Network Working Group G. Huston
Request for Comments: 4692 APNIC
Category: Informational October 2006
Network Working Group G. Huston
Request for Comments: 4692 APNIC
Category: Informational October 2006
Considerations on the IPv6 Host Density Metric
关于IPv6主机密度度量的思考
Status of This Memo
关于下段备忘
This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited.
本备忘录为互联网社区提供信息。它没有规定任何类型的互联网标准。本备忘录的分发不受限制。
Copyright Notice
版权公告
Copyright (C) The Internet Society (2006).
版权所有（C）互联网协会（2006年）。
Abstract
摘要
This memo provides an analysis of the Host Density metric as it is currently used to guide registry allocations of IPv6 unicast address blocks. This document contrasts the address efficiency as currently adopted in the allocation of IPv4 network addresses and that used by the IPv6 protocol. Note that for large allocations there are very significant variations in the target efficiency metric between the two approaches.
此备忘录提供了主机密度度量的分析，因为它当前用于指导IPv6单播地址块的注册表分配。本文档对比了IPv4网络地址分配中当前采用的地址效率和IPv6协议使用的地址效率。请注意，对于大型分配，两种方法之间的目标效率指标存在非常显著的差异。
Table of Contents
目录
1. Introduction ....................................................2
2. IPv6 Address Structure ..........................................2
3. The Host Density Ratio ..........................................3
4. The Role of an Address Efficiency Metric ........................4
5. Network Structure and Address Efficiency Metric .................6
6. Varying the HD-Ratio ............................................7
6.1. Simulation Results .........................................8
7. Considerations .................................................10
8. Security Considerations ........................................11
9. Acknowledgements ...............................................11
10. References ....................................................12
10.1. Normative References .....................................12
10.2. Informative References ...................................12
Appendix A. Comparison Tables ....................................13
1. Introduction ....................................................2
2. IPv6 Address Structure ..........................................2
3. The Host Density Ratio ..........................................3
4. The Role of an Address Efficiency Metric ........................4
5. Network Structure and Address Efficiency Metric .................6
6. Varying the HD-Ratio ............................................7
6.1. Simulation Results .........................................8
7. Considerations .................................................10
8. Security Considerations ........................................11
9. Acknowledgements ...............................................11
10. References ....................................................12
10.1. Normative References .....................................12
10.2. Informative References ...................................12
Appendix A. Comparison Tables ....................................13
Metrics of address assignment efficiency are used in the context of the Regional Internet Registries' (RIRs') address allocation function. Through the use of a common address assignment efficiency metric, individual networks can be compared to a threshold value in an objective fashion. The common use of this metric is to form part of the supporting material for an address allocation request, demonstrating that the network has met or exceeded the threshold address efficiency value, and it forms part of the supportive material relating to the justification of the allocation of a further address block.
地址分配效率指标用于区域互联网注册中心（RIR）的地址分配功能。通过使用通用地址分配效率指标，可以客观地将单个网络与阈值进行比较。该指标的常见用途是构成地址分配请求支持材料的一部分，证明网络已达到或超过阈值地址效率值，并构成与进一步地址块分配合理性相关的支持材料的一部分。
Public and private IP networks have significant differences in purpose, structure, size, and technology. Attempting to impose a single efficiency metric across this very diverse environment is a challenging task. Any address assignment efficiency threshold value has to represent a balance between stating an achievable outcome for any competently designed and operated service platform while without setting a level of consumption of address resources that imperils the protocol's longer term viability through consequent address scarcity. There are a number of views relating to address assignment efficiency, both in terms of theoretic analyses of assignment efficiency and in terms of practical targets that are part of current address assignment practices in today's Internet.
公共和私有IP网络在用途、结构、规模和技术上存在显著差异。试图在这个非常多样化的环境中实施单一的效率指标是一项具有挑战性的任务。任何地址分配效率阈值都必须在说明任何设计和运行良好的服务平台的可实现结果，同时不设置地址资源消耗水平之间取得平衡，而地址资源消耗水平会因地址稀缺而危及协议的长期生存能力。关于地址分配效率，无论是从分配效率的理论分析方面，还是从作为当今互联网地址分配实践一部分的实际目标方面，都有许多观点。
This document contrasts the address efficiency metric and threshold value as currently adopted in the allocation of IPv4 network addresses and the framework used by the address allocation process for the IPv6 protocol.
本文档对比了IPv4网络地址分配中当前采用的地址效率度量和阈值，以及IPv6协议地址分配过程中使用的框架。
Before looking at address allocation efficiency metrics, it is appropriate to summarize the address structure for IPv6 global unicast addresses.
在查看地址分配效率指标之前，最好先总结一下IPv6全局单播地址的地址结构。
The general format for IPv6 global unicast addresses is defined in [RFC4291] as follows (Figure 1).
IPv6全局单播地址的通用格式在[RFC4291]中定义如下（图1）。
| 64 - m bits | m bits | 64 bits |
+------------------------+-----------+----------------------------+
| global routing prefix | subnet ID | interface ID |
+------------------------+-----------+----------------------------+
| 64 - m bits | m bits | 64 bits |
+------------------------+-----------+----------------------------+
| global routing prefix | subnet ID | interface ID |
+------------------------+-----------+----------------------------+
IPv6 Address Structure
IPv6地址结构
Figure 1
图1
Within the current policy framework for allocation of IPv6 addresses in the context of the public Internet, the value for 'm' in the figure above, referring to the subnet ID, is commonly a 16-bit field. Therefore, the end-site global routing prefix is 48 bits in length, the per-customer subnet ID is 16 bits in length, and the interface ID is 64 bits in length [RFC3177].
在公共互联网上下文中分配IPv6地址的当前策略框架内，上图中的“m”值（指子网ID）通常为16位字段。因此，终端站点全局路由前缀长度为48位，每个客户子网ID长度为16位，接口ID长度为64位[RFC3177]。
In relating this address structure to the address allocation function, the efficiency metric is not intended to refer to the use of individual 128-bit IPv6 addresses nor that of the use of the 64- bit subnet prefix. Instead, it is limited to a measure of efficiency of use of the end-site global routing prefix. This allocation model assumes that each customer is allocated a minimum of a single /48 address block. Given that this block allows 2^16 possible subnets, it is also assumed that a /48 allocation will be used in the overall majority of cases of end-customer address assignment.
在将此地址结构与地址分配功能相关联时，效率指标并不旨在指单个128位IPv6地址的使用，也不指64位子网前缀的使用。相反，它仅限于测量终端站点全局路由前缀的使用效率。此分配模型假设每个客户至少分配一个/48地址块。考虑到此块允许2^16个可能的子网，还假设在终端客户地址分配的大多数情况下都将使用a/48分配。
The following discussion makes the assumption that the address allocation unit in IPv6 is an address prefix of 48 bits in length, and that the address assignment efficiency in this context is the efficiency of assignment of /48 address allocation units. However, the analysis presented here refers more generally to end-site address allocation practices rather than /48 address prefixes in particular, and is applicable in the context of any size of end-site global routing prefix.
以下讨论假设IPv6中的地址分配单元是长度为48位的地址前缀，并且在此上下文中的地址分配效率是/48地址分配单元的分配效率。然而，这里的分析更一般地指的是终端站点地址分配实践，而不是特别指/48地址前缀，并且适用于任何大小的终端站点全局路由前缀。
The "Host Density Ratio" was first described in [RFC1715] and subsequently updated in [RFC3194].
“宿主密度比”首先在[RFC1715]中描述，随后在[RFC3194]中更新。
The "H Ratio", as defined in RFC 1715, is:
RFC 1715中定义的“H比率”为：
log (number of objects)
H = -----------------------
available bits
log (number of objects)
H = -----------------------
available bits
Figure 2
图2
The argument presented in [RFC1715] draws on a number of examples to support the assertion that this metric reflects a useful generic measure of address assignment efficiency in a range of end-site addressed networks, and furthermore that the optimal point for such a utilization efficiency metric lies in an H Ratio value between 0.14 and 0.26. Lower H Ratio values represent inefficient address use, and higher H Ratio values tend to be associated with various forms of additional network overhead related to forced re-addressing operations.
[RFC1715]中提出的论点利用了大量示例来支持以下主张：该指标反映了一系列终端地址寻址网络中地址分配效率的有用通用度量，此外，该利用率指标的最佳点在于0.14和0.26之间的H比值。较低的H比率值表示地址使用效率低下，较高的H比率值往往与各种形式的与强制重新寻址操作相关的额外网络开销相关联。
This particular metric has a maximal value of log base 10 of 2, or 0.30103.
该特定指标的最大值为2的对数基数10，或0.30103。
The metric was 'normalized' in RFC 3194, and a new metric, the "HD-Ratio" was introduced, with the following definition:
该指标在RFC 3194中“标准化”，并引入了一个新指标“HD比率”，其定义如下：
log(number of allocated objects)
HD = ------------------------------------------
log(maximum number of allocatable objects)
log(number of allocated objects)
HD = ------------------------------------------
log(maximum number of allocatable objects)
Figure 3
图3
HD-Ratio values are proportional to the H ratio, and the values of the HD-Ratio range from 0 to 1. The analysis described in [RFC3194] applied this HD-Ratio metric to the examples given in [RFC1715] and, on the basis of these examples, postulated that HD-Ratio values of 0.85 or higher force the network into some form of renumbering. HD-Ratio values of 0.80 or lower were considered an acceptable network efficiency metric.
HD比率值与H比率成比例，HD比率的值范围为0到1。[RFC3194]中描述的分析将该HD比率度量应用于[RFC1715]中给出的示例，并基于这些示例，假设0.85或更高的HD比率值迫使网络进行某种形式的重新编号。HD比率值为0.80或更低被视为可接受的网络效率指标。
The HD-Ratio is referenced within the IPv6 address allocation policies used by the Regional Internet Registries, and their IPv6 address allocation policy documents specify that an HD-Ratio metric of 0.8 is an acceptable objective in terms of address assignment efficiency for an IPv6 network.
HD比率在区域Internet注册中心使用的IPv6地址分配策略中引用，其IPv6地址分配策略文件规定，就IPv6网络的地址分配效率而言，HD比率度量为0.8是可接受的目标。
By contrast, the generally used address efficiency metric for IPv4 is the simple ratio of the number of allocated (or addressed) objects to the maximum number of allocatable objects. For IPv4, the commonly applied value for this ratio is 0.8 (or 80%).
相比之下，IPv4通常使用的地址效率指标是分配（或寻址）对象数量与最大可分配对象数量的简单比率。对于IPv4，此比率的常用值为0.8（或80%）。
A comparison of these two metrics is given in Table 1 of Attachment A.
附件A表1中给出了这两个指标的比较。
The role of the address efficiency metric is to provide objective metrics relating to a network's use of address space that can be used by both the allocation entity and the applicant to determine whether an address allocation is warranted, and provide some indication of the size of the address allocation that should be undertaken. The metric provides a target address utilization level that indicates at what point a network's address resource may be considered "fully utilized".
地址效率度量的作用是提供与网络地址空间使用相关的客观度量，分配实体和申请人都可以使用这些客观度量来确定地址分配是否合理，并提供应进行的地址分配大小的一些指示。该指标提供了一个目标地址利用率级别，该级别指示在什么情况下网络的地址资源可以被视为“充分利用”。
The objective here is to allow the network service provider to deploy addresses across both network infrastructure and the network's customers in a manner that does not entail periodic renumbering, and
此处的目标是允许网络服务提供商以不需要定期重新编号的方式跨网络基础设施和网络客户部署地址，以及
in a manner that allows both the internal routing system and inter-domain routing system to operate without excessive fragmentation of the address space and consequent expansion of the number of route objects carried within the routing systems. This entails use of an addressing plan where at each level of structure within the network there is a pool of address blocks that allows expansion of the network at that structure level without requiring renumbering of the remainder of the network.
以允许内部路由系统和域间路由系统在地址空间不过度碎片化和路由系统内承载的路由对象数量不随之扩展的情况下运行的方式。这需要使用寻址计划，其中在网络内的每一层结构上都有一个地址块池，允许在该结构层上扩展网络，而无需对网络的其余部分重新编号。
It is recognized that an address utilization efficiency metric of 100% is unrealistic in any scenario. Within a typical network address plan, the network's address space is exhausted not when all address resources have been used, but at the point when one element within the structure has exhausted its pool, and when augmentation of this pool by drawing from the pools of other elements would entail extensive renumbering. While it is not possible to provide a definitive threshold of what overall efficiency level is obtainable in all IP networks, experience with IPv4 network deployments suggests that it is reasonable to observe that at any particular level within a hierarchically structured address deployment plan an efficiency level of between 60% to 80% is an achievable metric in the general case.
众所周知，100%的地址利用率指标在任何情况下都是不现实的。在典型的网络地址计划中，网络的地址空间不是在所有地址资源都已使用时耗尽，而是在结构中的一个元素耗尽其池时耗尽，并且当通过从其他元素池中提取来扩充此池将需要大量重新编号时耗尽。虽然无法提供在所有IP网络中可获得的总体效率水平的确定阈值，IPv4网络部署的经验表明，在分层结构的地址部署计划中的任何特定级别上，在一般情况下，60%到80%之间的效率级别都是可以实现的指标。
This IPv4 efficiency threshold is significantly greater than that observed in the examples provided in conjunction with the HD-Ratio description in [RFC1715]. Note that the examples used in the HD-Ratio are drawn from, among other sources, the Public Switched Telephone Network (PSTN). This comparison with the PSTN warrants some additional examination. There are a number of differences between public IP network deployments and PSTN deployments that may account for this difference. IP addresses are deployed on a per-provider basis with an alignment to network topology. PSTN addresses are, on the whole, deployed using a geographical distribution system of "call areas" that share a common number prefix. Within each call area, a sufficient number blocks from the number prefix must be available to allow each operator to draw their own number block from the area pool. Within the IP environment, service providers do not draw address blocks from a common geographic number pool but receive address blocks from the Regional Internet Registry on a 'whole of network' basis. This difference in the address structure allows an IP environment to achieve an overall higher level of address utilization efficiency.
该IPv4效率阈值明显大于[RFC1715]中结合HD比率描述提供的示例中观察到的阈值。注意，HD比率中使用的示例来自公共交换电话网（PSTN）等来源。这种与PSTN的比较需要进行一些额外的检查。公共IP网络部署和PSTN部署之间存在许多差异，这可能是造成这种差异的原因。IP地址根据每个提供商进行部署，并与网络拓扑保持一致。总的来说，PSTN地址使用共享一个通用号码前缀的“呼叫区”地理分布系统进行部署。在每个呼叫区内，号码前缀中必须有足够的号码块，以允许每个操作员从区域池中提取自己的号码块。在IP环境中，服务提供商不会从公共地理号码池中提取地址块，而是在“整个网络”的基础上从区域互联网注册中心接收地址块。地址结构中的这种差异允许IP环境实现更高级别的地址利用效率。
In terms of considering the number of levels of internal hierarchy in IP networks, the interior routing protocol, if uniformly deployed, admits a hierarchical network structure that is only two levels deep, with a fully connected backbone "core" and a number of satellite areas that are directly attached to this "core". Additional levels
考虑到IP网络内部层次结构的数量，如果统一部署，内部路由协议允许层次结构只有两层深，具有完全连接的主干“核心”和直接连接到该“核心”的多个卫星区域。附加级别
of routing hierarchy may be obtained using various forms of routing confederations, but this is not an extremely common deployment technique. The most common form of network structure used in large IP networks is a three-level structure using regions, individual Points of Presence (POPs), and end-customers.
可以使用各种形式的路由联盟来获得路由层次结构，但这不是一种非常常见的部署技术。大型IP网络中使用的最常见的网络结构形式是使用区域、单个存在点（POP）和最终客户的三级结构。
Also, note that large-scale IP deployments typically use a relatively flat routing structure, as compared to a deeply hierarchical structure. In order to improve the dynamic performance of the interior routing protocol the number of routes carried in the interior routing protocol, is commonly restricted to the routes corresponding to next-hop destinations for iBGP routes, and customer routes are carried in the iBGP domain and aggregated at the point where the routes are announced in eBGP sessions. This implies that per-POP or per-region address aggregations according to some fixed address hierarchy is not a necessary feature of large IP networks, so strict hierarchical address structure within all parts of the network is not a necessity in such routing environments.
另外，请注意，与深层层次结构相比，大规模IP部署通常使用相对平坦的路由结构。为了提高内部路由协议的动态性能，内部路由协议中承载的路由数量通常限制为iBGP路由的下一跳目的地对应的路由，客户路由在iBGP域中进行，并在eBGP会话中宣布路由的位置进行聚合。这意味着，根据某些固定地址层次结构的每POP或每区域地址聚合不是大型IP网络的必要特征，因此在此类路由环境中，网络所有部分内的严格层次地址结构不是必要的。
An address efficiency metric can be expressed using the number of levels of structure (n) and the efficiency achieved at each level (e). If the same efficiency threshold is applied at each level of structure, the resultant efficiency threshold is e^n. This then allows us to make some additional observations about the HD-Ratio values. Table 2 of Appendix A (Figure 8) indicates the number of levels of structure that are implied by a given HD-Ratio value of 0.8 for each address allocation block size, assuming a fixed efficiency level at all levels of the structure. The implication is that for large address blocks, the HD-Ratio assumes a large number of elements in the hierarchical structure, or a very low level of address efficiency at the lower levels. In the case of IP network deployments, this latter situation is not commonly the case.
地址效率度量可以使用结构的级别数（n）和在每个级别上实现的效率（e）来表示。如果在结构的每个级别应用相同的效率阈值，则生成的效率阈值为e^n。这样我们就可以对HD比率值进行一些额外的观察。附录A的表2（图8）显示了给定的HD比率值0.8为每个地址分配块大小所隐含的结构级别数，假设结构的所有级别都有固定的效率级别。这意味着，对于大型地址块，HD比率假设层次结构中有大量元素，或者在较低级别上的地址效率非常低。在IP网络部署的情况下，后一种情况并不常见。
The most common form of interior routing structure used in IP networks is a two-level routing structure. It is consistent with this constrained routing architecture that network address plans appear to be commonly devised using up to a three-level hierarchical structure, while for larger networks a four-level structure may generally be used.
IP网络中最常见的内部路由结构形式是两级路由结构。与这种受约束的路由体系结构一致的是，网络地址计划似乎通常使用三级层次结构来设计，而对于较大的网络，通常可以使用四级结构。
Table 3 of Attachment A (Figure 9) shows an example of address efficiency outcomes using a per-level efficiency metric of 0.75 (75%) and a progressively deeper network structure as the address block expands. This model (termed here "limited levels") limits the maximal number of levels of internal hierarchy to 6 and uses a model where the number of levels of network hierarchy increases by 1 when the network increases in size by a factor of a little over one order of magnitude.
附件A的表3（图9）显示了使用0.75（75%）的每级效率指标和随着地址块扩展而逐渐加深的网络结构的地址效率结果示例。该模型（此处称为“有限级别”）将内部层次结构的最大级别数限制为6，并使用一个模型，其中当网络规模增加一个数量级多一点的因子时，网络层次结构的级别数增加1。
It is illustrative to compare these metrics for a larger network deployment. If, for example, the network is designed to encompass 8 million end customers, each of which is assigned a 16-bit subnet ID for their end site, then the following table Figure 4 indicates the associated allocation size as determined by the address efficiency metric.
对于更大的网络部署，比较这些指标是很有说明性的。例如，如果网络设计为包含800万终端客户，每个终端客户都为其终端站点分配了一个16位子网ID，那么下表图4显示了由地址效率度量确定的相关分配大小。
Allocation: 8M Customers
分配：800万客户
Allocation Relative Ratio
分配相对比率
100% Allocation Efficiency /25 1 80% Efficiency (IPv4) /24 2 0.8 HD-Ratio /19 64 75% with Limited Level /23 4 0.94 HD-Ratio /23 4
100%分配效率/25 1 80%效率（IPv4）/24 2 0.8高清比率/19 64 75%有限级别/23 4 0.94高清比率/23 4
Figure 4
图4
Note that the 0.8 HD-Ratio produces a significantly lower efficiency level than the other metrics. The limited-level model appears to point to a more realistic value for an efficiency value for networks of this scale (corresponding to a network with 4 levels of internal hierarchy, each with a target utilization efficiency of 75%). This limited-level model corresponds to an HD-Ratio with a threshold value of 0.945.
请注意，与其他指标相比，0.8高清比率产生的效率水平要低得多。有限级别模型似乎为这种规模的网络的效率值指出了更现实的值（对应于具有4个内部层次结构级别的网络，每个级别的目标利用率为75%）。此有限级别模型对应于阈值为0.945的HD比率。
One way to model the range of outcomes of taking a more limited approach to the number of levels of aggregateable hierarchy is to look at a comparison of various values for the HD-Ratio with the model of a fixed efficiency and the "Limited Levels" model. This is indicated in Figure 5.
对可聚合层次结构的级别数量采取更有限的方法的结果范围进行建模的一种方法是将HD比率的各种值与固定效率模型和“有限级别”模型进行比较。如图5所示。
Prefix Length (bits)
|
|
| Limited HD-Ratio
| Levels 0.98 0.94 0.90 0.86 0.82 0.80
| | | | | | | |
1 0.750 0.986 0.959 0.933 0.908 0.883 0.871
4 0.750 0.946 0.847 0.758 0.678 0.607 0.574
8 0.750 0.895 0.717 0.574 0.460 0.369 0.330
12 0.563 0.847 0.607 0.435 0.312 0.224 0.189
16 0.563 0.801 0.514 0.330 0.212 0.136 0.109
20 0.422 0.758 0.435 0.250 0.144 0.082 0.062
24 0.422 0.717 0.369 0.189 0.097 0.050 0.036
28 0.316 0.678 0.312 0.144 0.066 0.030 0.021
32 0.316 0.642 0.264 0.109 0.045 0.018 0.012
36 0.237 0.607 0.224 0.082 0.030 0.011 0.007
40 0.237 0.574 0.189 0.062 0.021 0.007 0.004
44 0.178 0.543 0.160 0.047 0.014 0.004 0.002
48 0.178 0.514 0.136 0.036 0.009 0.003 0.001
Prefix Length (bits)
|
|
| Limited HD-Ratio
| Levels 0.98 0.94 0.90 0.86 0.82 0.80
| | | | | | | |
1 0.750 0.986 0.959 0.933 0.908 0.883 0.871
4 0.750 0.946 0.847 0.758 0.678 0.607 0.574
8 0.750 0.895 0.717 0.574 0.460 0.369 0.330
12 0.563 0.847 0.607 0.435 0.312 0.224 0.189
16 0.563 0.801 0.514 0.330 0.212 0.136 0.109
20 0.422 0.758 0.435 0.250 0.144 0.082 0.062
24 0.422 0.717 0.369 0.189 0.097 0.050 0.036
28 0.316 0.678 0.312 0.144 0.066 0.030 0.021
32 0.316 0.642 0.264 0.109 0.045 0.018 0.012
36 0.237 0.607 0.224 0.082 0.030 0.011 0.007
40 0.237 0.574 0.189 0.062 0.021 0.007 0.004
44 0.178 0.543 0.160 0.047 0.014 0.004 0.002
48 0.178 0.514 0.136 0.036 0.009 0.003 0.001
Figure 5
图5
As shown in this figure, it is possible to select an HD-Ratio value that models IP level structures in a fashion that behaves more consistently for very large deployments. In this case, the choice of an HD-Ratio of 0.94 is consistent with a limited-level model of up to 6 levels of hierarchy with a metric of 75% density at each level. This correlation is indicated in Table 3 of Attachment A.
如图所示，可以选择一个HD比率值，该值以一种更一致的方式对IP级结构进行建模，以用于非常大的部署。在这种情况下，选择0.94的HD比率与多达6个层次的有限层次模型一致，每个层次的密度为75%。该相关性如附件A表3所示。
In attempting to assess the impact of potentially changing the HD-Ratio to a lower value, it is useful to assess this using actual address consumption data. The results described here use the IPv4 allocation data as published by the Regional Internet Registries [RIR-Data]. The simulation work assumes that the IPv4 delegation data uses an IPv4 /32 for each end customer, and that assignments have been made based on an 80% density metric in terms of assumed customer count. The customer count is then used as the basis of an IPv6 address allocation, using the HD-Ratio to map from a customer count to the size of an address allocation.
在试图评估可能将HD比率更改为较低值的影响时，使用实际地址消耗数据进行评估是有用的。这里描述的结果使用由区域互联网注册中心发布的IPv4分配数据[RIR数据]。模拟工作假设IPv4委派数据对每个最终客户使用IPv4/32，并且根据假定的客户计数，根据80%的密度度量进行分配。然后，客户计数用作IPv6地址分配的基础，使用HD比率将客户计数映射到地址分配的大小。
The result presented here is that of a simulation of an IPv6 address allocation registry, using IPv4 allocation data as published by the RIRs spanning the period from January 1, 1999 until August 31, 2004. The aim is to identify the relative level of IPv6 address consumption using a IPv6 request size profile based on the application of various HD-Ratio values to the derived customer numbers.
这里给出的结果是对IPv6地址分配注册表的模拟，使用RIRs发布的从1999年1月1日到2004年8月31日期间的IPv4分配数据。其目的是使用IPv6请求大小配置文件来确定IPv6地址消耗的相对水平，该配置文件基于对派生客户号应用各种HD比率值。
The profile of total address consumption for selected HD-Ratio values is indicated in Figure 6. The simulation results indicate that the choice of an HD-Ratio of 0.8 consumes a total of 7 times the address space of that consumed when using an HD-Ratio of 0.94.
所选HD比率值的总地址消耗情况如图6所示。仿真结果表明，选择0.8的HD比率所消耗的地址空间是使用0.94的HD比率所消耗的地址空间的7倍。
HD-Ratio Total Address Consumption | Prefix Length Count of | Notation /32 prefixes 0.80 /14.45 191,901 0.81 /14.71 160,254 0.82 /15.04 127,488 0.83 /15.27 108,701 0.84 /15.46 95,288 0.85 /15.73 79,024 0.86 /15.88 71,220 0.87 /16.10 61,447 0.88 /16.29 53,602 0.89 /16.52 45,703 0.90 /16.70 40,302 0.91 /16.77 38,431 0.92 /16.81 37,381 0.93 /16.96 33,689 0.94 /17.26 27,364 0.95 /17.32 26,249 0.96 /17.33 26,068 0.97 /17.33 26,068 0.98 /17.40 24,834 0.99 /17.67 20,595
高清比率总地址消耗|符号前缀长度计数/32前缀0.80/14.45 191901 0.81/14.71 160254 0.82/15.04 127488 0.83/15.27 108701 0.84/15.46 95288 0.85/15.73 79024 0.86/15.88 71220 0.87/16.10 61447 0.88/16.29 53602 0.89/16.52 45703 0.90/16.70 40302 0.91/16.77 381 0.92/16.371 0.9633,689 0.94 /17.26 27,364 0.95 /17.32 26,249 0.96 /17.33 26,068 0.97 /17.33 26,068 0.98 /17.40 24,834 0.99 /17.67 20,595
Figure 6
图6
The implication of these results imply that an IPv6 address registry will probably see sufficient distribution of allocation request sizes such that the choice of a threshold HD-Ratio will impact the total address consumption rates, and the variance between an HD-Ratio of 0.8 and an HD-Ratio of 0.99 is a factor of one order of magnitude in relative address consumption over an extended period of time. The simulation also indicates that the overall majority of allocations fall within a /32 minimum allocation size (between 74% to 95% of all address allocations), and that the selection of a particular HD-Ratio value has a significant impact in terms of allocation sizes for a
这些结果意味着IPv6地址注册表可能会看到分配请求大小的充分分布，因此阈值HD比率的选择将影响总地址消耗率，HD比率为0.8和HD比率为0.99之间的差异是相对地址消耗在较长时间内的一个数量级因素。模拟还表明，总体上大多数分配都在a/32最小分配大小范围内（在所有地址分配的74%到95%之间），并且特定HD比率值的选择对特定地址的分配大小有重大影响
small proportion of allocation transactions (the remainder of allocations range between a /19 to a /31 for an HD-Ratio of 0.8 and between a /26 and a /31 for an HD-Ratio of 0.99).
分配交易的小部分（剩余分配范围在a/19至a/31之间，HD比率为0.8，分配范围在a/26至a/31之间，HD比率为0.99）。
The conclusion here is that the choice of the HD-Ratio will have some impact on one quarter of all allocations, while the remainder are serviced using the minimum allocation unit of a /32 address prefix. Of these 'impacted' allocations that are larger than the minimum allocation, approximately one tenth of these allocations are 'large' allocations. These large allocations have a significant impact on total address consumption, and varying the HD-Ratio for these allocations between 0.8 to 0.99 results in a net difference in total address consumption of approximately one order of magnitude. This is a heavy-tail distribution, where a small proportion of large address allocations significantly impact the total address consumption rate. Altering the HD-Ratio will have little impact on more than 95% of the IPv6 allocations but will generate significant variance within the largest 2% of these allocations, which, in turn, will have a significant impact on total address consumption rates.
这里的结论是，HD比率的选择将对所有分配中的四分之一产生一定影响，而其余分配使用a/32地址前缀的最小分配单元进行服务。在这些大于最低分配的“受影响”分配中，大约十分之一的分配是“大型”分配。这些较大的分配对总地址消耗有重大影响，将这些分配的HD比率在0.8到0.99之间变化会导致总地址消耗的净差异约为一个数量级。这是一个重尾分布，其中一小部分大地址分配会显著影响总地址消耗率。改变HD比率对超过95%的IPv6分配几乎没有影响，但会在这些分配的最大2%内产生显著差异，这反过来会对总地址消耗率产生显著影响。
The HD-Ratio with a value of 0.8 as a model of network address utilization efficiency produces extremely low efficiency outcomes for networks spanning of the order of 10**6 end customers and larger.
作为网络地址利用效率的模型，HD比率的值为0.8，对于跨越10**6个终端客户或更大的网络，产生极低的效率结果。
The HD-Ratio with a 0.8 value makes the assumption that as the address allocation block increases in size, the network within which the addresses will be deployed adds additional levels of hierarchical structure. This increasing depth of hierarchical structure to arbitrarily deep hierarchies is not a commonly observed feature of public IP network deployments.
值为0.8的HD比率假设随着地址分配块大小的增加，将在其中部署地址的网络会增加额外的层次结构。这种从层次结构向任意深度层次结构的不断加深并不是公共IP网络部署的常见特征。
The fixed efficiency model, as used in the IPv4 address allocation policy, uses the assumption that as the allocation block becomes larger, the network structure remains at a fixed level of levels; if the number of levels is increased, then efficiency achieved at each level increases significantly. There is little evidence to suggest that increasing a number of levels in a network hierarchy increases the efficiency at each level.
IPv4地址分配策略中使用的固定效率模型假设，随着分配块变大，网络结构保持在固定的级别上；如果级别数量增加，则每个级别的效率都会显著提高。几乎没有证据表明，增加网络层次结构中的多个级别可以提高每个级别的效率。
It is evident that neither of these models accurately encompass IP network infrastructure models and the associated requirements of address deployment. The fixed efficiency model places an excessive burden on the network operator to achieve very high levels of utilization at each level in the network hierarchy, leading to either customer renumbering or deployment of technologies such as Network Address Translation (NAT) to meet the target efficiency value in a
显然，这两种模型都没有准确地涵盖IP网络基础设施模型和地址部署的相关需求。固定效率模型给网络运营商带来了过重的负担，使其无法在网络层次结构的每一层实现非常高的利用率，从而导致客户重新编号或部署网络地址转换（NAT）等技术，以满足网络中的目标效率值
hierarchically structured network. The HD-Ratio model using a value of 0.8 specifies an extremely low address efficiency target for larger networks, and while this places no particular stress on network architects in terms of forced renumbering, there is the concern that this represents an extremely inefficient use of address resources. If the objective of IPv6 is to encompass a number of decades of deployment, and to span a public network that ultimately encompasses many billions of end customers and a very high range and number of end use devices and components, then there is legitimate cause for concern that the HD-Ratio value of 0.8 may be setting too conservative a target for address efficiency, in that the total address consumption targets may be achieved too early.
层次结构网络。使用值为0.8的HD比率模型为更大的网络指定了极低的地址效率目标，虽然这在强制重新编号方面对网络架构师没有特别的压力，但有人担心这表示地址资源的使用极为低效。如果IPv6的目标是包含数十年的部署，并跨越最终包含数十亿最终客户和大量终端设备和组件的公共网络，然后，有合理的理由担心HD Ratio值0.8可能为地址效率设置了过于保守的目标，因为总地址消耗目标可能过早实现。
This study concludes that consideration should be given to the viability of specifying a higher HD-Ratio value as representing a more relevant model of internal network structure, internal routing, and internal address aggregation structures in the context of IPv6 network deployment.
本研究得出结论，应考虑在IPv6网络部署环境下，指定更高的HD比率值作为内部网络结构、内部路由和内部地址聚合结构的更相关模型的可行性。
Considerations of various forms of host density metrics create no new threats to the security of the Internet.
考虑到各种形式的主机密度指标不会对互联网的安全造成新的威胁。
The document was reviewed by Kurt Lindqvist, Thomas Narten, Paul Wilson, David Kessens, Bob Hinden, Brian Haberman, and Marcelo Bagnulo.
该文件由Kurt Lindqvist、Thomas Narten、Paul Wilson、David Kessens、Bob Hinden、Brian Haberman和Marcelo Bagnulo审查。
[RFC1715] Huitema, C., "The H Ratio for Address Assignment Efficiency", RFC 1715, November 1994.
[RFC1715]Huitema，C.，“地址分配效率的H比率”，RFC17151994年11月。
[RFC3177] IAB and IESG, "IAB/IESG Recommendations on IPv6 Address Allocations to Sites", RFC 3177, September 2001.
[RFC3177]IAB和IESG，“IAB/IESG对站点IPv6地址分配的建议”，RFC3177，2001年9月。
[RFC3194] Durand, A. and C. Huitema, "The H-Density Ratio for Address Assignment Efficiency An Update on the H ratio", RFC 3194, November 2001.
[RFC3194]Durand，A.和C.Huitema，“地址分配效率的H密度比——H比率的更新”，RFC 31942001年11月。
[RFC4291] Hinden, R. and S. Deering, "IP Version 6 Addressing Architecture", RFC 4291, February 2006.
[RFC4291]Hinden，R.和S.Deering，“IP版本6寻址体系结构”，RFC 42912006年2月。
[RIR-Data] RIRs, "RIR Delegation Records", February 2005, <ftp://ftp.apnic.net/pub/stats/>.
[RIR数据]RIRs，“RIR代表团记录”，2005年2月<ftp://ftp.apnic.net/pub/stats/>.
The first table compares the threshold number of /48 end user allocations that would be performed for a given assigned address block in order to consider that the utilization has achieved its threshold utilization level.
第一表比较将为给定的分配地址块执行的阈值数/ 48个终端用户分配，以便考虑利用率已经达到其阈值利用水平。
Fixed Efficiency Value 0.8 HD-Ratio Value 0.8
固定效率值0.8 HD比率值0.8
Number of /48 allocations to fill the address block to the threshold level
将地址块填充到阈值级别的/48分配数
Prefix Size Fixed Efficiency HD-Ratio 0.8 0.8
前缀大小固定效率HD比率0.8 0.8
/48 1 1 100% 1 100%
/47 2 2 100% 2 87%
/46 4 4 100% 3 76%
/45 8 7 88% 5 66%
/44 16 13 81% 9 57%
/43 32 26 81% 16 50%
/42 64 52 81% 28 44%
/41 128 103 80% 49 38%
/40 256 205 80% 84 33%
/39 512 410 80% 147 29%
/38 1,024 820 80% 256 25%
/37 2,048 1,639 80% 446 22%
/36 4,096 3,277 80% 776 19%
/35 8,192 6,554 80% 1,351 16%
/34 16,384 13,108 80% 2,353 14%
/33 32,768 26,215 80% 4,096 13%
/32 65,536 52,429 80% 7,132 11%
/31 131,072 104,858 80% 12,417 9%
/30 262,144 209,716 80% 21,619 8%
/29 524,288 419,431 80% 37,641 7%
/28 1,048,576 838,861 80% 65,536 6%
/27 2,097,152 1,677,722 80% 114,105 5%
/26 4,194,304 3,355,444 80% 198,668 5%
/25 8,388,608 6,710,887 80% 345,901 4%
/24 16,777,216 13,421,773 80% 602,249 4%
/23 33,554,432 26,843,546 80% 1,048,576 3%
/22 67,108,864 53,687,092 80% 1,825,677 3%
/21 134,217,728 107,374,180 80% 3,178,688 2%
/20 268,435,456 214,748,365 80% 5,534,417 2%
/19 536,870,912 429,496,730 80% 9,635,980 2%
/18 1,073,741,824 858,993,460 80% 16,777,216 2%
/17 2,147,483,648 1,717,986,919 80% 29,210,830 1%
/48 1 1 100% 1 100%
/47 2 2 100% 2 87%
/46 4 4 100% 3 76%
/45 8 7 88% 5 66%
/44 16 13 81% 9 57%
/43 32 26 81% 16 50%
/42 64 52 81% 28 44%
/41 128 103 80% 49 38%
/40 256 205 80% 84 33%
/39 512 410 80% 147 29%
/38 1,024 820 80% 256 25%
/37 2,048 1,639 80% 446 22%
/36 4,096 3,277 80% 776 19%
/35 8,192 6,554 80% 1,351 16%
/34 16,384 13,108 80% 2,353 14%
/33 32,768 26,215 80% 4,096 13%
/32 65,536 52,429 80% 7,132 11%
/31 131,072 104,858 80% 12,417 9%
/30 262,144 209,716 80% 21,619 8%
/29 524,288 419,431 80% 37,641 7%
/28 1,048,576 838,861 80% 65,536 6%
/27 2,097,152 1,677,722 80% 114,105 5%
/26 4,194,304 3,355,444 80% 198,668 5%
/25 8,388,608 6,710,887 80% 345,901 4%
/24 16,777,216 13,421,773 80% 602,249 4%
/23 33,554,432 26,843,546 80% 1,048,576 3%
/22 67,108,864 53,687,092 80% 1,825,677 3%
/21 134,217,728 107,374,180 80% 3,178,688 2%
/20 268,435,456 214,748,365 80% 5,534,417 2%
/19 536,870,912 429,496,730 80% 9,635,980 2%
/18 1,073,741,824 858,993,460 80% 16,777,216 2%
/17 2,147,483,648 1,717,986,919 80% 29,210,830 1%
/16 4,294,967,296 3,435,973,837 80% 50,859,008 1%
/15 8,589,934,592 6,871,947,674 80% 88,550,677 1%
/14 17,179,869,184 13,743,895,348 80% 154,175,683 1%
/13 34,359,738,368 27,487,790,695 80% 268,435,456 1%
/12 68,719,476,736 54,975,581,389 80% 467,373,275 1%
/11 137,438,953,472 109,951,162,778 80% 813,744,135 1%
/10 274,877,906,944 219,902,325,556 80% 1,416,810,831 1%
/9 549,755,813,888 439,804,651,111 80% 2,466,810,934 0%
/8 1,099,511,627,776 879,609,302,221 80% 4,294,967,296 0%
/7 2,199,023,255,552 1,759,218,604,442 80% 7,477,972,398 0%
/6 4,398,046,511,104 3,518,437,208,884 80% 13,019,906,166 0%
/5 8,796,093,022,208 7,036,874,417,767 80% 22,668,973,294 0%
/16 4,294,967,296 3,435,973,837 80% 50,859,008 1%
/15 8,589,934,592 6,871,947,674 80% 88,550,677 1%
/14 17,179,869,184 13,743,895,348 80% 154,175,683 1%
/13 34,359,738,368 27,487,790,695 80% 268,435,456 1%
/12 68,719,476,736 54,975,581,389 80% 467,373,275 1%
/11 137,438,953,472 109,951,162,778 80% 813,744,135 1%
/10 274,877,906,944 219,902,325,556 80% 1,416,810,831 1%
/9 549,755,813,888 439,804,651,111 80% 2,466,810,934 0%
/8 1,099,511,627,776 879,609,302,221 80% 4,294,967,296 0%
/7 2,199,023,255,552 1,759,218,604,442 80% 7,477,972,398 0%
/6 4,398,046,511,104 3,518,437,208,884 80% 13,019,906,166 0%
/5 8,796,093,022,208 7,036,874,417,767 80% 22,668,973,294 0%
Table 1. Comparison of Fixed Efficiency Threshold vs HD-Ratio Threshold
表1。固定效率阈值与高清比率阈值的比较
Figure 7
图7
One possible assumption behind the HD-Ratio is that the inefficiencies that are a consequence of large-scale deployments are an outcome of an increased number of levels of hierarchical structure within the network. The following table calculates the depth of the hierarchy in order to achieve a 0.8 HD-Ratio, assuming a 0.8 utilization efficiency at each level in the hierarchy.
HD比率背后的一个可能假设是，大规模部署导致的低效率是网络中层次结构数量增加的结果。下表计算层次结构的深度，以实现0.8高清比率，假设层次结构中每个级别的利用率为0.8。
Prefix Size 0.8 Structure
HD-Ratio Levels
/48 1 1 1
/47 2 2 1
/46 4 3 2
/45 8 5 2
/44 16 9 3
/43 32 16 4
/42 64 28 4
/41 128 49 5
/40 256 84 5
/39 512 147 6
/38 1,024 256 7
/37 2,048 446 7
/36 4,096 776 8
/35 8,192 1,351 9
/34 16,384 2,353 9
/33 32,768 4,096 10
/32 65,536 7,132 10
/31 131,072 12,417 11
/30 262,144 21,619 12
/29 524,288 37,641 12
/28 1,048,576 65,536 13
Prefix Size 0.8 Structure
HD-Ratio Levels
/48 1 1 1
/47 2 2 1
/46 4 3 2
/45 8 5 2
/44 16 9 3
/43 32 16 4
/42 64 28 4
/41 128 49 5
/40 256 84 5
/39 512 147 6
/38 1,024 256 7
/37 2,048 446 7
/36 4,096 776 8
/35 8,192 1,351 9
/34 16,384 2,353 9
/33 32,768 4,096 10
/32 65,536 7,132 10
/31 131,072 12,417 11
/30 262,144 21,619 12
/29 524,288 37,641 12
/28 1,048,576 65,536 13
/27 2,097,152 114,105 14
/26 4,194,304 198,668 14
/25 8,388,608 345,901 15
/24 16,777,216 602,249 15
/23 33,554,432 1,048,576 16
/22 67,108,864 1,825,677 17
/21 134,217,728 3,178,688 17
/20 268,435,456 5,534,417 18
/19 536,870,912 9,635,980 19
/18 1,073,741,824 16,777,216 19
/17 2,147,483,648 29,210,830 20
/16 4,294,967,296 50,859,008 20
/15 8,589,934,592 88,550,677 21
/14 17,179,869,184 154,175,683 22
/13 34,359,738,368 268,435,456 22
/12 68,719,476,736 467,373,275 23
/11 137,438,953,472 813,744,135 23
/10 274,877,906,944 1,416,810,831 24
/9 549,755,813,888 2,466,810,934 25
/8 1,099,511,627,776 4,294,967,296 25
/27 2,097,152 114,105 14
/26 4,194,304 198,668 14
/25 8,388,608 345,901 15
/24 16,777,216 602,249 15
/23 33,554,432 1,048,576 16
/22 67,108,864 1,825,677 17
/21 134,217,728 3,178,688 17
/20 268,435,456 5,534,417 18
/19 536,870,912 9,635,980 19
/18 1,073,741,824 16,777,216 19
/17 2,147,483,648 29,210,830 20
/16 4,294,967,296 50,859,008 20
/15 8,589,934,592 88,550,677 21
/14 17,179,869,184 154,175,683 22
/13 34,359,738,368 268,435,456 22
/12 68,719,476,736 467,373,275 23
/11 137,438,953,472 813,744,135 23
/10 274,877,906,944 1,416,810,831 24
/9 549,755,813,888 2,466,810,934 25
/8 1,099,511,627,776 4,294,967,296 25
Table 2: Number of Structure Levels Assumed by HD-Ratio
表2:HD比率假设的结构层数
Figure 8
图8
An alternative approach is to use a model of network deployment where the number of levels of hierarchy increases at a lower rate than that indicated in a 0.8 HD-Ratio model. One such model is indicated in the following table. This is compared to using an HD-Ratio value of 0.94.
另一种方法是使用网络部署模型，其中层次结构的数量以低于0.8 HD比率模型中所示的速度增加。下表中显示了一种此类模型。这与使用0.94的HD比率值进行比较。
Per-Level Target Efficiency: 0.75
每级目标效率：0.75
Prefix Size Stepped Stepped Efficiency HD-Ratio Levels 0.75 0.94
前缀大小分级效率HD比率级别0.75 0.94
/48 1 1 1 100% 1 100%
/47 2 1 2 100% 2 100%
/46 4 1 3 75% 4 100%
/45 8 1 6 75% 7 88%
/44 16 1 12 75% 13 81%
/43 32 1 24 75% 25 78%
/42 64 1 48 75% 48 75%
/41 128 1 96 75% 92 72%
/40 256 1 192 75% 177 69%
/39 512 2 384 75% 338 66%
/38 1,024 2 576 56% 649 63%
/37 2,048 2 1,152 56% 1,244 61%
/48 1 1 1 100% 1 100%
/47 2 1 2 100% 2 100%
/46 4 1 3 75% 4 100%
/45 8 1 6 75% 7 88%
/44 16 1 12 75% 13 81%
/43 32 1 24 75% 25 78%
/42 64 1 48 75% 48 75%
/41 128 1 96 75% 92 72%
/40 256 1 192 75% 177 69%
/39 512 2 384 75% 338 66%
/38 1,024 2 576 56% 649 63%
/37 2,048 2 1,152 56% 1,244 61%
/36 4,096 2 2,304 56% 2,386 58%
/35 8,192 2 4,608 56% 4,577 56%
/34 16,384 2 9,216 56% 8,780 54%
/33 32,768 2 18,432 56% 16,845 51%
/32 65,536 2 36,864 56% 32,317 49%
/31 131,072 3 73,728 56% 62,001 47%
/30 262,144 3 110,592 42% 118,951 45%
/29 524,288 3 221,184 42% 228,210 44%
/28 1,048,576 3 442,368 42% 437,827 42%
/27 2,097,152 3 884,736 42% 839,983 40%
/26 4,194,304 3 1,769,472 42% 1,611,531 38%
/25 8,388,608 3 3,538,944 42% 3,091,767 37%
/24 16,777,216 3 7,077,888 42% 5,931,642 35%
/23 33,554,432 4 14,155,776 42% 11,380,022 34%
/22 67,108,864 4 21,233,664 32% 21,832,894 33%
/21 134,217,728 4 42,467,328 32% 41,887,023 31%
/20 268,435,456 4 84,934,656 32% 80,361,436 30%
/19 536,870,912 4 169,869,312 32% 154,175,684 29%
/18 1,073,741,824 4 339,738,624 32% 295,790,403 28%
/17 2,147,483,648 4 679,477,248 32% 567,482,240 26%
/16 4,294,967,296 4 1,358,954,496 32% 1,088,730,702 25%
/15 8,589,934,592 5 2,717,908,992 32% 2,088,760,595 24%
/14 17,179,869,184 5 4,076,863,488 24% 4,007,346,185 23%
/13 34,359,738,368 5 8,153,726,976 24% 7,688,206,818 22%
/12 68,719,476,736 5 16,307,453,952 24% 14,750,041,884 21%
/11 137,438,953,472 5 32,614,907,904 24% 28,298,371,876 21%
/10 274,877,906,944 5 65,229,815,808 24% 54,291,225,552 20%
/9 549,755,813,888 5 130,459,631,616 24% 104,159,249,331 19%
/8 1,099,511,627,776 5 260,919,263,232 24% 199,832,461,158 18%
/36 4,096 2 2,304 56% 2,386 58%
/35 8,192 2 4,608 56% 4,577 56%
/34 16,384 2 9,216 56% 8,780 54%
/33 32,768 2 18,432 56% 16,845 51%
/32 65,536 2 36,864 56% 32,317 49%
/31 131,072 3 73,728 56% 62,001 47%
/30 262,144 3 110,592 42% 118,951 45%
/29 524,288 3 221,184 42% 228,210 44%
/28 1,048,576 3 442,368 42% 437,827 42%
/27 2,097,152 3 884,736 42% 839,983 40%
/26 4,194,304 3 1,769,472 42% 1,611,531 38%
/25 8,388,608 3 3,538,944 42% 3,091,767 37%
/24 16,777,216 3 7,077,888 42% 5,931,642 35%
/23 33,554,432 4 14,155,776 42% 11,380,022 34%
/22 67,108,864 4 21,233,664 32% 21,832,894 33%
/21 134,217,728 4 42,467,328 32% 41,887,023 31%
/20 268,435,456 4 84,934,656 32% 80,361,436 30%
/19 536,870,912 4 169,869,312 32% 154,175,684 29%
/18 1,073,741,824 4 339,738,624 32% 295,790,403 28%
/17 2,147,483,648 4 679,477,248 32% 567,482,240 26%
/16 4,294,967,296 4 1,358,954,496 32% 1,088,730,702 25%
/15 8,589,934,592 5 2,717,908,992 32% 2,088,760,595 24%
/14 17,179,869,184 5 4,076,863,488 24% 4,007,346,185 23%
/13 34,359,738,368 5 8,153,726,976 24% 7,688,206,818 22%
/12 68,719,476,736 5 16,307,453,952 24% 14,750,041,884 21%
/11 137,438,953,472 5 32,614,907,904 24% 28,298,371,876 21%
/10 274,877,906,944 5 65,229,815,808 24% 54,291,225,552 20%
/9 549,755,813,888 5 130,459,631,616 24% 104,159,249,331 19%
/8 1,099,511,627,776 5 260,919,263,232 24% 199,832,461,158 18%
Table 3: Limited Levels of Structure
表3：有限的结构层次
Figure 9
图9
Author's Address
作者地址
Geoff Huston APNIC
杰夫·休斯顿呼吸暂停
EMail: gih@apnic.net
EMail: gih@apnic.net
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