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Versions: 00 01 02 03 04 05 06 07 08 09 RFC 6837

Network Working Group                                            E. Lear
Internet-Draft                                        Cisco Systems GmbH
Intended status: Experimental                         September 19, 2007
Expires: March 22, 2008


               NERD: A Not-so-novel EID to RLOC Database
                      draft-lear-lisp-nerd-02.txt

Status of this Memo

   By submitting this Internet-Draft, each author represents that any
   applicable patent or other IPR claims of which he or she is aware
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   This Internet-Draft will expire on March 22, 2008.

Copyright Notice

   Copyright (C) The IETF Trust (2007).

Abstract

   LISP is a protocol to encapsulate IP packets in order to allow end
   sites to multihome without injecting routes from one end of the
   Internet to another.  This memo specifies a database and a method to
   transport the mapping of EIDs to RLOCs to routers in a reliable,
   scalable, and secure manner.  Our analysis concludes that transport
   of of all EID/RLOC mappings scales well to at least 10^8 entries, and
   that use of DNS or any approach that queries for mappings has
   substantial operational concerns.



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Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
     1.1.  Base Assumptions . . . . . . . . . . . . . . . . . . . . .  3
     1.2.  What is NERD?  . . . . . . . . . . . . . . . . . . . . . .  4
     1.3.  Glossary . . . . . . . . . . . . . . . . . . . . . . . . .  5
   2.  Theory of Operation  . . . . . . . . . . . . . . . . . . . . .  5
     2.1.  Who are database authorities?  . . . . . . . . . . . . . .  6
   3.  NERD Format  . . . . . . . . . . . . . . . . . . . . . . . . .  7
     3.1.  NERD Record Format . . . . . . . . . . . . . . . . . . . .  9
     3.2.  Database Update Format . . . . . . . . . . . . . . . . . . 10
   4.  NERD Distribution Mechanism  . . . . . . . . . . . . . . . . . 10
     4.1.  Initial Bootstrap  . . . . . . . . . . . . . . . . . . . . 10
     4.2.  Retrieving Changes . . . . . . . . . . . . . . . . . . . . 10
   5.  Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
     5.1.  Database Size  . . . . . . . . . . . . . . . . . . . . . . 12
     5.2.  Router Throughput Versus Time  . . . . . . . . . . . . . . 14
     5.3.  Number of Servers Required . . . . . . . . . . . . . . . . 14
     5.4.  Security Considerations  . . . . . . . . . . . . . . . . . 16
       5.4.1.  Use of Public Key Infrastructures (PKIs) . . . . . . . 17
       5.4.2.  Other Risks  . . . . . . . . . . . . . . . . . . . . . 19
   6.  Why not use XML? . . . . . . . . . . . . . . . . . . . . . . . 19
   7.  Other Distribution Mechanisms  . . . . . . . . . . . . . . . . 20
     7.1.  What About DNS as a retrieval model? . . . . . . . . . . . 21
       7.1.1.  Perhaps use a hybrid model?  . . . . . . . . . . . . . 22
     7.2.  Use of BGP . . . . . . . . . . . . . . . . . . . . . . . . 23
   8.  Deployment Issues  . . . . . . . . . . . . . . . . . . . . . . 23
     8.1.  HTTP . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
   9.  Conclusions  . . . . . . . . . . . . . . . . . . . . . . . . . 24
   10. IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 25
   11. Acknowledgments  . . . . . . . . . . . . . . . . . . . . . . . 25
   12. References . . . . . . . . . . . . . . . . . . . . . . . . . . 25
     12.1. Normative References . . . . . . . . . . . . . . . . . . . 25
     12.2. Informational References . . . . . . . . . . . . . . . . . 26
   Appendix A.  Generating and verifying the database signature
                with OpenSSL  . . . . . . . . . . . . . . . . . . . . 27
   Appendix B.  Changes . . . . . . . . . . . . . . . . . . . . . . . 28
   Appendix C.  Open Questions  . . . . . . . . . . . . . . . . . . . 28
   Author's Address . . . . . . . . . . . . . . . . . . . . . . . . . 29
   Intellectual Property and Copyright Statements . . . . . . . . . . 30











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1.  Introduction

   Locator/ID Separation Protocol (LISP) [1] is a protocol whose primary
   purpose is to separate an IP address used by a host and local routing
   system from the locators advertised by BGP participants on the
   Internet in general, and in the default free zone (DFZ) in
   particular.  It accomplishes this by establishing a mapping between
   globally unique endpoint identifiers (EIDs) and routing locators
   (RLOCs) within the global routing table.  This reduces the amount of
   state change that occurs on routers within the default-free zone on
   the Internet, while enabling end sites to be multihomed.

   In early stages of LISP (1 and 1.5) the mapping is either configured
   into a device or it is learned via data-triggered control messages
   between ingress tunnel routers (ITRs) and egress tunnel routers
   (ETRs) under the assumption that during transition, EIDs will be
   present within the global routing system, as they are today.

   In later stages of LISP, the assumption will be that EIDs are not
   contained within the global routing system, but that instead the
   mapping from EIDs to RLOCs will be learned through some other means.
   This memo addresses different approaches to the problem, and
   specifies a Not-so-novel EID RLOC Database (NERD) and methods to both
   receive the database and to receive updates.

   LISP and NERD are both currently experimental stages.  The NERD
   database is specified in such a way that the methods used to
   distribute or retrieve it may vary over time.  Multiple databases are
   supported in order to allow for multiple data sources.  An effort has
   been made to divorce the database from access methods so that both
   can evolve independently through experimentation and operational
   validation.

1.1.  Base Assumptions

   In order to specify a mapping it is important to understand how it
   will be used, and the nature of the data being mapped.  In the case
   of LISP, the following assumptions are pertinant:

   o  The data contained within the mapping changes only on provisioning
      or configuration operations, and is not intended to change when a
      link either fails or is restored.  Some other mechanism (via LISP
      or other) handles healing operations, particularly when a tail
      circuit within an service provider's aggregate goes down.
   o  While weight and priority are defined, these are not hop-by-hop
      metrics.  Hence the information contained within the mapping does
      not change based on where one sits within the topology.




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   o  The purpose of LISP being to reduce control plane overhead by
      reducing "rate X state" complexity, updates to the mapping will be
      relatively rare.
   o  Because LISP and NERD are designed to ease interdomain routing,
      their use is intended within the inter-domain environment.  That
      is, LISP is best implemented at either the customer edge or
      provider edge, and there will be on the order of as many ITRs and
      LISP announcements as there are connections to Internet Service
      Providers by end customers.
   o  As such, LISP and NERD cannot be the sole means to implement host
      mobility, although they may be in used in conjunction with other
      mechanisms.  For instance, it would be possible for a mobile node
      to receive a local address that is an EID and pass that to the
      correspondant node, who could also make use of an EID.  As such
      use of LISP in this case would be transparent, and no mapping
      entries are changed for mobility.
   o  As such, there is no interaction with the interior gateway
      protocol (IGP).


1.2.  What is NERD?

   NERD is a Not-so-novel EID to RLOC Database.  It consists of the
   following components:

   1.  a network database format;
   2.  a change distribution format;
   3.  a database retrieval/bootstrapping method;
   4.  a change distribution method.

   The network database format is compressable.  However, at this time
   we specify no compression method.  NERD will make use of potentially
   several transport methods, but most notably HTTP [2].  HTTP has
   restart and compression capabilities.  It is also widely deployed.

   There exist many methods to show differences between two versions of
   a database or a file, UNIX's "diff" being the classic example.  In
   this case, because the data is well structured and easily keyed, we
   can make use of a very simple format for version differences that
   simply provides a list of EID/RLOC mappings that have changed using
   the same record format as the database, and a list of EIDs that are
   to be removed.

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [3].





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1.3.  Glossary

   The reader is once again referred to [1] for a general glossary of
   terms related to LISP.  The following terms are specific to this
   memo.


   Base Distribution URI:  An Absolute-URI as defined in Section 4.3 of
      [6] from which other references are relative.  The base
      distribution URI is used to construct a URI to an EID/RLOC mapping
      database.  If more than one NERD is known then there will be one
      or more base distribution URIs associated with each (although each
      such base distribution URI may have the same value).

   EID Database Authority:  The authority that will sign database files
      and updates.  It is the source of both.

   The Authority:  Shorthand for the EID Database Authority.

   NERD:  (N)ot-so-novel (E)ID to (R)LOC (D)atabase.

   AFI  Address Family Identifier.

   Pull Model:  An architecture where clients pull only the information
      they need at any given time, such as when a packet arrives for
      forwarding.

   Push Model:  An architecture in which clients receive an entire
      dataset, containing data they may or may not require, such as
      mappings for EIDs that no host served is attempting to send to.

   Hybrid Model:  An architecture in which clients receive a subset of
      the entire dataset and query as needed for the rest.



2.  Theory of Operation

   What follows is a summary of how NERDs are generated and updated.
   Specifics can be found in Section 3.  The general way in which NERD
   works is as follows:

   1.  A NERD is generated by an authority that allocates provider
       independent (PI) addresses (e.g., IANA or an RIR) which are used
       by sites as EIDs.  As part of this process the authority
       generates a digest for the database and signs it with a private
       key whose public key is part of an X.509 certificate. [12] That
       signature along with a copy of the authority's public key is



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       included in the NERD.
   2.  The NERD is distributed to a group of well known servers.
   3.  ITRs retrieve an initial copy of the NERD via HTTP when they come
       into service.
   4.  ITRs are preconfigured with a group of certificates whose private
       keys are used by database authorities to sign the NERD.  This
       list of certificates should be configurable by administrators.
   5.  ITRs next verify both the validity of the public key and the
       signed digest.  If either fail validation, the ITR attempts to
       retrieve the NERD from a different source.  The process iterates
       until either a valid database is found or the list of sources is
       exhausted.
   6.  Once a valid NERD is retrieved, the ITR installs it into both
       non-volatile and local memory.
   7.  At some point the authority updates the NERD and increments the
       database version counter.  At the same time it generates a list
       of changes, which it also signs, as it does with the original
       database.
   8.  Periodically ITRs will poll from their list of servers to
       determine if a new version of the database exists.  When a new
       version is found, an ITR will attempt to retrieve a change file,
       using its list of preconfigured servers.
   9.  The ITR validates a change file just as it does the original
       database.  Assuming the change file passes validation, the ITR
       installs new entries, overwrites existing ones, and removes empty
       entries, based on the content of the change file.

   As time goes on it is quite possible that an ITR may probe a list of
   configured neighbors for a database or change file copy.  It is
   equally possible that neighbors might advertise to each other the
   version number of their database.  Such methods are not explored in
   detph in this memo, but are mentioned for future consideration.

2.1.  Who are database authorities?

   This memo does not specify who the database authority is.  That is
   because there are several possible operational models.  In each case
   the number of database authorities is meant to be small so that ITRs
   need only keep a small list of authorities, similar to the way a name
   server might cache a list of root servers.

   o  A single database authority exists.  In this case all entries in
      the database are registered to a single entity, and that entity
      distributes the database.  Because the EID space is provider
      independent address space, there is no architectural requirement
      that address space be hierarchically distributed to anyone, as
      there is with provider-assigned address space.  Hence, there is a
      natural affinity between the IANA function and the database



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      authority function.
   o  Each region runs a database authority.  In this case, provider
      independent address space is allocated to either regional internet
      registries or to affiliates of such organizations of network
      operations guilds (NOGs).  The benefit of this approach is that
      there is no single organization that controls the database.  It
      allows one database authority to backup another.  One could
      envision as many as ten database authorities in this scenario.
   o  Each country runs a database authority.  This could occur should
      countries decide to regulate this function.  While limiting the
      scope of any single database authority as the previous scenario
      describes, this approach would introduce some overhead as the list
      of database authorities would grow to as many as 200, and possibly
      more if jurisdictions within countries attempted to regulate the
      function.

   As the number of authorities increases the amount of change on that
   list will also increase, requiring both an update mechanism and the
   potential need for a discovery mechanism, both of which would be the
   subject of future work (i.e., not to be found in this memo).  For
   this reason alone, as a starting point two database authorities are
   recommended, but their selection is left for others.


3.  NERD Format

   The NERD consists of a header that contains a database version and a
   signature that is generated by ignoring the signature field and
   setting the authentication block length to 0 (NULL).  The
   authentication block itself consists of a signature and a certificate
   whose private key counterpart was used to generate the signature.
   The exact format of the authentication block is TBD.

   Records are kept sorted in numeric order with AFI plus EID as primary
   key and mask length as secondary.  This is so that after a database
   update it should be possible to reconstruct the database to verify
   the digest signature, which may be retrieved separately from the
   database for verification purposes.













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        0                   1                   2                   3
        0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       | Schema Vers=1 |  DB Code      |     Database Name Size        |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                      Database Version                         |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                   Old Database Version or 0                   |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                                                               |
       |                        Database Name                          |
       |                                                               |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |       PKCS#7 Block Size       |          Reserved             |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                                                               |
       |      PKCS#7 Block containing Certificate and Signature        |
       |                                                               |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+




   Database Header

   The DB Code indicates 0 if what follows is an entire database or 1 if
   what follows is an update.  The database file version is incremented
   each time the complete database is generated by the authority.  In
   the case of an update, the database file version indicates the new
   database file version, and the old database file version is indicated
   in the "old DB version" field.  The database file version is used by
   routers to determine whether or not they have the most current
   database.

   The database name is a Universal Resource Name (URN) [7] of the
   following form:


       dburn  = "urn:lisp:3.0:" dbname
       dbname = 1*(URN Chars)  ;; URN Chars is defined in RFC 2141.


   The purpose of the database name is to allow for more than one
   database.  Such databases would be merged by the router.  It is
   important that an EID/RLOC mapping be listed in no more than one
   database, lest inconsistencies arise.  However, it may be possible to
   transition a mapping from one database to another.  During the
   transition period, the mappings MUST be identical.  When they are



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   not, the resultant behavior will be undefined.

   The PKCS#7 [4] authentication block contains a DER encoded [5]
   signature and associated public key.

3.1.  NERD Record Format

   As distributed over the network, NERD records appear as follows:



        0                   1                   2                   3
        0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       | Num. RLOCs    | EID Mask Len  |            EID AFI            |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                       End point identifier                    |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       | Priority 1    |    Weight 1   |             AFI 1             |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                       Routing Locator 1                       |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       | Priority 2    |    Weight 2   |             AFI 2             |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                       Routing Locator 2                       |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       | Priority 3    |    Weight 3   |             AFI 3             |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
       |                       Routing Locator 3...                    |
       +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+



   Priority N and Weight N, and AFI N are associated with Routing
   Locator N. There will always be at least one routing locator.  The
   minimum record size for IPv4 is 16 bytes.  Each additional IPv4 RLOC
   increases the record size by 8 bytes.  The purpose of this format is
   to keep the database compact, but somewhat easily read.  The meaning
   of weight and priority are described in [1].  The format of the AFI
   is specified by IANA as "Address Family Numbers", with the exception
   of how IPv6 addresses are stored.

   In order to reduce storage and transmission amounts for IPv6, only
   the necessary number of bytes as specified by the prefix length are
   kept in the record, rounded to the nearest four byte (word) boundary.
   This is true for both EIDs and RLOCs.  For instance, if the prefix
   length is /49, the nearest four-byte word boundary would require that
   eight bytes are stored.



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3.2.  Database Update Format

   A database update contains a set of changes to an existing database.
   Each AFI/EID/mask-length tuple may have zero or more RLOCs associated
   with it.  In the case where there are no RLOCs, the EID entry is
   removed from the database.  Records that contain EIDs and mask
   lengths that were not previously listed are simply added.  Otherwise,
   the old record for the EID and mask length is replaced by the more
   current information.  The record format used by the a database update
   is the same as described in Section 3.1.


4.  NERD Distribution Mechanism

4.1.  Initial Bootstrap

   Bootstrap occurs when a router needs to retrieve the entire database.
   It knows it needs to retrieve the entire database because either it
   has none or an update too substantial to process, as might be the
   case if a router has been out of service for a substantially lengthy
   period of time.

   To bootstrap the router appends the database name plus "/current/
   entiredb" to a Base Distribution URI and retrieves the file via HTTP.
   For example, if the configured URI is
   "http://www.example.com/eiddb/", and assuming a database name of
   "arin", the router would request
   "http://www.example.com/eiddb/current/arin/entiredb".  Routers MUST
   check the signature on the database prior to installing it, and MUST
   check that the database schema matches a schema they understand.
   Once a router has a valid database it MUST store that database in
   some sort of non-volatile memory (e.g., disk, flash memory, etc).

   N.B., the host component for such URIs MUST NOT resolve to a LISP
   EID, lest a circular dependency be created.

4.2.  Retrieving Changes

   In order to retrieve a set of database changes a router will have
   previously retrieved the entire database.  Hence it knows the current
   version of the database it has.  Its first step for retrieving
   changes is to retrieve the current version of the database.  It does
   so by appending "current/version" to the base distribution URI and
   retrieving the file.  Its format is text and it contains the integer
   value of the current database version.

   Once a router has retrieved the current version it compares version
   of its local copy.  If there is no difference, then the router is up



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   to date and need take no further actions until it next checks.

   If the versions differ, the router next sends a request for the
   appropriate change file by appending "current/changes/" and the
   textual representation of the version of its local copy of the
   database to the base distribution URI.  For example, if the current
   version of the database is 1105503 and router's version is 1105500,
   and the base URI and database name are the same as above, the router
   would request
   "http://www.example.com/eiddb/arin/current/changes/1105500".

   The server may not have that change file, either because there are
   too many versions between what the router has and what is current, or
   because no such change file was generated.  If the server has changes
   from the routers version to any later version, the server SHOULD
   issue an HTTP redirect to that change file, and the router SHOULD
   retrieve and process it.  Once it has done so, the router should then
   repeat the process until it has brought itself up to date.  It is
   thus important for servers to expire old change files in the order in
   which they were generated.

   By way of convention, it is suggested that the URIs issued in
   redirects be of the following form:

   {base dist.  URI}/{dbname}/{more-recent-version}/changes/
   {older-version}

   where "base dist.  URI" is the base distribution URI, "dbname" is the
   name of the database, and each version is the textual representation
   of the integer version value.

   For example, if the current database version was 1105503 and a router
   made a request for
   "http://www.example.com/eiddb/arin/current/changes/1105400" but there
   was no change file from 1105400 to 1105503, and the server had a
   group of change files to make the router current, it would issue a
   redirect to
   "http://www.example.com/eiddb/arin/110450/changes/1105400" that the
   router would then process.  The router would then make a request for
   "http://www.example.com/eiddb/arin/current/changes/110450" that the
   server would have.

   While it is unlikely that database versions would wrap, as they
   consists of 32 bit integers, should the event occur, ITRs MUST
   attempt first to retrieve a change file when their current version
   number is within 10,000 of 2^32 and they see a version available that
   is less than 10,000.  Barring the availability of a change file, the
   ITR MUST still assume that the database version has wrapped and



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   retrieve a new copy.


5.  Analysis

   We will start our analysis by looking at how much data will be
   transferred to a router during bootstrap conditions.  We will then
   look at the bandwidth required.  Next we will turn our concerns to
   servers.  Finally we will ponder the effect of providing only
   changes.

   In the analysis below we treat the overhead of the database header as
   insignificant (because it is).  The analysis should be similar,
   whether a single database or multiple databases are employed, as we
   would assume that no entry would appear more than once.

5.1.  Database Size

   By its very nature the information to be transported is relatively
   static and is specifically designed to be topologically insensitive.
   That is, every ITR is intended to have the same set of RLOCs for a
   given EID.  While some processing power will be necessary to install
   a table, the amount required should be far less than that of a
   routing information database because the level of entropy is intended
   to be lower.

   For purposes of this analysis, we will assume that the world has
   migrated to IPv6, as this increases the size of the database, which
   would be our primary concern.  However, to mitigate the size
   increase, we have limited the size of the prefix transmitted.  For
   purposes of this analysis, we shall assume an average prefix length
   of 64 bits.

   Based on that assumption, Section 3.1 states that mapping information
   for each EID/Prefix includes a group of RLOCs, each with an
   associated priority and weight, and that a minimum record size with
   IPv6 EIDs with at least one RLOC is 24 bytes uncompressed.  Each
   additional IPv6 RLOC costs 12 bytes (again, assuming an average
   prefix length of 64 bits).












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                 +-----------+--------+--------+---------+
                 | 10^n EIDs | 2 RLOC | 4 RLOC |  8 RLOC |
                 +-----------+--------+--------+---------+
                 |         4 | 360 KB | 600 KB | 1.08 MB |
                 |         5 | 3.6 MB | 6.0 MB | 10.8 MB |
                 |         6 |  36 MB |  60 MB |  108 MB |
                 |         7 | 360 MB | 600 MB | 1.08 GB |
                 |         8 | 3.6 GB | 6.0 GB | 10.8 GB |
                 +-----------+--------+--------+---------+

    Database size for IPv6 routes with average prefix length = 64 bits

                                  Table 1

   Entries in the above table are derived as follows:


        E * (24 + 12 * (R -1 ))


   where E = number of EIDs (10^n), R = number of RLOCs per EID.

   Our scaling target is to accommodate 10^8 multihomed systems, which
   is one order magnitude greater than what is discussed in [10].  At
   10^8 entries, a device could be expected to use between 3.6 and 10.8
   and gigabytes of RAM for the mapping.  No matter the method of
   distribution, any router that sits in the core of the Internet would
   require near this amount of memory in order to perform the ITR
   function.  Large enterprise ETRs would be similarly strained, simply
   due to the diversity of of sites that communicate with one another.
   The good news is that this is not our starting point, but rather our
   scaling target, a number that we intend to reach by the year 2050.
   Our starting point is more likely in the neighborhood of 10^4 or 10^5
   EIDs, thus requiring between 360KB and 10.8 MB.

















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5.2.  Router Throughput Versus Time

        +-------------------+---------+--------+---------+-------+
        | Table Size (10^N) |   1mb/s | 10mb/s | 100mb/s | 1gb/s |
        +-------------------+---------+--------+---------+-------+
        |                 6 |       8 |    0.8 |    0.08 | 0.008 |
        |                 7 |      80 |      8 |     0.8 |  0.08 |
        |                 8 |     800 |     80 |       8 |   0.8 |
        |                 9 |   8,000 |    800 |      80 |     8 |
        |                10 |  80,000 |  8,000 |     800 |    80 |
        |                11 | 800,000 | 80,000 |   8,000 |   800 |
        +-------------------+---------+--------+---------+-------+

                     Number of seconds to process NERD

                                  Table 2

   The length of time it takes to process the database is significant in
   models where the device acquires the entire table.  During this
   period of time, either the router will be unable to route packets
   using LISP or it must use some sort of query mechanism for specific
   EIDs as the rest it populates its table through the transfer.
   Table 2 shows us that at our scaling target, the length of time it
   would take for a router using 1 mb/s of bandwidth is about 80
   seconds.  We can measure the processing rate in small numbers of
   hours for any transfer speed greater than that.  The fastest
   processing time shows us as taking 8 seconds to process an entire
   table of 10^9 bytes and 80 for 10^10 bytes.

5.3.  Number of Servers Required

   As easy as it may be for a router to retrieve, the aggregate
   information may be difficult for servers to transmit, assuming the
   information is transmitted in aggregate (we'll revisit that
   assumption later).
















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   +----------------+------------+-----------+------------+------------+
   | # Simultaneous | 10 Servers |       100 |      1,000 |     10,000 |
   |       Requests |            |   Servers |    Servers |    Servers |
   +----------------+------------+-----------+------------+------------+
   |            100 |        480 |        48 |         48 |         48 |
   |          1,000 |      4,800 |       480 |         48 |         48 |
   |         10,000 |     48,000 |     4,800 |        480 |         48 |
   |        100,000 |    480,000 |    48,000 |      4,800 |        480 |
   |      1,000,000 |  4,800,000 |   480,000 |     48,000 |      4,800 |
   |     10,000,000 | 48,000,000 | 4,800,000 |    480,000 |     48,000 |
   +----------------+------------+-----------+------------+------------+

     Retrieval time per number of servers in seconds.  Assumes average
   10^8 entries with 4 RLOCs per EID and that each server has access to
    1gb/s and 100% efficient use of that bandwidth and no compression.

                                  Table 3

   Entries in the above table were generated using the following method:

   For 10^8 entries with four RLOCs per EID, the table size is 6.0GB,
   per our previous table.  Assume 1 Gb/s transfer rates and 100%
   utilization.  Protocol overhead is ignored for this exercise.  Hence
   a single transfer X takes 48 seconds and can get no faster.

   With this in mind, each entry is as follows:


            max(1X,N*X/S)

     where N=number of transfers, X = 48 seconds,
     and S = number of servers.


   If we have a distribution model which every device must retrieve the
   mapping information upon start, Table 3 shows the length of time in
   seconds it will take for a given number of servers to complete a
   transfer to a given number of devices.  This table says, as an
   example, that it would take 48,000 seconds (over 13 hours) for one
   million ITRs to simultaneously retrieve the database from one
   thousand servers.  Should a cold start scenario occur, this number
   should be of some concern.  Hence it is important to take some
   measures both to avoid such a scenario, and to ease the load should
   it occur.  The primary defense should be for ITRs to first attempt to
   retrieve their databases from their peers or upstream providers.
   Secondary defenses could include data sanity checks within ITRs, with
   agreed norms for how much the database should change in any given
   update or over any given period of time.  As we will see below,



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   dissemination of changes is considerably less volume.

     +----------------+-------------+---------------+----------------+
     | % Daily Change | 100 Servers | 1,000 Servers | 10,000 Servers |
     +----------------+-------------+---------------+----------------+
     |           0.1% |         200 |            20 |              2 |
     |           0.5% |        1000 |           100 |             10 |
     |             1% |        2000 |           200 |             20 |
     |             5% |      10,000 |          1000 |            100 |
     |            10% |      20,000 |          2000 |            200 |
     +----------------+-------------+---------------+----------------+

     Assuming 10 million routers and a database size of 6GB, resulting
    hourly transfer times are shown in seconds, given number of servers
                         and daily rate of change.

                                  Table 4

   This table shows us that with 10,000 servers the average transfer
   time with 1Gb/s links for 10,000,000 routers will be 200 seconds with
   10% daily change spread over 24 hourly updates.  For a 0.1% daily
   change, that number is 2 seconds for a database of size 6.0GB.

   The amount of change goes to the purpose of LISP.  If its purpose is
   to provide effective multihoming support to end customers, then we
   might anticipate relatively random changes.  If, on the other,
   service providers attempt to make use of LISP to provide some form of
   traffic engineering, we can expect the same data to change more
   often.  We can probably not conclude much in this regard without
   additional operational experience.  The one thing we can say is that
   different applications of the LISP protocol may require new and
   different distribution mechanisms.  Such optimization is left for
   another day.

5.4.  Security Considerations

   Whichever the answer to our previous question, we must consider the
   security of the information being transported.  If an attacker can
   forge an update or tamper with the database, he can in effect
   redirect traffic to end sites.  Hence, integrity and authenticity of
   the NERD is critical.  In addition, a means is required to determine
   whether a source is authorized to modify a given database.  No data
   privacy is required.  Quite to the contrary, this information will be
   necessary for any ITR.

   The first question one must ask is who to trust to provide the ITR a
   mapping.  Ultimately the owner of the EID prefix is most
   authoritative for the mapping to RLOCs.  However, were all owners to



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   sign all such mappings, ITRs would need to know which owner is
   authorized to modify which mapping, creating a problem of O(N^2)
   complexity.

   We can reduce this problem substantially by investing some trust in a
   small number of entities that are allowed to sign entries.  If
   authority manages EIDs much the same way a domain name registrar
   handles domains, then the owner of the EID would choose a database
   authority she or he trusts, and ITRs must trust each such authority
   in order to map the EIDs listed by that authority to RLOCs.  This
   reduces the amount of management complexity on the ETR to retaining
   knowledge of O(#authorities), but does require that each authority
   establish procedures for authenticating the owner of an EID.  Those
   procedures needn't be the same.

   There are two classic methods to ensure integrity of data:

   o  secure transport of the source of the data to the consumer, such
      as Transport Layer Security (TLS) [8]; and
   o  provide object level security.

   These methods are not mutually exclusive, although one can argue
   about the need for the former, given the latter.

   In the case of TLS, when it is properly implemented, the objects
   being transported cannot easily be modified by interlopers or so-
   called men in the middle.  When data objects are distributed to
   multiple servers, each of those servers must be trusted.  As we have
   seen above, we could have quite a large number of servers, thus
   providing an attacker a large number of targets.  We conclude that
   some form of object level security is required.

   Object level security involves an authority signing an object in a
   way that can easily be verified by a consumer, in this case a router.
   In this case, we would want the mapping table and any incremental
   update to be signed by the originator of the update.  This implies
   that we cannot simply make use of a tool like CVS [11].  Instead, the
   originator will want to generate diffs, sign them, and make them
   available either directly or through some sort of content
   distribution or peer to peer network.

5.4.1.  Use of Public Key Infrastructures (PKIs)

   X.509 provides a certificate hierarchy that has scaled to the size of
   the Internet.  The system is particularly manageable when there are
   fewer certificates to manage.  The model proposed in this memo makes
   use of one current certificate per database authority.  The three
   pieces of information necessary to verify a signature, therefore, are



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   as follows:

   o  the certificate of the database authority, which can be provided
      along with the database;
   o  the certificate authority's certificate; and
   o  A table of database names and distinguished names (DNs) that are
      allowed to update them.

   The latter two pieces of information must be very well known and must
   be configured on each ITR.  It is expected that both would change
   very rarely, and it would not be unreasonable for such updates to
   occur as part of a normal OS release process.

   The tools for both signing and verifying are readily available.
   Openssl [20] provides tools and libraries for both signing and
   verifying.  Other tools commonly exist.

   Use of PKIs is not without implementation, operational complexity or
   risk.  The following risks and mitigations are identified with NERD's
   use of PKIs:


   If a NERD database authority private key is exposed:

      In this case an attacker could sign a false database update,
      either redirecting traffic, or otherwise causing havoc.  In this
      case, the NERD database administrator must revoke its existing key
      and issue a new one.  The certificate is added to a certificate
      revocation list (CRL), which may be distributed with both this and
      other databases, as well as through other channels.  Because this
      event is expected to be rare, and the number of database
      authorities is expected to be small, a CRL will be small.  When a
      router receives a revocation, it checks it against its existing
      databases, and attempts to update the one that is revoked.  This
      implies that prior to issuing the revocation, the database
      authority MUST sign an update with the new key.  Routers SHOULD
      discard updates they have already received that were signed after
      the revocation was generated.  If a router cannot confirm that
      whether the authority's certificate was revoked before or after a
      particular update, it MUST retrieve a fresh new copy of the
      database with a valid signature.

   The private key associated with the CA that signed the Authority's
   certificate is compromised:

      In this case, it becomes possible for an attacker to masquerade as
      the database authority.  To ameliorate damage, the database
      authority SHOULD revoke its certificate and get a new certificate



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      issued from a CA that is not compromised.  Once it has done so,
      the previous procedure is followed.  The compromised certificate
      can be removed during the normal operating system upgrade cycle.

   An algorithm used if either the certificate or the signature is
   cracked:

      This is a catastrophic failure and the above forms of attack
      become possible.  The only mitigation is to make use of a new
      algorithm.  In theory this should be possible, but in practice has
      proven very difficult.  For this reason, additional work is
      recommended to make alternative algorithms available.

   The Database Authority loses its key or disappears:

      In this case nobody can update the existing database.  There are
      few programmatic mitigations.  If the database authority places
      its private keys and suitable amounts of information escrow, under
      agreed upon circumstances, such as no updates for three days, for
      example, the escrow agent would release the information to a party
      competent of generating a database update.


5.4.2.  Other Risks

   Because this specification does not require secure transport, if an
   attacker prevents updates to an ITR for the purposes of having that
   ITR continue to use a compromised ETR, the ITR could continue to use
   an old version of the database without realizing a new version has
   been made available.  If one is worried about such an attack, a
   secure channel such as SSL to a secure chain back to the database
   authority should be used.  It is possible that after some operational
   experience, later versions of this format will contain additional
   semantics to address this attack.

   As discussed above, substantial risk would be a cold start scenario.
   If an attacker found a bug in a common operating system that allowed
   it to erase an ITR's database, and was able to disseminate that bug,
   the collective ability of ITRs to retrieve new copies of the database
   could be taxed by collective demand.  The remedy to this is for
   devices to share copies of the database with their neighbors, thus
   making each potential requestor a potential service.


6.  Why not use XML?

   Many objects these days are distributed as either XML pages or
   something derived as XML [17], such as SOAP [18],[19].  Use of such



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   well known standards allows for high level tools and library reuse.
   Why not, then, use these standards in this case?  There are two
   answers to this question.  First, the obvious concern is that XML is
   not known for efficiency of data transport.  Being based in text, an
   IPv4 address is expanded from one octet to three octets, plus either
   an attribute and quotes or element tags and end tags.  Let us presume
   for the moment a very simple schema that might cause a record to be
   represented as follows:


       <r e="10.1.1.0" m="24">
         <l w="10" p="15">
           <v4>
           192.168.1.1
           </v4>
        </l>
         <l w="5" p="15">
           <v4>
           192.168.1.2
           </v4>
        </l>
      </r>


   With white space removed the uncompressed XML represents 120 bytes
   versus 20 bytes for the record specified in Section 3.1, representing
   a five fold expansion.  That brings our 920MB database to 4.6GB.

   The other concern about XML is that version 1.0 of the specification
   is silent on the order of sibling elements.  Specifications other
   than the base specification state that order is significant.  Order
   is significant to LISP and NERD because once an update is applied to
   the database it should be possible to verify the signature of the
   entire database.  Prior to applying the signature the XML generator
   would need to ensure the order of information.  That same sort would
   be required of the router.  This seems to add unnecessary fragility
   to a critical system without much benefit.  While there may indeed be
   uses of an XML representation of the database, these uses are likely
   to be outside of a router.


7.  Other Distribution Mechanisms

   We now consider various different mechanisms.  The problem of
   distributing changes in various databases is as old as databases.
   The author is aware of two obvious approaches that have been well
   used in the past.  One approach would be the wide distribution of CVS
   repositories.  However, for reasons mentioned in the previous



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   section, CVS is insufficient to the task.

   The other tried and true approach is the use of periodic updates in
   the form of messages.  Good old NNTP [13] itself provides two
   separate mechanisms (one push and another pull) to provide a coherent
   update process.  This was in fact used to update molecular biology
   databases [14] in the early 1990s.  Netnews offers a way to determine
   whether articles with specified Article-Ids have been received.  In
   the case where the mapping file source of authority wishes to
   transmit updates, it can sign a change file and then post it into the
   network.  Routers merely need to keep a record of article ids that it
   has received.  Initially this is probably overkill, but it may not be
   so later in this process.  Some consideration should be given to a
   mechanism known to widely distribute vast amounts of data, as
   instantaneously either the sender or the receiver wishes.

   To attain an additional level of hierarchy in the distribution
   network, service providers could retrieve information to their own
   local servers, and configure their routers with the host portion of
   the above URI.

   Another possibility would be for providers to establish an agreement
   on a small set of anycast addresses for use for this purpose.  There
   are limitations to the use of anycast, particularly with TCP.  In the
   midst of a routing flap anycast address can become all but unusable.
   Careful study of such a use as well as appropriate use of HTTP
   redirects is expected.

7.1.  What About DNS as a retrieval model?

   It has been proposed that a query/response mechanism be used for this
   information, and that specifically the domain name system (DNS) [16]
   be used.  The previous models do not preclude the DNS.  DNS has the
   advantage that the administrative lines are well drawn, and that the
   ID/RLOC mapping is likely to appear very close to these boundaries.
   DNS also has the added benefit that an entire distribution
   infrastructure already exists.  There are, however, some problems
   that could impact end hosts when intermediate routers make queries,
   some of which were first pointed out in [15]:

   o  Any query mechanism offers an opportunity for a resource attack if
      an attacker can force the ITR to query for information.  In this
      case, all that would be necessary would be for a "botnet" (a group
      of computers that have been compromised and used as vehicles to
      attack others) to ping or otherwise contact via some normal
      service hosts that sit behind the ETR.  If the botnet hosts
      themselves are behind ETRs, the victim's ITR will need to query
      for each and every one of them, thus becoming part of a classic



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      reflector attack.
   o  Packets will be delayed at the very least, and probably dropped in
      the process of a mapping query.  This could be at the beginning of
      a communication, but it will be impossible for a router to
      conclude with certainty that this is the case.
   o  The DNS has a backoff algorithm that presumes that applications
      are making queries prior to the beginning of a communication.
      This is appropriate for end hosts who know in fact when a
      communication begins.  An end user may not enjoy a router waiting
      seconds for a retry.
   o  While the administrative lines may appear to be correct, the
      location of name servers may not be.  If name servers sit within
      PI address space, thus requiring LISP to reach, a circular
      dependency is created.  This is precisely where many enterprise
      name servers sit.  The LISP experiment should not predicate its
      success on relocation of such name servers.

   Never-the-less, DNS may be able to play a role in providing the
   enterprise control over the mapping of its EIDs to RLOCs.  Posit a
   new DNS record "EID2RLOC".  This record is used by the authority to
   collect and aggregate mapping information so that it may be
   distributed through one of the other mechanisms.  As an example:

      $ORIGIN 0.10.PI-SPACE.
       128   EID2RLOC   mask 23 priority 10 weight 5 172.16.5.60
             EID2RLOC   mask 23 priority 15 weight 5 192.168.1.5


   In the above figure network 10.0.128/23 would delegated to some end
   system, say EXAMPLE.COM.  They would manage the above zone
   information.  This would allow a DNS mechanism to work, but it would
   also allow someone to aggregate the information and distribution a
   table.

7.1.1.  Perhaps use a hybrid model?

   It would be possible to use both a prepopulated database such as NERD
   and query mechanism (perhaps DNS) to determine an EID/RLOC mapping.
   The general idea would be to receive a subset of the mappings, say,
   by taking only the NERD for certain regions.  This alleviates the
   need to drop packets for some subset of destinations under the
   assumption that one's business is localized to a particular region.
   If one did not have a local entry for a particular EID one would then
   make a query.

   One improvement on simply using DNS to query live would be to
   periodically walk the entire network, in search of EID2RLOC records,
   and caching them to non-volatile storage.  This has two benefits.



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   First, it prevents resource attacks.  Care has to be given to how
   memory is cached it avoid an attacker causing a performance
   degradation by attempting to exceed memory limits through a random
   source attack.

   As important as resisting attacks, having a complete or near complete
   copy of the database provides for a faster recovery time when a
   router goes out of service, for whatever reason.  Absent such a
   mechanism, devices would need to repopulate their local caches
   through the help of another system, leading to additional system
   fragility.

7.2.  Use of BGP

   Border Gateway Protocol (BGP) [9] is currently used to distribute
   inter-domain routing throughout the Internet.  Why not, then, use BGP
   to distribute the mapping table?  A simple answer is that the objects
   BGP best handles are routes.  While it may be possible to transmit
   EID/RLOC mappings instead (because they look an awful lot like
   routes) the rate of updates of EID/RLOC mappings is specifically
   intended to be considerably less than routes, and would probably
   require additional dampening mechanisms to ensure that this is so.

   In addition, the ownership of the mapping does not flow from service
   providers but rather from end users of the identifiers.  It should
   not be possible for anyone to filter the mapping, other than perhaps
   ITRs for local policy purposes.  The current limited security model
   for BGP does not fit the general requirements of how the mapping is
   to be processed.

   Furthermore, as BGP is currently the lifeblood of the Internet its
   use for any means other than routing should be strongly scrutinized.

   This is not to say that BGP has no role to play whatsoever.  It may
   well be possible for routers to exchange database version numbers and
   perhaps base distribution URIs as extensions or capabilities.  This
   would allow routers to serve their copy of the database to their
   neighbors, easing the load off the rest of the server infrastructure.
   How this would be done is future work.


8.  Deployment Issues

   While LISP and NERD are intended as experiments at this point, it is
   already obvious one must give serious consideration to circular
   dependencies with regard to the protocols used and the elements
   within them.




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8.1.  HTTP

   In Section 7.1 we have already seen how DNS can have circular
   dependencies.  In as much as HTTP depends on DNS, either due to the
   authority section of a URI, or due to the configured base
   distribution URI, these same concerns apply.  In addition, any HTTP
   server that itself makes use of provider independent addresses would
   be a poor choice to distribute the database for these exact same
   reasons.

   One issue with using HTTP is that it is possible that a middlebox of
   some form, such as a cache, may intercept and process requests.  In
   some cases this might be a good thing.  For instance, if a cache
   correctly returns a database, some amount of bandwidth is conserved.
   On the other hand, if the cache itself fails to function properly for
   whatever reason, end to end connectivity could be impaired.  For
   example, if the cache itself depended on the mapping being in place
   and functional, a cold start scenario might leave the cache
   functioning improperly, in turn providing routers no means to update
   their databases.  Some care must be given to avoid such
   circumstances.


9.  Conclusions

   This memo has specified a database format, an update format, a URI
   convention, an update method, and a validation method for EID/RLOC
   mappings.  We have shown that beyond the predictions of 10^7
   locators, the aggregate database size would be at most 10.8GB.  We
   have considered the amount of servers to distribute that information
   and we have demonstrated the limitations of a simple content
   distribution network and other well known mechanisms.  The effort
   required to retrieve a database change amounts to between 2 and 20
   seconds of processing time per hour at at today's gigabit speeds.  We
   conclude that there is no need for an off box query mechanism today,
   and that there are distinct disadvantages for having such a mechanism
   in the control plane.

   Beyond this we have examined alternatives that allow for hybrid
   models that do use query mechanisms, should our operating assumptions
   prove overly optimistic.  Use of NERD today does not forclose use of
   such models in the future, and in fact both models can happily co-
   exist.

   We leave to future work how the list of databases is distributed, how
   BGP can play a role in distributing knowledge of the databases, and
   how DNS can play a role in aggregating information into these
   databases.



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   We also leave to future work whether HTTP is the best protocol for
   the job, and whether the scheme described in this document is the
   most efficient.  One could easily envision that when applied in high
   delay or high loss environments, a broadcast or multicast method may
   prove more effective.


10.  IANA Considerations

   This memo makes no requests of IANA.


11.  Acknowledgments

   Dino Farinacci, Patrik Faltstrom, Dave Meyer, Joel Halpern, Dave
   Thaler, Mohamed Boucadair, and Max Pritikin were very helpful with
   their reviews of this document.  The astute will notice a lengthy
   References section.  This work stands on the shoulders of many
   others' efforts.


12.  References

12.1.  Normative References

   [1]   Farinacci, D., "Locator/ID Separation Protocol (LISP)",
         draft-farinacci-lisp-03 (work in progress), August 2007.

   [2]   Fielding, R., Gettys, J., Mogul, J., Frystyk, H., Masinter, L.,
         Leach, P., and T. Berners-Lee, "Hypertext Transfer Protocol --
         HTTP/1.1", RFC 2616, June 1999.

   [3]   Bradner, S., "Key words for use in RFCs to Indicate Requirement
         Levels", BCP 14, RFC 2119, March 1997.

   [4]   Kaliski, B., "PKCS #7: Cryptographic Message Syntax Version
         1.5", RFC 2315, March 1998.

   [5]   International Telecommunications Union, "Information technology
         - Open Systems Interconnection - The Directory: Public-key and
         attribute certificate frameworks", ITU-T Recommendation X.509,
         ISO Standard 9594-8, March 2000.

   [6]   Berners-Lee, T., Fielding, R., and L. Masinter, "Uniform
         Resource Identifier (URI): Generic Syntax", STD 66, RFC 3986,
         January 2005.

   [7]   Moats, R., "URN Syntax", RFC 2141, May 1997.



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12.2.  Informational References

   [8]   Dierks, T. and E. Rescorla, "The Transport Layer Security (TLS)
         Protocol Version 1.1", RFC 4346, April 2006.

   [9]   Rekhter, Y., Li, T., and S. Hares, "A Border Gateway Protocol 4
         (BGP-4)", RFC 4271, January 2006.

   [10]  Carpenter, B., "IETF Plenary Presentation: Routing and
         Addressing: Where we are today", March 2007.

   [11]  Grune, R., Baalbergen, E., Waage, M., Berliner, B., and J.
         Polk, "CVS: Concurrent Versions System", November 1985.

   [12]  International International Telephone and Telegraph
         Consultative Committee, "Information Technology - Open Systems
         Interconnection - The Directory: Authentication Framework",
         CCITT Recommendation X.509, November 1988.

   [13]  Kantor, B. and P. Lapsley, "Network News Transfer Protocol",
         RFC 977, February 1986.

   [14]  Smith, R., Gottesman, Y., Hobbs, B., Lear, E., Kristofferson,
         D., Benton, D., and P. Smith, "A mechanism for maintaining an
         up-to-date GenBank database via Usenet", CABIOS , April 1991.

   [15]  Huitema, C., "An Experiment in DNS Based IP Routing", RFC 1383,
         December 1992.

   [16]  Mockapetris, P., "Domain names - concepts and facilities",
         STD 13, RFC 1034, November 1987.

   [17]  Bray, T., Paoli, J., Sperberg-McQueen, C., and E. Maler,
         "Extensible Markup Language (XML) 1.0 (2nd ed)", W3C REC-xml,
         October 2000, <http://www.w3.org/TR/REC-xml>.

   [18]  Gudgin, M., Hadley, M., Mendelsohn, N., Moreau, J., and H.
         Nielsen, "SOAP Version 1.2 Part 1: Messaging Framework", W3C
         Working Draft soap12-part1, June 2002,
         <http://www.w3.org/TR/soap12-part1>.

   [19]  Gudgin, M., Hadley, M., Mendelsohn, N., Moreau, J., and H.
         Nielsen, "SOAP Version 1.2 Part 2: Adjuncts", W3C Working
         Draft soap12-part2, June 2002,
         <http://www.w3.org/TR/soap12-part2>.

URIs




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   [20]  <http://www.openssl.org>


Appendix A.  Generating and verifying the database signature with
             OpenSSL

   As previously mentioned, one goal of NERD was to use off-the-shelf
   tools to both generate and retrieve the database.  To many, PKI is
   magic.  This section is meant to provide at least some clarification
   as to both the generation and verification process, complete with
   command line examples.  Not included is how you get the entries
   themselves.  We'll assume they exist, and that you're just trying to
   sign the database.

   To sign the database, to start with, you need a database file that
   has a database header described in Section 3.  Block size should be
   zero, and there should be no PKCS#7 block at this point.  You also
   need a certificate and its private key with which you will sign the
   database.

   The OpenSSL "smime" command contains all the functions we need from
   this point forth.  To sign the database, issue the following command:


         openssl smime -binary -sign -outform DER -signer yourcert.crt \
                 -inkey yourcert.key -in database-file -out signature



   -binary states that no MIME canonicalization should be performed.
   -sign indicates that you are signing the file that was given as the
   argument to -in.  The output format (-outform) is binary DER, and
   your public certificate is provided with -signer along with your key
   with -inkey.  The signature itself is specified with -out.

   The resulting file "signature" is then copied into to PKCS#7 block in
   the database header, its size in bytes is recorded in the PKCS#7
   block size field, and the resulting file is ready for distribution to
   ITRs.

   To verify a database file, first retrieve the PKCS#7 block from the
   file by copying the appropriate number of bytes into another file,
   say "signature".  Then zero this field, and set the block size field
   to 0.  Next use the "smime" command to verify the signature as
   follows:


       openssl smime -binary -verify -inform DER -content database-file



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               -out /dev/null -in signature



   Openssl will return "Verification OK" if the signature is correct.

   To improve verification performance it would make modifications to
   the program so that it takes as input the database with a null
   signature and as an argument the name of the file containing the
   signature.  Better yet, use a call to the appropriate library with
   each block.


Appendix B.  Changes

   This section to be removed prior to publication.

   o  02: Incorporate some of Dave Thaler's comments.  Add
      authentication block detail.  Modify analysis to take IPv6 into
      account, along with a more realistic number of RLOCs per EID.  Add
      some comments about potential risks of a cold start.  Add S/MIME
      example as appendix A and take out old ToDo.  Provide some amount
      of compression of IPv6 addresses by limiting their size to
      significant bytes rounded to a four byte word boundary.
   o  01: Massive spelling correction, URI example correction.
   o  00: Initial Revision.



Appendix C.  Open Questions

   This section to be removed prior to publication.

   o  Should the database contain its name?  It is probably sufficient
      to merely reference the database by name.
   o  Should the signature portion be separated from the actual
      database?  By specifying the signature we hope to reduce
      interoperability issues and encourage proper security from the get
      go.  On the other hand, since the object is opaque it is not clear
      how much interoperability we are actually encouraging.
   o  Should we specify a (perhaps compressed) tarball that treads a
      middle ground for the last question, where each update tarball
      contains both a signature for the update and for the entire
      database, once the update is applied.
   o  Should we compress?  In some initial testing of databases with 1,
      5, and 10 million IPv4 EIDs and a random distribution of IPv4
      RLOCs, the current format in this document compresses down by a
      factor of between 35% and 36%, using Burrows-Wheeler block sorting



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      text compression algorithm (bzip2).  The NERD used random EIDs
      with mask lengths varying from 19-29, with probability weighted
      toward the smaller masks.  This only very roughly reflects
      reality.  A better test would be to start with the existing
      prefixes found in the DFZ.


Author's Address

   Eliot Lear
   Cisco Systems GmbH
   Glatt-com
   Glattzentrum, ZH  CH-8301
   Switzerland

   Phone: +41 1 878 7525
   Email: lear@cisco.com


































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