Scalability of IPv6 Transition Technologies for IPv4aaS
draft-lencse-v6ops-transition-scalability-02
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draft-lencse-v6ops-transition-scalability-02
v6ops G. Lencse
Internet-Draft Szechenyi Istvan University
Intended status: Informational 7 March 2022
Expires: 8 September 2022
Scalability of IPv6 Transition Technologies for IPv4aaS
draft-lencse-v6ops-transition-scalability-02
Abstract
Several IPv6 transition technologies have been developed to provide
customers with IPv4-as-a-Service (IPv4aaS) for ISPs with an IPv6-only
access and/or core network. All these technologies have their
advantages and disadvantages, and depending on existing topology,
skills, strategy and other preferences, one of these technologies may
be the most appropriate solution for a network operator.
This document examines the scalability of the five most prominent
IPv4aaS technologies (464XLAT, Dual Stack Lite, Lightweight 4over6,
MAP-E, MAP-T) considering two aspects: (1) how their performance
scales up with the number of CPU cores, (2) how their performance
degrades, when the number of concurrent sessions is increased until
hardware limit is reached.
Status of This Memo
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provisions of BCP 78 and BCP 79.
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material or to cite them other than as "work in progress."
This Internet-Draft will expire on 8 September 2022.
Copyright Notice
Copyright (c) 2022 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 (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Requirements Language . . . . . . . . . . . . . . . . . . 3
2. Scalability of iptables . . . . . . . . . . . . . . . . . . . 3
2.1. Measurement Method . . . . . . . . . . . . . . . . . . . 3
2.2. Performance scale up against the number of CPU cores . . 4
2.3. Performance degradation caused by the number of
sessions . . . . . . . . . . . . . . . . . . . . . . . . 6
2.4. Connection tear down rate . . . . . . . . . . . . . . . . 8
3. Scalability of Jool . . . . . . . . . . . . . . . . . . . . . 9
3.1. Measurement Method . . . . . . . . . . . . . . . . . . . 10
3.2. Performance scale up against the number of CPU cores . . 10
3.3. Performance degradation caused by the number of
sessions . . . . . . . . . . . . . . . . . . . . . . . . 11
3.4. Connection tear down rate . . . . . . . . . . . . . . . . 12
4. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 13
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
6. Security Considerations . . . . . . . . . . . . . . . . . . . 13
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
7.1. Normative References . . . . . . . . . . . . . . . . . . 13
7.2. Informative References . . . . . . . . . . . . . . . . . 14
Appendix A. Change Log . . . . . . . . . . . . . . . . . . . . . 15
A.1. 00 . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
A.2. 01 . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Author's Address . . . . . . . . . . . . . . . . . . . . . . . . 15
1. Introduction
IETF has standardized several IPv6 transition technologies [LEN2019]
and occupied a neutral position trusting the selection of the most
appropriate ones to the market.
[I-D.ietf-v6ops-transition-comparison] provides a comprehensive
comparative analysis of the five most prominent IPv4aaS technologies
to assist operators with this problem. This document adds one more
detail: measurement data regarding the scalability of the examined
IPv4aaS technologies.
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Currently, this document contains only the scalability measurements
of the iptables stateful NAT44 implementation. It serves as a sample
to test if the disclosed results are (1) useful and (2) sufficient
for the network operators.
1.1. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in
BCP14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here.
2. Scalability of iptables
2.1. Measurement Method
[RFC8219] has defined a benchmarking methodology for IPv6 transition
technologies. [I-D.lencse-bmwg-benchmarking-stateful] has amended it
by addressing how to benchmark stateful NATxy gateways using
pseudorandom port numbers recommended by [RFC4814]. It has defined a
measurement procedure for maximum connection establishment rate and
reused the classic measurement procedures like throughput, latency,
frame loss rate, etc. from [RFC8219]. We used two of them: maximum
connection establishment rate and throughput to characterize the
performance of the examined system.
The scalability of iptables is examined in two aspects:
* How its performance scales up with the number of CPU cores?
* How its performance degrades, when the number of concurrent
sessions is increased?
+--------------------------------------+
10.0.0.2 |Initiator Responder| 198.19.0.2
+-------------| Tester |<------------+
| private IPv4| [state table]| public IPv4 |
| +--------------------------------------+ |
| |
| +--------------------------------------+ |
| 10.0.0.1 | DUT: | 198.19.0.1 |
+------------>| Sateful NAT44 gateway |-------------+
private IPv4| [connection tracking table] | public IPv4
+--------------------------------------+
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Figure 1: Test setup for benchmarking stateful NAT44 gateways
The test setup in Figure 1 was followed. The two devices, the Tester
and the DUT (Device Under Test), were both Dell PowerEdge R430
servers having two 2.1GHz Intel Xeon E5-2683 v4 CPUs, 384GB 2400MHz
DDR4 RAM and Intel 10G dual port X540 network adapters. The NICs of
the servers were interconnected by direct cables, and the CPU clock
frequecy was set to fixed 2.1 GHz on both servers. They had Debian
9.13 Linux operating system with 4.9.0-16-amd64 kernel. The
measurements were performed by siitperf [LEN2021] using the
"stateful" branch (latest commit Aug. 16, 2021). The DPDK version
was 16.11.11-1+deb9u2. The version of iptables was 1.6.0.
The ratio of number of connections in the connection tracking table
and the value of the hashsize parameter of iptables significantly
influences its performance. Although the default setting is
hashsize=nf_conntrack_max/8, we have usually set
hashsize=nf_conntrack_max to increase the performance of iptables,
which was crucial, when high number of connections were used, because
then the execution time of the tests was dominated by the preliminary
phase, when several hundereds of millions connections had to be
established. (In some cases, we had to use different settings due to
memory limitations. The tables presenting the results always contain
these parameters.)
The size of the port number pool is an important parameter of the
bechmarking method for stateful NATxy gateways, thus it is also given
for all tests.
2.2. Performance scale up against the number of CPU cores
To examine how the performance of iptables scales up with the number
of CPU cores, the number of active CPU cores was set to 1, 2, 4, 8,
16 using the "maxcpus=" kernel parameter.
The number of connections was always 4,000,000 using 4,000 different
source port numbers and 1,000 different destination port numbers.
Both the connection tracking table size and the hash table size was
set to 2^23.
The error of the binary search was chosen to be lower than 0.1% of
the expected results. The experiments were executed 10 times.
Besides the connection establishment rate and the throughput of
iptables, also the throughput of the IPv4 packet forwarding of the
Linux kernel was measured to provide a basis for comparison.
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The results are presented in Figure 2. The unit for the maximum
connection establishment rate is 1,000 connections per second. The
unit for throughput is 1,000 packets per second (measured with
bidirectional traffic, and the number of all packets per second is
displayed).
num. CPU cores 1 2 4 8 16
src ports 4,000 4,000 4,000 4,000 4,000
dst ports 1,000 1,000 1,000 1,000 1,000
num. conn. 4,000,000 4,000,000 4,000,000 4,000,000 4,000,000
conntrack t. s. 2^23 2^23 2^23 2^23 2^23
hash table size 2^23 2^23 2^23 2^23 2^23
c.t.s/num.conn. 2.097 2.097 2.097 2.097 2.097
num. experiments 10 10 10 10 10
error 100 100 100 1,000 1,000
cps median 223.5 371.1 708.7 1,341 2,383
cps min 221.6 367.7 701.7 1,325 2,304
cps max 226.7 375.9 723.6 1,376 2,417
cps rel. scale up 1 0.830 0.793 0.750 0.666
throughput median 414.9 742.3 1,379 2,336 4,557
throughput min 413.9 740.6 1,373 2,311 4,436
throughput max 416.1 746.9 1,395 2,361 4,627
tp. rel. scale up 1 0.895 0.831 0.704 0.686
IPv4 packet forwarding (using the same port number ranges)
error 200 500 1,000 1,000 1,000
throughput median 910.9 1,523 3,016 5,920 11,561
throughput min 874.8 1,485 2,951 5,811 10,998
throughput max 914.3 1,534 3,037 5,940 11,627
tp. rel. scale up 1 0.836 0.828 0.812 0.793
throughput ratio (%) 45.5 48.8 45.7 39.5 39.4
Figure 2: Scale up of iptables against the number of CPU cores
(Please refer to the next figure for the explanation of the
abbreviations.)
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abbreviation explanation
------------ -----------
num. CPU cores number of CPU cores
src ports size of the source port number range
dst ports size of the destination port number range
num. conn. number of connections = src ports * dst ports
conntrack t. s. size of the connection tracking table of the
DUT
hash table size size of the hash table of the DUT
c.t.s/num.conn. conntrack table size / number of connections
num. experiments number of experiments
error the difference between the upper and the lower
bound of the binary search when it stops
cps (median/min/max) maximum connection establishment rate
(median, minimum, maximum)
cps rel. scale up the relative scale up of the maximum connection
establishment rate against the number of CPU
cores
tp. rel. scale up the relative scale up of the throughput
throughput ratio (%) the ratio of the throughput of iptables and the
throughput of IPv4 packet forwarding
Figure 3: Explanation of the abbreviations for the scale up of
iptables against the number of CPU cores
Whereas the throughput of IPv4 packet forwarding scaled up from
0.91Mpps to 11.56Mpps showing a relative scale up of 0.793, the
throughput of iptables scaled up from 414.9kpps to 4,557kpps showing
a relative scale up of 0.686 (and the relative scale up of the
maximum connection establishment rate is only 0.666). On the one
hand, this is the price of the stateful operation. On the other
hand, this result is quite good compared to the scale-up results of
NSD (a high performance authoritative DNS server) presented in
Table 9 of [LEN2020], which is only 0.52. (1,454,661/177,432=8.2-fold
performance using 16 cores.) And DNS is not a stateful technology.
2.3. Performance degradation caused by the number of sessions
To examine how the performance of iptables degrades with the number
connections in the connection tracking table, the number of
connections was increased fourfold by doubling the size of both the
source port number range and the destination port number range. Both
the connection tracking table size and the hash table size was also
increased four fold. However, we reached the limits of the hardware
at 400,000,000 connections: we could not set the size of the hash
table to 2^29 but only to 2^28. The same value was used at
800,000,000 connections too, when the number of connections was only
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doubled, because 1.6 billion connections would not fit into the
memory.
The error of the binary search was chosen to be lower than 0.1% of
the expected results. The experiments were executed 10 times (except
for the very long lasting measurements with 800,000,000 connections).
The results are presented in Figure 4. The unit for the maximum
connection establishment rate is 1,000,000 connections per second.
The unit for throughput is 1,000,000 packets per second (measured
with bidirectional traffic, and the number of all packets per second
is displayed).
num. conn. 1.56M 6.25M 25M 100M 400M 800M
src ports 2,500 5,000 10,000 20,000 40,000 40,000
dst ports 625 1,250 2,500 5,000 10,000 20,000
conntrack t. s. 2^21 2^23 2^25 2^27 2^29 2^30
hash table size 2^21 2^23 2^25 2^27 2^28 2^28
num. exp. 10 10 10 10 10 5
error 1,000 1,000 1,000 1,000 1,000 1,000
n.c./h.t.s. 0.745 0.745 0.745 0.745 1.490 2.980
cps median 2.406 2.279 2.278 2.237 2.013 1.405
cps min 2.358 2.226 2.226 2.124 1.983 1.390
cps max 2.505 2.315 2.317 2.290 2.050 1.440
throughput med. 5.326 4.369 4.510 4.516 4.244 3.689
throughput min 5.217 4.240 3.994 4.373 4.217 3.670
throughput max 5.533 4.408 4.572 4.537 4.342 3.709
Figure 4: Performance of iptables against the number of sessions
The performance of iptables shows degradation at 6.25M connections
compared to 1.56M connections very likely due to the exhaustion of
the L3 cache of the CPU of the DUT. Then the performance of iptables
is fearly constant up to 100M connections. A small performance
decrease can be observed at 400M connections due to the lower hash
table size. A more significant performance decrease can be observed
at 800M connections. It is caused by two factors:
* on average, about 3 connections were hashed to the same place
* non NUMA local memory was also used.
We note that the CPU has 2 NUMA nodes, cores 0, 2, ... 14 belong to
NUMA node 0, and cores 1, 3, ... 15 belong to NUMA node 1. The
maximum memory consumption with 400,000,000 connections was below
150GB, thus it could be stored in NUMA local memory.
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Therefore, we have pointed out important limitations of the stateful
NAT44 technology:
* there is a performance decrease, when approaching hardware limits
* there is a hardware limit, beyond which the system cannot handle
the connections at all (e.g. 1600M connections would not fit into
the memory).
Therefore, we can conclude that, on the one hand, a well tailored
hashing may guarantee an excellent scale-up of stateful NAT44
regarding the number of connections in a wide range, however, on the
other hand, stateful operation has its limits resulting both in
performance decrease, when approaching hardware limits and also in
inability to handle more sessions, when reaching the memory limits.
2.4. Connection tear down rate
[I-D.lencse-bmwg-benchmarking-stateful] has defined connection tear
down rate measurement as an aggregate measurement, that is, N number
of connections are loaded into the connection tracking table of the
DUT and then the entire content of the connection tracking table is
deleted, and its deletion time is measured (T). Finally, the
connection tear down rate is computed as: N/T.)
We have observed that the deletion of an empty connection tracking
table of iptables my take a significant amount of time depending on
its size. Therefore, we made our measurements more accurate by
subtracting the deletion time of the empty connection tracking table
from that of the filled one, thus we got the time spent with the
deleting of the connections.
The same setup and parameters were used as in Section 2.3 and the
experiments were executed 10 times (except for the long lasting
measurements with 800,000,000 connections).
The results are presented in Figure 5.
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num. conn. 1.56M 6.35M 25M 100M 400M 800M
src ports 2,500 5,000 10,000 20,000 40,000 40,000
dst ports 625 1,250 2,500 5,000 10,000 20,000
conntrack t. s. 2^21 2^23 2^25 2^27 2^29 2^30
hash table size 2^21 2^23 2^25 2^27 2^28 2^28
num. exp. 10 10 10 10 10 5
n.c./h.t.s. 0.745 0.745 0.745 0.745 1.490 2.980
full contr. del med 4.33 18.05 74.47 305.33 1,178.3 2,263.1
full contr. del min 4.25 17.93 72.04 299.06 1,164.0 2,259.6
full contr. del max 4.38 18.20 75.13 310.05 1,188.3 2,275.2
empty contr. del med 0.55 1.28 4.17 15.74 31.2 31.2
empty contr. del min 0.55 1.26 4.16 15.73 31.1 31.1
empty contr. del max 0.57 1.29 4.22 15.79 31.2 31.2
conn. deletion time 3.78 16.77 70.30 289.59 1,147.2 2,232.0
conn. tear d. rate 413,360 372,689 355,619 345,316 348,690 358,429
Figure 5: Connetion tear down rate of iptables against the number of
connections
The connection tear down performance of iptables shows significant
degradation at 6.25M connections compared to 1.56M connections very
likely due to the exhaustion of the L3 cache of the CPU of the DUT.
Then it shows only a minor degradation up to 100M connections. A
small performance increase can be observed at 400M connections due to
the relatively lower hash table size. A more visible performance
decrease can be observed at 800M connections. It is likely caused by
keeping the hash table size constant and doubling the number of
connections. The same thing that caused performance degradation of
the maximum connection establishment rate and throughput, made now
the deletion of the connections faster and thus caused an increase of
the connection tear down rate.
We note that according to the recommended settings of iptables, 8
connections are hashed to each place of the hash table on average,
but we wilfully used much smaller number (0.745 whenever it was
possible) to increase the maximum connection estabilishment rate and
thus to speed up experimenting. However, finally this choice
significantly slowed down our experiments due to the very low
connection tear down rate.
3. Scalability of Jool
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3.1. Measurement Method
The same methodology was used as in Section 2, but now the test setup
in Figure 6 was followed. The same Tester and DUT devices were used
as before, but the operating system of the DUT was updated to Debian
10.11 with 4.19.0-18-amd64 kernel to meet the requirement of the
jool-tools package. The version of Jool was 4.1.6. (The most mature
version of Jool at the date of starting the measurements, Relase
Date: 2021-12-10.)
+--------------------------------------+
2001:2::2 |Initiator Responder| 198.19.0.2
+-------------| Tester |<------------+
| IPv6 address| [state table]| IPv4 address|
| +--------------------------------------+ |
| |
| +--------------------------------------+ |
| 2001:2::1 | DUT: | 198.19.0.1 |
+------------>| Sateful NAT64 gateway |-------------+
IPv6 address| [connection tracking table] | IPv4 address
+--------------------------------------+
Figure 6: Test setup for benchmarking stateful NAT64 gateways
Unlike with iptables, we did not find any way to tune the hashsize or
any other parameters of Jool.
3.2. Performance scale up against the number of CPU cores
The number of connections was always 1,000,000 using 2,000 different
source port numbers and 500 different destination port numbers.
The error of the binary search was chosen to be lower than 0.1% of
the expected results. The experiments were executed 10 times.
The results are presented in Figure 7. The unit for the maximum
connection establishment rate is 1,000 connections per second. The
unit for throughput is 1,000 packets per second (measured with
bidirectional traffic, and the number of all packets per second is
displayed).
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num. CPU cores 1 2 4 8 16
src ports 2,000 2,000 2,000 2,000 2,000
dst ports 500 500 500 500 500
num. conn. 1,000,000 1,000,000 1,000,000 1,000,000 1,000,000
num. experiments 10 10 10 10 10
error 100 100 100 100 100
cps median 228.6 358.5 537.4 569.9 602.6
cps min 226.5 352.5 530.7 562.0 593.7
cps max 230.5 362.4 543 578.3 609.7
cps rel. scale up 1 0.784 0.588 0.312 0.165
throughput median 251.8 405.7 582.4 604.1 612.3
throughput min 249.8 402.9 573.2 587.3 599.8
throughput max 253.3 409.6 585.7 607.2 616.6
tp. rel. scale up 1 0.806 0.578 0.300 0.152
Figure 7: Scale up of Jool against the number of CPU cores
Both the maximum connection establishment rate and the throughput
scaled up poorly with the number of active CPU cores. The increase
of the performance was very low above 4 CPU cores.
3.3. Performance degradation caused by the number of sessions
To examine how the performance of Jool degrades with the number
connections, the number of connections was increased fourfold by
doubling the size of both the source port number range and the
destination port number range. We did not reach the limits of the
hardware regarding the number of connections, because unlike
iptables, Jool worked also with 1.6 billion connections.
The error of the binary search was chosen to be lower than 0.1% of
the expected results and the experiments were executed 10 times
(except for the very long lasting measurements with 800 million and
1.6 billion connections to save execution time).
The results are presented in Figure 8. The unit for the maximum
connection establishment rate is 1,000 connections per second. The
unit for throughput is 1,000 packets per second (measured with
bidirectional traffic, and the number of all packets per second is
displayed).
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num. conn. 1.56M 6.35M 25M 100M 400M 1600M
src ports 2,500 5,000 10,000 20,000 40,000 40,000
dst ports 625 1,250 2,500 5,000 10,000 40,000
num. exp. 10 10 10 10 5 5
error 100 100 100 100 1,000 1,000
cps median 480.2 394.8 328.6 273.0 243.0 232.0
cps min 468.6 392.7 324.9 269.4 243.0 230.5
cps max 484.9 397.4 331.3 280.6 244.5 233.6
throughput med. 511.5 423.9 350.0 286.5 257.8 198.4
throughput min 509.2 420.3 348.2 284.2 257.8 195.3
throughput max 513.1 428.3 352.5 290.8 260.9 201.6
Figure 8: Performance of Jool against the number of sessions
The performance of Jool shows degradation at the entire range of the
number of connections. We did not analyze the root cause of the
degradation yet. And we are not aware of the implementation of its
connection tracking table. We also plan to check the memory
consumption of Jool, what is definitely lower that that of iptables.
3.4. Connection tear down rate
Basically, the same measurement method was used as in Section 2.4,
however having no parameter of Jool to tune, only a single
measurement series was performed to determine the deletion time of
the empty connection tracking table. The median, minimum and maximum
values of the 10 measurements were 0.46s, 0.42s and 0.50s
respectively.
The same setup and parameters were used as in Section 2.3 and the
experiments were executed 10 times (except for the long lasting
measurements with 800,000,000 connections).
The results are presented in Figure 9. The unit for the connection
tear down rate is 1,000,000 connections per second.
Num. conn. 1.56M 6.35M 25M 100M 400M 1600M
src ports 2,500 5,000 10,000 20,000 40,000 40,000
dst ports 625 1,250 2,500 5,000 10,000 40,000
num. exp. 10 10 10 10 10 5
full contr. del med 0.87 2.05 7.84 36.38 126.09 474.68
full contr. del min 0.80 2.02 7.80 36.27 125.84 473.20
full contr. del max 0.91 2.09 7.94 36.80 127.54 481.38
empty contr. del med 0.46 0.46 0.46 0.46 0.46 0.46
conn. deletion time 0.41 1.59 7.38 35.92 125.63 474.22
conn. t. d. r. (M) 3.811 3.931 3.388 2.784 3.184 3.374
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Figure 9: Connetion tear down rate of Jool against the number of
connections
The connection tear down performance of Jool is excellent at any
number of connections. It is about and order of magnitude higher
that its connection establishment rate and than the connection tear
down rate of iptables. (A slight degradation can be observed at 100M
connections.)
4. Acknowledgements
The measurements were carried out by remotely using the resources of
NICT StarBED, 2-12 Asahidai, Nomi-City, Ishikawa 923-1211, Japan.
The author would like to thank Shuuhei Takimoto for the possibility
to use StarBED, as well as to Satoru Gonno and Makoto Yoshida for
their help and advice in StarBED usage related issues.
The author would like to thank Ole Troan for his comments on the
v6ops mailing list, while the scalalability measurements of iptables
were intended to be a part of [I-D.ietf-v6ops-transition-comparison].
5. IANA Considerations
This document does not make any request to IANA.
6. Security Considerations
TBD.
7. References
7.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC4814] Newman, D. and T. Player, "Hash and Stuffing: Overlooked
Factors in Network Device Benchmarking", RFC 4814,
DOI 10.17487/RFC4814, March 2007,
<https://www.rfc-editor.org/info/rfc4814>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
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Internet-Draft Scalability of IPv4aaS Technologies March 2022
[RFC8219] Georgescu, M., Pislaru, L., and G. Lencse, "Benchmarking
Methodology for IPv6 Transition Technologies", RFC 8219,
DOI 10.17487/RFC8219, August 2017,
<https://www.rfc-editor.org/info/rfc8219>.
7.2. Informative References
[I-D.ietf-v6ops-transition-comparison]
Lencse, G., Martinez, J. P., Howard, L., Patterson, R.,
and I. Farrer, "Pros and Cons of IPv6 Transition
Technologies for IPv4aaS", Work in Progress, Internet-
Draft, draft-ietf-v6ops-transition-comparison-02, 3 March
2022, <https://www.ietf.org/archive/id/draft-ietf-v6ops-
transition-comparison-02.txt>.
[I-D.lencse-bmwg-benchmarking-stateful]
Lencse, G. and K. Shima, "Benchmarking Methodology for
Stateful NATxy Gateways using RFC 4814 Pseudorandom Port
Numbers", Work in Progress, Internet-Draft, draft-lencse-
bmwg-benchmarking-stateful-03, 4 March 2022,
<https://www.ietf.org/archive/id/draft-lencse-bmwg-
benchmarking-stateful-03.txt>.
[LEN2019] Lencse, G. and Y. Kadobayashi, "Comprehensive Survey of
IPv6 Transition Technologies: A Subjective Classification
for Security Analysis", IEICE Transactions on
Communications, vol. E102-B, no.10, pp. 2021-2035., DOI:
10.1587/transcom.2018EBR0002, 1 October 2019,
<http://www.hit.bme.hu/~lencse/publications/
e102-b_10_2021.pdf>.
[LEN2020] Lencse, G., "Benchmarking Authoritative DNS
Servers", IEEE Access, vol. 8. pp. 130224-130238, DOI:
10.1109/ACCESS.2020.3009141, July 2020,
<https://ieeexplore.ieee.org/document/9139929>.
[LEN2021] Lencse, G., "Design and Implementation of a Software
Tester for Benchmarking Stateless NAT64 Gateways", IEICE
Transactions on Communications, DOI:
10.1587/transcom.2019EBN0010, 1 February 2021,
<http://www.hit.bme.hu/~lencse/publications/IEICE-2020-
siitperf-revised.pdf>.
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Appendix A. Change Log
A.1. 00
Initial version: scale up of iptables.
A.2. 01
Added the scale up of Jool.
Author's Address
Gabor Lencse
Szechenyi Istvan University
Gyor
Egyetem ter 1.
H-9026
Hungary
Email: lencse@sze.hu
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