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.
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Task Force (IETF). Note that other groups may also distribute
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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
Provisions Relating to IETF Documents (https://trustee.ietf.org/
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Please review these documents carefully, as they describe your rights
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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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