042,
while an exponential growth model has a prediction of complete
exhaustion of 2023.

### Combining the Three Views

Before completing the projections for IPv4 address space there is one
remaining question. There are 43.3 /8 blocks, or some 17% of the total
IPv4 address space which has been allocated for use, but is not visible
in the Internet\'s routing table. This is a very significant amount of
address space, and if it's growing at the same rate as the advertised
space, then this will have a significant impact on any overall model of
consumption of use of address space. The question here is whether this
\'invisible\' address pool is a legacy of the address allocations
policies in place before the RIR system can into operation in the mid
1990\'s, or some intrinsic inefficiency in the current system. If its
the latter, then its likely that this pool of unannounced addresses will
grow in direct proportion to the growth in the announced address space,
while if its the former then the pool will remain relatively constant in
size in the future.

The RIR allocation data and look at the allocation dates of unannounced
address space (Figure 14). This view indicates that the bulk of the
space is a legacy of earlier address allocation practices, and that
since 1997, when the RIR operation was fully established, there is an
almost complete mapping of RIR allocated address space to BGP routing
announcements. The recent 2003 data indicates that there is some lag
between recent allocations and BGP announcements, most probably due to
the time lag between an LIR receiving an allocation and subsequent
assignments to end users and advertisement in the routing table.

![](media/image14.png){width="6.610416666666667in"
height="3.5131944444444443in"}

Fig 14 - Age Distribution of Unadvertised Address Space

This confirms that in recent years the overall majority of the address
space that has been assigned by the RIRs appears in the Internet\'s
routing table. This in turn implies that projections of the amount of
address space advertised in the routing table provide a reasonable
correlation to underlying mechanics of address space consumption. With
this in mind it is now possible to construct a model of the address
distribution process, working backward from the BGP routing table
address size.

From the sum of the BGP table size and the pool of allocated but
unadvertised addresses it is possible to derive the total RIR-managed
address pool. To this number is added the RIR holding pool low size and
its low threshold where a further IANA-allocation is required. This
allows a view of the entire system, projected forward over time, where
the central driver for the projection is the growth in the network
itself, as described by the size of the announced IPv4 address space.
This is shown in Figure 9.

![](media/image15.wmf){width="6.590277777777778in"
height="4.044444444444444in"}

Figure 15 - Address Consumption Model

This model tracks the process of IANA allocation to the RIRs, the RIRs
operating allocation windows to their LIRs and ISPs, and LIRs and ISPs
advertising this address space to the routing system. The underlying
assumption of the growth model is that of a continuation of a constant
growth model, with a constant consumption rate of some 3.4 /8 blocks per
year. Within this mode the IANA pool will be exhausted in mid 2027, and
the RIR pool will cease to operate using allocation windows early 2028.
While there would be sufficient addresses within the allocation system
to sustain a further 5 years of RIRs drawing from their allocation
pools, it is reasonable to predict that the current address allocation
practices would be forced to change in early 2028. Accordingly, this
linear growth model predicts an effective exhaustion date of current
allocation IPv4 allocations in 2028,

> An accelerating growth model of Internet address consumption, assuming
> that the trends over the past 3 years in address consumption rates
> continue to grow at the same accelerating rate would see effective
> exhaustion occur a decade earlier, in 2018.

### Uncertainties and Assumptions

Of course such projections are based on the underlying assumption that
the visible changes that have occurred in the past will smoothly
translate to continued change the future. There are some obvious
weaknesses in this assumption, and many events could disrupt this
prediction.

Some disruptions could be found in technology evolution. An upward shift
in address take up rates could occur because of an inability of NATs to
support some new popular class of applications. Widespread deployment of
peer-to-peer applications implies the need for persistent address
presentation, which may imply greater levels of requirement for public
address space. The use of personal mobile IP devices (such as PDAs in
their various formats) using public IPv4 addresses would place a massive
load on the address space, simply due to the very large volumes
associated with deployment of this particular technology[^5].

Other disruptions have a social origin, such as the boom and bust cycle
of Internet expansion in recent years. Another form of disruption in
this category could be the adoption of a change in the distribution
function. The current RIR and LIR distribution model has been very
effective in limiting the amount of accumulation of address space in
holding pools, and allocating addresses based on efficiency of
utilization and conformance to the routing topology of the .network.
Many other forms of global resource distribution use a geo-political
framework, where number blocks are passed to national entities, and
further distribution is a matter of local policy[^6]. The disruptive
nature of such a change would be to immediately increase the number of
\'holding\' points in the distribution system, locking away larger pools
of address space from being deployed and advertised and generating a
significant upward change in the overall address consumption rates due
to an increase in the inefficiency of the altered distribution function.

The other factor to be aware of is the steadily decreasing \"buffer\'\"
of unallocated address that can be used to absorb the impacts of a
disruptive change in address consumption rates. While, at present, some
60% of the address space, or some 2.6 billion addresses are available in
the unallocated address pools or held in reserve, this pool will reduce
over time. If a disruptive event is, for example, a requirement to
directly address some 500 million devices , then such an event would
reduce the expectancy of address space availability by some years,
assuming it occurred within the period when there remains sufficient
address space to meet such a surge of demand.

The other source of uncertainty is that this form of predictive modeling
assumes that the ratios of actual connected devices and the amount of
address space deployed to service this device pool remain relatively
constant.

The assumption is also made that market behaviours will remain
relatively constant over the period under examination. This is a
relatively weak assumption, in that as the unallocated pool of addresses
diminishes in size it is reasonable to anticipate both an increase in
market demand for alternative technologies that have a reduced (or no)
requirement for IPv4 address space (such as IPv6), and also an emergence
of secondary address trading markets where address space distribution is
realigned to reflect a distribution that maximizes the utility value of
the address space. In this predictive investigation the externalities
associated with modified market behaviours in the face of a visibly
diminishing address resource will be assumed to have no impact on the
rate of consumption of address resources.

> This particular model also assumes some form of continuity of current
> address allocation polices. This is not a likely scenario, as it is
> likely that address policies will reflect some notion of balance
> between the level of current demand and future demands. As the
> unallocated address pool shrinks it is possible that policies will
> alter to express the increased level of competitive demand for the
> remaining resource. Consumption rates would be moderated by such a
> change in allocation policy. The commonly cited intended evolutionary
> path for the Internet is to a transition to ubiquitous use of IPv6,
> and at some point in that transition process it is reasonable to
> assume that further demands for IPv4 space will dwindle, and it may be
> that at such a \"cross over\" time allocation policies may then be
> altered to reflect a drop in both current and future demands for IPv4
> address space.

In attempting to assess the possible future path of address allocation
policies, it is also evident that the current address allocation process
does not operate as a pure market. The current address management system
assumes a steady influx of new addresses to meet emerging demands, and
the overall address utilization efficiency is not set by any form of
market force, but by the outcomes of the application of RIR address
allocation policies to new requests for address space. A market
rationalist could well point to the use of market price as a means of
determining the most economically efficient form of utilization of a
commodity product. Such a position is based on the observation that the
way that the consumer chooses between alternative substitutable services
is by a market choice that is generally price sensitive. By removing
price from an IPv4 address market the choices made by market players are
not necessarily the most efficient choices, and some would argue that
the current situation underprices IPv4 at the expense of a smooth
market-led transition into IPv6.

### IPv4 Consumption Prediction

Three factors have substantially altered the IPv4 Internet in
intervening decade since the original IETF predictions of address space
exhaustion. They are:

Dynamic Host Configuration Protocol (DHCP)

> The original IP architecture assumed that every device would be
> assigned a unique address on a persistent basis. DHCP allowed network
> administrators and service providers to maintain a pool of addresses
> and 'lend' them to devices for the period during which they were
> attached to the network. This has realized considerable savings in
> terms of address consumption. For example, in a dial-up service
> environment, the size of the required address pool is not the number
> of contracted customers of the service, but the maximal number of
> simultaneously connected customers, or, in other words, the size of
> the address pool.

Network Address Translation (NAT)

> Various host census estimates indicate that the number of devices that
> are in some fashion "attached" to the Internet is somewhere between 2
> and 3.5 billion. The total amount of address space being advertised
> within the global routing tables encompasses some 1.3 billion
> addresses. This would imply that, if the advertised address space were
> fully utilized, then the number of devices behind NATs is either equal
> to, or up to double the number of directly addresses hosts. NATs are
> very common in today's Internet. The reasons for their popularity are
> as much, if not more, to do with the level of protection they are
> perceived to offer against various forms of malicious attack as they
> have to do with their capability to undertake address compression.
> There are three commonly cited drawbacks to NAT deployment, those of
> its inability to provide protection of the packet header in the
> context of the IPSEC end-to-end security protocol, its inability to
> allow persistent services to be located within the "private " realm of
> the NAT and the inability to support application protocols that carry
> IP addresses within their payload. None of these reasons has observed
> to be an impediment to the widespread deployment of NATs.

Address Allocation Policies

> The third factor is the policies associated with the current address
> allocation function undertaken by the RIRs. The common use of an 80%
> utilization threshold as the necessary precondition for a Service
> Provider to obtain additional address resources, after the initial
> allocation, and careful management of the initial allocation requests
> to ensure that the initial allocation is capable of supporting the
> documented rollout of the network have combined to ensure that the
> policy objectives of the RIR system, those of conservation and
> responsible use of the address resource, appear to be achieved.

The assumptions used here include a continuation of the current
utilization efficiency levels in the Internet, and a continuing balance
between public address utilization and the use various forms of address
compression, continuity of current address allocation policies, as well
as the absence of highly disruptive events.

> With all this in mind, it would appear that the IPv4 Internet, in
> terms of address availability, could continue up to around 2030
> without reaching any fixed boundary of address exhaustion.

But it must be remembered that each of the assumptions made here are
relatively sweeping, and to combine them as is done here is pushing the
predictive exercise to its limits. Three decades out is well over the
event horizon for any form of useful prediction for the Internet. If the
question is restricted to the next decade (i.e. up to 2014), then we can
answer with some level of confidence that there is really no visible
evidence of IPv4 exhausting its address pool based on the available
address consumption data.

The conclusion drawn here is that if the prime driver for the adoption
of IPv6 lies in a looming shortage of public IPv4 addresses, then this
is not a near term prospect, and any impetus for the adoption for IPv6
would need to be based on factors other than an imminent exhaustion of
IPv4 address space.

### Data Sources

**IANA IPv4 Address Registry**:
http://www.iana.org/assignments/ipv4-address-space

**Registry \"delegated\" report files:**

> APNIC: ftp://ftp.apnic.net/pub/apnic/delegated
>
> ARIN: ftp://ftp.arin.net/pub/delegated
>
> LACNIC: ftp://ftp.lacnic.net/pub/delegated
>
> RIPE NCC: ftp://ftp.ripe.net/ripe/delegated

**BGP Address Data**: http://bgp.potaroo.net

[^1]: The work was undertaken in the Address Lifetime Expectations (ALE)
    Working Group of the IETF in 1993 - 1994. The final outcome from
    this effort was reported from the December 1994 meeting of this
    group: \" Both models currently suggest that IPv4 addresses would be
    depleted around 2008, give or take three years.\" This prediction
    was documented in RFC 1752. No further predictions have been
    undertaken within the IETF on this topic since that date.

    .

[^2]: This registry is online at
    http://www.iana.org/assignments/ipv4-address-space

[^3]: There are some anomalies in the consistency of registry data
    relating to the date of the allocation transaction. Some of these
    anomalies are found in historical allocations where the registry
    date is the date when the allocation entry was re-homed to the local
    RIR. Others are where the original allocation date does not appear
    to have been recorded in any location.

[^4]: It would normally be expected in a uniformly connected network
    that all addresses would be seen from all locations, and that the
    point at which the observations are being made as to the total span
    of addresses being advertised in the Internet would be immaterial.
    Analysis of routing views using "route collectors" suggests that
    this is not entirely the case, and that there are differences
    between various viewpoints. The scale of difference is not
    considered to be so large that it creates any significant
    uncertainty in the related predictive analysis based on the data.

[^5]: On the other hand it is evident that the growth of the Internet in
    recent years has been fuelled by the increasing prevalence of NATs.
    In order for applications to be accepted into common use in today\'s
    Internet they need to be able to function through various NAT-based
    constraints, and increasing sophistication of applications in
    operating across NATs is certainly evident today.

[^6]: Such a geo-political distribution system is used in the E.164
    number space for telephony.