Internet DRAFT - draft-trossen-rtgwg-impact-of-dlts

draft-trossen-rtgwg-impact-of-dlts







Network Working Group                                         D. Trossen
Internet-Draft                                       Huawei Technologies
Intended status: Informational                                 D. Guzman
Expires: 12 August 2024                      Technical University Munich
                                                              M. McBride
                                                               FutureWei
                                                                  X. Fan
                                                                   IoTeX
                                                         9 February 2024


                  Impact of DLTs on Provider Networks
                 draft-trossen-rtgwg-impact-of-dlts-03

Abstract

   This document discusses the impact of distributed ledger technologies
   being realized over IP-based provider networks.  The focus here lies
   on the impact that the DLT communication patterns have on efficiency
   of resource usage in the underlying networks.  We provide initial
   insights into experimental results to quantify this impact in terms
   of inefficient and wasted communication, aligned along challenges
   that the DLT realization over IP networks faces.

   This document intends to outline this impact but also opportunities
   for network innovations to improve on the identified impact as well
   as the overall service quality.  While this document does not promote
   specific solutions that capture those opportunities, it invites the
   wider community working on DLT and network solutions alike to
   contribute to the insights in this document to aid future research
   and development into possible solution concepts and technologies.

   The findings presented here have first been reported within the
   similarly titled whitepaper released by the Industry IoT Consortium
   (IIC) [IIC_whitepaper].

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.






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   Internet-Drafts are draft documents valid for a maximum of six months
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   This Internet-Draft will expire on 12 August 2024.

Copyright Notice

   Copyright (c) 2024 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Main DLT Concepts . . . . . . . . . . . . . . . . . . . . . .   5
   4.  Communication in a DLT  . . . . . . . . . . . . . . . . . . .   6
     4.1.  DLT Interactions  . . . . . . . . . . . . . . . . . . . .   6
     4.2.  Resulting Communication Patterns  . . . . . . . . . . . .   8
   5.  Challenges for Users and Provider Networks  . . . . . . . . .   9
   6.  Experimental Insights . . . . . . . . . . . . . . . . . . . .  10
     6.1.  Types of DLT Peers  . . . . . . . . . . . . . . . . . . .  11
     6.2.  Communication Waste . . . . . . . . . . . . . . . . . . .  11
   7.  Opportunities for Network Innovations . . . . . . . . . . . .  12
   8.  Relation to IETF/IRTF and IEEE SA Efforts . . . . . . . . . .  14
   9.  Open Questions  . . . . . . . . . . . . . . . . . . . . . . .  15
   10. Next Steps  . . . . . . . . . . . . . . . . . . . . . . . . .  15
   11. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . .  16
   12. Security Considerations . . . . . . . . . . . . . . . . . . .  16
   13. Privacy Considerations  . . . . . . . . . . . . . . . . . . .  16
   14. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  16
   15. Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  17
   16. Informative References  . . . . . . . . . . . . . . . . . . .  17
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  19







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1.  Introduction

   The current routing system was initially designed for a single
   purpose, namely reachability between end nodes.  This capability is
   utilized in many higher layer technologies in the form of overlays.
   Distributed Ledger Technologies (DLT) are one such form of overlay
   with the aim to facilitate communication patterns that allow a
   distributed consensus among distributed, and generally unknown,
   participants in the DLT overlay.

   The realization of a DLT overlay follows that of other well-known
   examples for distributed computing tasks, such as Torrents,
   distributed file storage, among others.  That is, DLTs form their own
   overlay through contributing 'peers' that partake in the DLT.  For
   this, reachability information (in the form of IP addresses) of other
   DLT peers is centrally maintained (in so-called 'bootstrap nodes') to
   establish peer-specific pools of peers, within which each peer in
   turn communicates for the specific purpose of the DLT.  DLTs secure
   the transactions using transport-level methods.  As an overlay, DLTs
   are little concerned with the underlying network(s) itself, simply
   utilizing the provided IP reachability service for their purpose.

   Continuing on the insights first reported in [IIC_whitepaper], this
   document sheds light onto the realization of specific DLT overlay
   mechanisms from the perspective of the resulting impact on the
   utilized provider networks in the form of the actual communication
   taking place.

   For this, we outline the communication patterns upon which certain
   forms of DLTs rely (Section 4.2) in order to implement the key DLT
   concepts (Section 3).  Based on our insights of those communication
   patterns, we then identify a number of key challenges (Section 5)
   through initial experimental results (Section 6) within an example
   DLT platform (here, Ethereum [REF]).

   Here, we explicitly recognize that those insights are highly
   dependent on the specific DLT mechanisms under investigation and are
   therefore not generally transferable to other DLT platforms and their
   realization.  For instance, DLT platforms relying on proof-of-work
   for transaction verification tend to differ in their communication
   from those relying on proof-of-stake.  However, this document does
   attempt to develop a wider methodology over time that may allow for
   quantifying the impact on underlying networks across those different
   types of DLTs.

   While the quantification of DLT impact serves as an interesting
   benchmark into the possible costs for operating DLTs, the identified
   challenges give also rise to possible opportunities for network-level



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   innovations to improve on the situation observed in our experiments,
   thereby reducing the identified impact on provider network.
   Section 7 outlines a possible realization of those opportunities
   through a constraint-based selection of communication relations,
   utilizing semantic information beyond IP reachability.

   With this in mind, we position an improved DLT performance as a
   possible applicability for semantic routing, introduced in more
   detail in [I-D.farrel-irtf-introduction-to-semantic-routing], while
   also soliciting other possible realizations of an improved DLT
   performance through network-level innovations.  Moreover, we draw
   connections with ongoing IETF/IRTF efforts (Section 8), where our
   insights may provide useful input.

   Note: This document does neither discuss the particular rationale for
   selecting DLTs in order to realize the intended application purpose
   nor the specific DLT mechanisms eventually used.  It therefore does
   not pass comment on the advisability or practicality of using DLTs
   and their solutions, nor does it define any specific technical
   solutions for reducing the observed provider impact.

2.  Terminology

   The following terminology is used throughout the remainder of this
   draft:

   Smart contract  : distributed state machine over which transactions
                  will be executed and logged.

   Transaction    : cryptographically signed (set of) instruction(s)
                  against a smart contract.

   Ledger         : information on transactions

   Block          : set of verified ledger information

   Blockchain     : concatenated blocks with longest chain of blocks
                  representing the current consensus of ledger
                  information.

   Peer           : participant in the DLT, with a possible narrower
                  role of client or miner.

   Client         : a DLT peer issuing transactions towards a set of
                  miners.

   Miner          : a DLT peer receiving transactions from miners and




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                  performing suitable block operations and exchanges to
                  maintain DLT information.

3.  Main DLT Concepts

   There has been ample work, such as [DLT_intro] [DLT_intro2], among
   others, including in other SDOs such as the IEEE but also within the
   IRTF/IETF [DINRGref], on defining main DLT concepts; we refer the
   reader to those references for more details.  We focus our brief
   introduction here on those concepts most important to understand from
   a communication perspective.

   The core abstraction used in a DLT is that of a 'transaction', i.e.,
   a cryptographically signed (set of) instruction(s) to modify a state
   machine, which in turn represents the distributed consensus the DLT
   is trying to maintain.  These transactions are executed within the
   higher-level concept of a 'smart contract', which implements the
   specific DLT application, such as for cryptocurrency, storage
   management, decentralized governance, among others.

   Valid transactions are maintained in a distributed 'ledger' in the
   form of hashed information referred to as 'blocks'.  Consensus is
   represented through the longest available chain of blocks that can be
   obtained from another DLT peer.

   The validation of transactions, and therefore the inclusion into the
   (distributed) ledger, is realized through the consensus layer,
   realizing computational operations, such as Proof-of-Work, Proof-of-
   Stake, and others.  There has been much discussion on the
   implications of those computational aspects, e.g., on energy
   consumption, which is not the focus of this draft.

   Figure 1 provides an overview of a typical layering within a DLT
   architecture.  The focus of this draft is on the layers below the
   session, i.e. the communication that needs to be upheld in order to
   facilitate transactions and block exchange within the DLT system.















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+------------++---------------------------------------------------------+
| Application||   User    |  DLT   |   DLT    |     DLT   |Decentralized|
|   Layer    || Interface | Wallet | Explorer | Analytics |  Finance    |
+------------++---------------------------------------------------------+
|App Protocol||  Identity | Token  |  Storage |    DLT    |Decentralized|
|   Layer    ||    Mgmt   |  Mgmt  |   Mgmt   |   Oracle  |  Governance |
+------------++-----------------------------+---------------------------+
|  Contract  ||         Transaction         |           Smart           |
|   Layer    ||           Engine            |         Contract          |
+------------++-----------------------------+---------------------------+
|  Consensus ||                 PoW/PoS/DPoS/PBFT/Raft/etc.             |
|   Layer    ||                                                         |
+------------++-------------------+------------------+------------------+
|  Session   ||    Transaction    |      Block       |      Account     |
|   Layer    ||                   |                  |                  |
+------------++-------------------+------------------+------------------+
|  Transport ||        TCP        |       QUIC       |       UDP        |
|   Layer    ||      (+TLS)       |                  |                  |
+------------++-------------------+------------------+------------------+
|  Network   ||    (DNS + ) IP    |     Service      |     Pub/sub      |
|   Layer    ||                   |     Routing      |     overlay      |
+------------++-------------------+------------------+------------------+
|  Resource  ||       CPU         |     Storage      |    Transport     |
|   Layer    ||                   |                  |     Network      |
+------------++-------------------+------------------+------------------+


        Figure 1: DLT Conceptual Architecture [IIC_whitepaper]

4.  Communication in a DLT

   With our focus on the communication impact of DLTs, we now tease
   apart the communication as it usually takes place in a DLT in order
   to realize the transactions within a distributed ledger and the
   maintenance of the latter.  We first outline the interactions at a
   higher level before delving into the communication patterns that
   result from those.

   As stated in the introduction, these insights are currently limited
   to those obtained from Ethereum, a proof-of-work based DLT platform.
   Future draft revisions will enrich this section with any differing
   insights from other DLT realizations and platforms.

4.1.  DLT Interactions

   We can distinguish three core interactions in a DLT:





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   1.  A client commits a transaction to the DLT.  The transaction
       request is being diffused across a set of DLT miners, which
       respond to the transaction request separately and add the
       transaction to their internal ledger information.  The commit of
       the transaction leads to the miners committing compute and
       storage resources in relation to the smart contract that
       underlies the transaction.  For this, so-called 'proofs' will be
       executed as part of the computational part of the DLT, although
       some methods for proof require additional communication to take
       place, e.g., election protocols.

   2.  The result of the aforementioned proof is a 'block' (of ledger
       information) that the miners in turn commit to a set of (other)
       DLT miners, which each receiving miner adds to their internal
       blockchain.

   3.  A client may query the latest blockchain, again from a set of
       miners to which the query is being sent.  The longest returned
       blockchain represents the most trustworthy ledger information
       available.

   We can see from those interactions above that communication in a DLT
   is multipoint in nature, i.e., transactions or information (such as
   blocks) are sent to a set of DLT peers, not just a single one.

   Important here is that the set of DLT peers is a randomized sample
   from a larger pool of available DLT peers; this is to achieve
   diffusion among many DLT peers, avoiding repeated communication with
   a fixed set of DLT peers and thereby reducing the threat of collusion
   of information through a malicious set of DLT peers.

   The consequence of that varying random nature of the multipoint
   diffusion, however, is that repeated unicast replication is utilized
   instead of efficient network-level multicast; this constitutes a
   first recognizable impact on provider networks.

   In the following subsection, we now focus on the communication
   patterns that are utilized to achieve the aforementioned interaction.
   Special attention is here given to the establishment of the pool of
   DLT peers that is used in the multipoint operations that are executed
   for each interaction, be it a transaction or the commitment of a
   newfound (ledger) block.









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4.2.  Resulting Communication Patterns

   As mentioned before, it is key for any DLT peer, be it a client or a
   miner, to establish and maintain a 'pool of peers' from which it can
   select a set of DLT peers for each intended interaction.  Figure 2
   outlines those steps, detailed in the following.  Our insights on
   realization were obtained from an Ethereum based experiment, using
   the go-ethereum release V1.10.2-stable on a Linux-based machine,
   operating out of Munich, Germany.

   1.  The first phase is that of a 'peer discovery'.  For this, an
       initial list of DLT peer information is obtained from a
       'bootstrap node', of which only few exist in the DLT, holding the
       IP address and port information of each DLT peer that has signed
       up to the DLT overlay (other information may include DLT-specific
       information, such as an overlay ID or similar).

   2.  This initial list of DLT peers is now contacted through a (UDP-
       level) PING/PONG sequence, thereby discovering those DLT peers
       that are reachable for the DLT interactions.

   3.  A successful discovery of the DLT peer is now followed with the
       establishment of suitable transport security.  Once successfully
       secured, the discovered DLT peer is being added to the 'DLT pool'
       list at the initiating DLT peer.

   4.  Once security is established, capabilities are exchanged that
       ensure that the discovered peer can successfully complete
       possible requests.  Those capabilities may include HW
       capabilities (e.g., GPU usage, certain memory build-out), SW
       capabilities (use of certain hash functions, blockchain
       checkpoint) and others.

   5.  The initiating DLT peer repeats now the previous steps 1 through
       4 until the pool size reaches a defined limit.  Unlike contacting
       the bootstrap nodes, however, the newly and successfully
       discovered DLT peers in the previous round are contacted instead
       for obtaining a list of DLT peers.

   6.  Any member of the DLT pool is continuously checked for
       connectivity through frequent (e.g., TCP-based) HELLO messages.
       Any failed HELLO transaction leads to removing the DLT peer from
       the pool and obtaining another DLT peer as replacement.

   The final size of the pool is a matter of local configuration (in our
   case about 28k DLT peers, significantly less than the size of the
   overall DLT network, which was about 500k at the time of the
   experiment).



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   Also, a DLT client may commence with transactions (to the DLT
   overlay) already while the pool creation is still ongoing, thereby
   progressing to the last step in Figure 2 once a suitable set of DLT
   peers can be obtained from the overall (and possibly still growing)
   local pool of peers.


+-------------------+                                  if DLT peer connection failed
|    Obtain list    |<--------------------------------------+
|   of DLT peers    |<--+                                   |
+-------------------+   | if pool size       +--------------+---
|       Node        |   | smaller than max   |  Maintain peer  |
|      discovery    |   |                    |  connectivity   |
+-------------------+   |                    +-----------------+
|     Transport     |   |
|      security     |   |
+-------------------+   |
|    Capability     +---+
|     exchange      |
+-------------------+
          |
          |   add discovered peers to pool of DLT peers
         \|/
+--------------------------------+
|     Obtain set of DLT peers    |
|     from pool of DLT peers     |
+--------------------------------+
|         Transactions           |
+--------------------------------+


              Figure 2: Steps of Communications in a DLT

5.  Challenges for Users and Provider Networks

   Considering the observed communication patterns in the previous
   section, we can identify a number of challenges that need addressing:

   1.  Reachability information is required to interact with other
       peers.  For that, bootstrap nodes maintain IP addresses of all
       peers (plus port information).  As illustrated in Figure 2, new
       DLT peers need to download and expand suitable reachability
       information upon joining, either from bootstrap node or via
       discovered nodes - see Figure 2, , requiring each DLT peer to
       maintain a pool of peer as active connections.






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   2.  Clients know nothing about capabilities of peers to serve
       requests.  In other words, the discovery in Figure 2 merely
       ensures possible reachability but not necessarily successful
       communication.  As a consequence, the resulting approach,
       illustrated in Figure 2, is to (1) contact potential peer, (2)
       wait for connection, (3) inquire capabilities, (4) disconnect if
       not matching.  Here, peers may never reply to connection
       establishment (step 2), usually resulting in additional latency
       due to timeouts involved, prolonging therefore the establishment
       of the pool of peers to communicate with.  Such capabilities
       often reflect the continuous evolution of business models over
       DLT networks and may be dynamic in nature.  For example, the
       minimum transaction fee may depend on the 'DLT gas price', which
       is set up at the transaction recipient (miner).

   3.  Peers map sending of transactions onto unicast communication,
       which negatively impacts efficiency (bandwidth usage) and
       transaction completion time.  Here, the use of group-based
       multicast approaches is difficult due to the random nature of the
       set of peers selected for communication in every request
       exchange, aiming at the diffusion of requests rather than
       interacting with a stable (but possibly colluding) set of peers.

   4.  DLT peers need to expose their IP address to the DLT system,
       replicated to the bootstrap nodes, but also other DLT peers by
       virtue of the discovery process outlined in Figure 2.  This may
       lead to privacy and/or security issues in the form of geo-
       identifying specific peers, DoS attacks on particular parts of
       the DLT and others.

6.  Experimental Insights

   To shed some more light onto the possible impact on provider
   networks, stemming from some of the challenges in Section 5, we
   conducted experiments, using the same setup described in Section 4.2.
   More details (and suitable graphical representations of our initial
   results can be found in [IIC_whitepaper]).

   Here, the goal was to undergo the steps needed to build up the needed
   pool of DLT peers, after which we sought to synchronize to determine
   the longest blockchain available in the discovered pool.  The
   resulting geographic spread of the discovered DLT peers included all
   continents albeit with an expected clustering of nodes North America,
   Europe, Asia, and Australia, with only few discovered in South
   America and Africa.






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6.1.  Types of DLT Peers

   Our first target was to differentiate types of DLT peers that stem
   from the communication patterns in Figure 2.  Specifically, we came
   to differentiate the following types of DLT peers:

   1.  Non routable peers: This type include all those peers that never
       positively responded to step 1 of the discovery, i.e. the PING/
       PONG to determine reachability.  Reasons here may include to be
       located behind a firewall, being intermittently available (and
       switched off during the connection attempt), or simply having
       left the DLT while still remaining in the information pool
       maintained at the bootstrap nodes.

   2.  Signalling peers: This type includes peers that respond
       positively to reachability but do not positively succeed in the
       transport security or capability exchange steps (blockchain
       checkpoint).

   3.  Dropped data peers: This type of peers successfully complete all
       discovery steps, thereby end up in the pool of peers, but still
       do not provide suitable data upon request (here a valid
       blockchain information).  The reasons here could be unavailable
       information or not completing the transfer of information
       (blockchain information can be very large, several GBs, so that
       DLT peers may run out of available BW budget or decide to sever
       the connection because of switch-off or other reasons during the
       transfer).  While here communication in the DLT does take place,
       it is not successful in regards to the intended communication,
       therefore wasted.

   4.  Data peers: This final type of peers successfully completes all
       steps in Figure 2, i.e. not only the discovery but also the
       intended transfer of DLT-relevant data.

   In our experiments, we determined at about 18% of peers are of the
   last type, i.e. successfully contribute to DLT purposes, while about
   2% are of the third category, about 12% are non routable peers and
   about 68% are signalling peers.  In other words, almost 80% of all
   attempted discoveries fails either because of the lack of
   reachability or mismatching capabilities.

6.2.  Communication Waste

   Looking at the bandwidth usage across the different peer types allows
   for shedding some light on the communication that needs to be carried
   through the participating provider networks.




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   Given the amount of data for each blockchain synchronization, it is
   not surprising that, despite forming a mere 18% of peers, the 'data
   peers' account for about 58% of traffic in the overall system.  This
   is followed by the 'dropped data peers' with about 31.5% (since still
   much data is sent albeit unsuccessfully).  Both non routable and
   signalling peers account for a total of slightly under 10% of data
   used.

   Although the amount of data that is wasted here accounts for
   (significant) total of about 42%, the data-heavy operation of
   synchronization large amounts of (blockchain) data is mainly to blame
   for this; however, the synchronization has to happen for any DLT peer
   to start operating as a possible DLT miner, so is not avoidable.

7.  Opportunities for Network Innovations

   The challenges outlined in Section 5 lead us to outline possible
   opportunities for network innovations that may address those
   challenges and reduce the observed impact on provider networks.  We
   stress here that none of the suggested approaches constitute
   solutions for those opportunities but merely possible starting points
   beyond which further study is required:

   1.  Addressing model: With the DLT overlay being realized over an IP
       network, each DLT peer is being addressed via its IP(v4/v6)
       address.  With the discovery step selecting a dedicated DLT peer
       (through its IP address), the discovery steps (see Figure 2)
       include dedicated steps to ensure the reachability of the
       specific DLT peer under discovery.  Until reachability can be
       ensured, traffic (in the form of PING/PONG messages) and latency
       (through sending those messages, while needing to wait for a
       timeout in case the DLT peer is not routable) need to occur,
       despite the DLT peer not being eventually used for communication.

       *  Approaches such as those in
          [SOI][SarNet2021][IFIPNetworking2022] may allow for DLT peers
          to advertise their capability to serve as a miner by using
          'service announcements' that expose the capability to serve
          transaction requests, which each announced DLT peer
          representing a service instance of the announced mining
          service.  Such native L3 (or L3.5) level service routing
          capability would therefore remove any of the discovery steps
          and the maintenance of the dedicated DLT overlay
          infrastructure.  Furthermore, it would remove any visibility
          of individual DLT peers' reachability information from other
          miners, until directly communicating with a specific DLT peer
          (for which the peer's IP address may be used, as suggested in
          [SarNet2021][IFIPNetworking2022]).  Last but not least, being



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          able to send a request without previously forming a pool of
          DLT peers (which is smaller than the number of all DLT peers
          in the overlay) also increases the possible number of DLT
          peers to communicate with rather than being limited to the
          peer-specific pool.

   2.  Constraint-based peer selection: Following on the aspect of
       relying purely on reachability information in the form of IP
       addresses, the discovery steps in Figure 2 further include a
       number of capability-dependent selection criteria to finally
       include a DLT peer in its pool of peers.  Specifically, the
       security and capability exchange may lead to a disconnect from a
       successfully contacted DLT because of such exchange leading to
       mismatching capabilities.  Furthermore, even after an initial
       capability exchange being successful, the actual transaction
       itself may be constrained by capabilities such as available
       resources (e.g., bandwidth or CPU), leading to unsuccessful
       communication, which in turn will need to be compensated with
       including another DLT peer into the diffusion request.

       *  Approaches such as [SarNet2021][IFIPNetworking2022] may allow
          to constrain the forwarding to one of possible many DLT peers.
          Hence, the capabilities used in the current DLT steps Figure 2
          could be encoded as suitable constraints for such selection,
          the constraints itself being advertised as part of the service
          announcement (see above).  As a result, the request will be
          forwarded to those destinations only which have previously
          announced constraints that match those of the request, thereby
          ensuring the successful completion of the request - further
          study is needed for those situations in which constraints may
          change frequently, thereby leading to successful matching, yet
          still unsuccessful request completion.

   3.  Diffusion multicast: The multipoint replication of the
       transaction request to a set of DLT peers, chosen from the larger
       DLT pool maintained at the initiating DLT peer, increases the
       overall system but, in particular, individual client bandwidth
       usage, which in turn impacts the provider network by needing to
       provide the necessary resources for the replicated sending.

       *  Approaches such as those in
          [SOI][SarNet2021][IFIPNetworking2022] may allow for sending a
          service request to a given number of DLT peers, where the
          replication is part of the constraint-based forwarding
          decision, thereby optimizing the packet delivery through in-
          network instead of endpoint-based replication.  The challenge
          here lies in preserving the diffusion character of the
          multipoint operation.  In other words, the set of DLT peers



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          used for the transactions changes for each request with a
          randomization that attempts to prevent possible collusion
          through DLT peers.  With that, typical group-based methods,
          most notably IP multicast, do not suffice.

8.  Relation to IETF/IRTF and IEEE SA Efforts

   Both, DLTs as well as routing innovations, are subject to
   investigation in a number of related IETF and IRTF efforts.  For
   instance, the Decentralized Internet Infrastructure RG [DINRGref] has
   been studying various aspects of DLTs and blockchains.  Our findings
   in this draft may provide additional input into the work of this RG,
   while we would solicit feedback from this group of experts into the
   specific insights we have derived so far.

   There is no standard way of providing interoperability between DLT
   networks.  This results in difficulty of transferring or exchanging
   virtual assets from one DLT network to another.  An interoperability
   architecture is being proposed in the IETF
   [I-D.hardjono-blockchain-interop-arch] to permit two gateways,
   belonging to distinct DLT networks, to conduct a virtual asset
   transfer between them while ensuring the asset does not exist
   simultaneously on both networks.  The Open Digital Asset Protocol
   (ODAP) [I-D.hargreaves-odap] is a gateway-to-gateway protocol to
   perform a unidirectional transfer of a virtual asset.

   Blockchain technologies, and thereby DLTs, have also been proposed
   for use in network functions itself.  For instance, the work in
   [I-D.mcbride-rtgwg-bgp-blockchain] proposes to position BGP as DLT-
   managed transactions and thus, to utilize the power of a
   permissionless (DLT-based) management infrastructure to improve on
   resilience and trust into the operations performed within BGP, such
   as origin announcements and BGP updates.  Such proposition, however,
   opens the question on the exact nature of such infrastructure but
   also its impact in terms of incurred traffic, particularly when
   operating at scale.

   Furthermore, routing innovations under the label of 'semantic
   routing' have been the topic of recent work, see
   [I-D.farrel-irtf-introduction-to-semantic-routing] for an overview.
   With the examples of service routing as possible approaches to
   realize the opportunities outlined in the previous subsection, a
   stronger linkage to this activity should be considered.








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   While the DLT standardization efforts in IEEE SA mainly focus on the
   upper layers of the DLT architecture, the decentralized identity
   related standards (e.g., P2958 [P2958] and P3210 [P3210]) that are
   currently under development might be relevant for addressing specific
   challenges in the DLT network layer.

9.  Open Questions

   The work initially presented in [IIC_whitepaper] focused on the
   specific impact that DLT operations may have on provider networks,
   thereby turning the attention not to the specific applications of DLT
   but what their realization may mean to the underlying network
   operators.

   Although attempting from the onset to base our insights on actual
   experiments we conducted, we recognize that those insights are only
   the start to a possibly wider understanding beyond this initial work.

   We therefore solicit not only feedback on the specific findings
   presented in the previous sections, but also to specific questions
   that our work has led to:

   1.  Correctness of observed DLT behaviour: Is our observed behaviour
       correct or have we overlooked important aspects?

   2.  Depth of insights: Can we deepen our insights through more
       experiments, focus on different or more KPIs?

   3.  Transfer of insights: Our insights so far are based on the
       Ethereum DLT system.  How transferable are the observed patterns
       of communication onto other DLT systems that are in use?

   4.  Differences in DLT realizations: If the answer to the previous
       question leads to little transfer onto other DLT platform, can we
       distil those difference with the goal to develop a wider
       methodology to capture DLT behaviour?

   5.  Applicability of other network innovations: What other network
       innovations may address the specific impacts we identified in our
       study?  Which ones beyond the ones currently listed should be
       included?

10.  Next Steps

   As for the next steps for this draft, the authors seek to deepen the
   current insights through further conducted experiments, providing
   more insights on the disconnects experienced by the system and the
   costs for maintaining the pool of DLT peers.



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   Furthermore, the authors will more directly link to relevant network
   innovations, particularly in the service routing and instantaneous
   multicast domain, with the goal of providing estimates of improving
   on the operational costs of DLTs through such new network
   innovations.

11.  Conclusions

   This draft is a living document, originating from an initial study in
   the impact of DLTs on provider networks [IIC_whitepaper].

   As such, the authors solicit feedback from the wider DLT and network
   community to improve on the insights, transfer them onto more DLT
   systems, and shed light onto how possible network innovations could
   improve on the identified issues.

12.  Security Considerations

   This document does not introduce or modify any security mechanisms.
   The nature of DLTs is to provide a high level of transactional
   security through immutability of the data in blocks.  But 51% attacks
   are possible amongst miners particularly on smaller, private
   blockchains where legitimate miners could be prevented from
   completing blocks and new blocks could be created by illegitimate
   miners.  Smart contracts could become vulnerable if a function calls
   the wrong contract either intentionally or through human error.
   Transactional data meant to be private might be exposed.  DLT attacks
   most often involve accounts being hacked outside of the DLT domain.

13.  Privacy Considerations

   Since the IP addresses of DLT peers are exposed in the DLT system,
   the DLT network layer might be subject to privacy leakage.  This
   document does not introduce any mechanisms for protecting IP address
   privacy and the methods described in
   [I-D.ip-address-privacy-considerations] could be employed to enhance
   the privacy of DLT peers.

14.  IANA Considerations

   This draft does not request any IANA action.










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15.  Acknowledgements

   This draft acknowledges the work done in the IIC Industrial Digital
   Ledger focus group, leading to the whitepaper in [IIC_whitepaper].
   We would like to thank the co-authors of this whitepaper for their
   work, specifically David Guzman (Huawei Technologies), Abhijeet
   Kelkar (GEOOWN Consulting), Xinxin Fan (IoTex), Mike McBride
   (Futurewei Technologies), Lei Zhang (iExec), Ulrich Graf (Huawei
   Technologies) and Dirk Trossen (Huawei Technologies) but also Stephen
   Mellor (IIC staff) who oversaw the process of organizing the
   contributions.

16.  Informative References

   [DINRGref] "Decentralized Internet Infrastructure (dinrg)", WG DIN
              Research Group, <https://irtf.org/dinrg>.

   [DLT_intro]
              Antonopoulos, A. M., "Mastering Bitcoin, 2nd Edition",
              Book O'Reilly Media, Inc., 2017,
              <https://www.iiconsortium.org/pdf/2022-01-10-Impact-of-
              Distributed-Ledgers-on-Provider-Networks.pdf>.

   [DLT_intro2]
              Rauchs, M., Glidden, A., Gordon, B., Pieters, G.,
              Recanatini, M., Rostand, F., Vagneur, K., and B. Zhang,
              "Distributed Ledger Technology Systems: A Conceptual
              Framework", Report Cambridge Centre for Alternative
              Finance, 2017, <https://www.jbs.cam.ac.uk/wp-content/
              uploads/2020/08/2018-10-26-conceptualising-dlt-
              systems.pdf>.

   [I-D.farrel-irtf-introduction-to-semantic-routing]
              Farrel, A. and D. King, "An Introduction to Semantic
              Routing", Work in Progress, Internet-Draft, draft-farrel-
              irtf-introduction-to-semantic-routing-04, 25 April 2022,
              <https://datatracker.ietf.org/doc/html/draft-farrel-irtf-
              introduction-to-semantic-routing-04>.

   [I-D.hardjono-blockchain-interop-arch]
              Hardjono, T., Hargreaves, M., Smith, N., and V.
              Ramakrishna, "Interoperability Architecture for DLT
              Gateways", Work in Progress, Internet-Draft, draft-
              hardjono-blockchain-interop-arch-03, 6 November 2021,
              <https://datatracker.ietf.org/doc/html/draft-hardjono-
              blockchain-interop-arch-03>.





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   [I-D.hargreaves-odap]
              Hargreaves, M., Hardjono, T., and R. Belchior, "Open
              Digital Asset Protocol", Work in Progress, Internet-Draft,
              draft-hargreaves-odap-03, 6 November 2021,
              <https://datatracker.ietf.org/doc/html/draft-hargreaves-
              odap-03>.

   [I-D.ip-address-privacy-considerations]
              Finkel, M., Lassey, B., Iannone, L., and B. Chen, "IP
              Address Privacy Considerations", Work in Progress,
              Internet-Draft, draft-ip-address-privacy-considerations-
              03, 10 January 2022,
              <https://datatracker.ietf.org/doc/html/draft-ip-address-
              privacy-considerations-03>.

   [I-D.mcbride-rtgwg-bgp-blockchain]
              McBride, M., Trossen, D., Guzman, D., and T. Martin, "BGP
              Blockchain", Work in Progress, Internet-Draft, draft-
              mcbride-rtgwg-bgp-blockchain-03, 6 February 2024,
              <https://datatracker.ietf.org/doc/html/draft-mcbride-
              rtgwg-bgp-blockchain-03>.

   [IFIPNetworking2022]
              Khandaker, K. S., Trossen, D., Khalili, R., Despotovic,
              Z., Hecker, A., and G. Carle, "CArDS: Dealing a New Hand
              in Reducing Service Request Completion Times", Paper IFIP
              Networking, 2022.

   [IIC_whitepaper]
              Trossen, D., Guzman, D., Kelkar, A., Fan, X., McBride, M.,
              Zhang, L., and U. Graf, "Impact of Distributed Ledgers on
              Provider Networks", Whitepaper Industry IoT Consortium
              Whitepaper, 2022, <https://www.iiconsortium.org/
              pdf/2022-01-10-Impact-of-Distributed-Ledgers-on-Provider-
              Networks.pdf>.

   [P2958]    "P2958: Standard for a Decentralized Identity and Access
              Management Framework for Internet of Things",
              Standard IEEE Standards Association.,
              <https://standards.ieee.org/ieee/2958/10483/>.

   [P3210]    "P3210: Standard for Blockchain-based Digital Identity
              System Framework", Standard IEEE Standards Association.,
              <https://standards.ieee.org/ieee/3210/10242/>.







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   [SarNet2021]
              Glebke, R., Trossen, D., Kunze, I., Lou, Z., Rueth, J.,
              Stoffers, M., and K. Wehrle, "Service-based Forwarding via
              Programmable Dataplanes", Paper 1st Intl Workshop on
              Semantic Addressing and Routing for Future Networks, 2021.

   [SOI]      Jiang, S., Li, G., and B. Carpenter, "A New Approach to a
              Service Oriented Internet Protocol", Paper IEEE INFOCOM
              2020 - IEEE Conference on Computer Communications
              Workshops (INFOCOM WKSHPS), 2020.

Authors' Addresses

   Dirk Trossen
   Huawei Technologies
   Munich
   Germany
   Email: dirk.trossen@huawei.com


   David Guzman
   Technical University Munich
   Munich
   Germany
   Email: david.a.guzman.c@gmail.com


   Mike Mc Bride
   FutureWei
   Email: michael.mcbride@futurewei.com


   Xinxin Fan
   IoTeX
   Email: xinxin@iotex.io
















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