



Network Working Group                                       J. Dong, Ed.
Internet-Draft                                       Huawei Technologies
Intended status: Informational                           M. McBride, Ed.
Expires: 23 April 2026                                         Futurewei
                                                            F. Clad, Ed.
                                                           Cisco Systems
                                                                Z. Zhang
                                                        Juniper Networks
                                                                  Y. Zhu
                                                           China Telecom
                                                                   X. Xu
                                                            China Mobile
                                                                 R. Pang
                                                            China Unicom
                                                                   H. Lu
                                                                  Y. Liu
                                                                 Tencent
                                                            L. Contreras
                                                              Telefonica
                                                               M. Durmus
                                                                Turkcell
                                                         20 October 2025


                  Fast Notification Problem Statement
                 draft-dong-fantel-problem-statement-00

Abstract

   Modern networks require adaptive traffic manipulation including
   Traffic Engineering (TE), load balancing, flow control and protection
   etc. to support applications like AI training and real-time services.
   A good and timely understanding of network operational status, such
   as congestion and failures, can help improve utilization, reduce
   latency, and enable faster response to critical events.  This
   document describes the existing problems and why the IETF may need a
   new set of fast notification related solutions to support any high-
   throughput, low-latency and lossless application.

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
   and may be updated, replaced, or obsoleted by other documents at any
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   This Internet-Draft will expire on 23 April 2026.

Copyright Notice

   Copyright (c) 2025 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
     1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
   2.  Glossary  . . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  The Problem . . . . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Example: AI Training Cluster with Fiber Link Failure  . . . .   5
     4.1.  Limitations of Existing Mechanisms  . . . . . . . . . . .   5
     4.2.  How Fast Notification Helps . . . . . . . . . . . . . . .   6
   5.  Fast Notification Problem Statement . . . . . . . . . . . . .   7
     5.1.  Information of Fast Notifications . . . . . . . . . . . .   8
     5.2.  Recipients of Fast Notifications  . . . . . . . . . . . .   8
     5.3.  Delivery of Fast Notifications  . . . . . . . . . . . . .  11
   6.  Summary . . . . . . . . . . . . . . . . . . . . . . . . . . .  12
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  12
   8.  Security Considerations . . . . . . . . . . . . . . . . . . .  12
   9.  Acknowledgement . . . . . . . . . . . . . . . . . . . . . . .  13
   10. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  13
   11. References  . . . . . . . . . . . . . . . . . . . . . . . . .  13
     11.1.  Normative References . . . . . . . . . . . . . . . . . .  13
     11.2.  Informative References . . . . . . . . . . . . . . . . .  13
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  14








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1.  Introduction

   Modern network applications, ranging from AI training to large-scale
   cloud services, require lossless and adaptive networks to ensure
   reliable, congestion-free data transfer within a single data center
   or across multiple sites.  These workloads demand high throughput,
   low latency, and minimal packet loss across dynamically shifting
   traffic patterns.  To meet these requirements, networks employ
   mechanisms such as traffic engineering (TE), load balancing, flow
   control, and protection.  However, existing solutions often face
   limitations in responsiveness, coverage, and operational complexity,
   particularly in high-speed, large-scale environments.

   This document summarizes the limitations of existing mechanisms that
   prevent rapid notification and action to critical network events,
   including link or node failures and congestion.  This document
   describes why the IETF may need a new set of fast notification
   related solutions to support these use cases.
   [I-D.geng-fantel-fantel-gap-analysis] provides a gap analysis of
   existing solutions and where they are deficient in supporting high
   demand services.  This document primarily focuses on describing the
   problem space.

1.1.  Requirements Language

   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 [RFC2119].

2.  Glossary

   FaNTEL: Fast Notification for Traffic Engineering and Load Balancing

   FRR: Fast Re-Route

   ECN: Explicit Congestion Notification

   BFD: Bidirectional Forwarding Detection

   IOAM: In-situ Operations, Administration, and Maintenance











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3.  The Problem

   Current network traffic manipulation mechanisms such as TE, load
   balancing, flow control, and protection, has deficiencies in
   providing the low-latency, high-granularity responsiveness needed in
   modern, dynamic networks, at least in part due to the lack of dynamic
   network state information.  This results in suboptimal performance,
   low reliability and delayed recovery.  FaNTEL is proposed as a set of
   solutions to address this by enabling fast, real-time, lightweight
   notifications that enhance the responsiveness for traffic
   engineering, congestion mitigation, and rapid failure protection.
   There is a demonstrable need for a standardized framework in IETF to
   define these fast notification mechanisms, requirements and
   integration strategies.

   The following describes a summary of limitations of existing
   notification solutions:

   *  Slow Reaction: Existing control protocols (e.g., routing protocol,
      etc.) may be used for dissemination of dynamic network state
      information, while they usually rely on control plane based hop-
      by-hop distribution, which causes delay when the recipient is
      multiple hops away.  With modern high-throughput environments (AI/
      ML clusters, multi-DC WANs), this delay is often prohibitive.
      Explicit Congestion Notification (ECN) [RFC3168] needs congestion
      signals to be sent back to the sender, which can be slow if the
      source node is far away, and it relies on the source node to react
      in the transport layer.  What is needed is a lightweight signaling
      method that can provide real-time alerts (e.g., at the level of
      sub-10 ms) on failures, congestion, or threshold breaches,
      enabling immediate actions (e.g., in ms to 10s ms ranges) in the
      network layer.

   *  Coarse-Grained Signals: ECN and similar mechanisms only provide
      binary or threshold-based feedback, without granularity for rapid,
      fine-tuned adjustments.  This leads to either overreaction or
      underutilization of available capacity.  What would be useful is a
      set of notifications that aren't just "on-off" state reports but
      can also convey information like congestion level/utilization
      information, latency spikes, queue buildup or flow
      characteristics, so that it can trigger immediate and precise
      responses like rerouting, rate adjustment, or protection switching
      for specific flows.

   *  Overhead and Churn: IOAM [RFC9197] and similar tools provide
      detailed telemetry information, but the collection and feedback
      loops are controller-centric.  They cannot be used to deliver
      lightweight, real-time alerts for immediate action on specific



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      network nodes.  And carrying dynamic network state information in
      control protocols (e.g. routing protocols) also increases the
      overhead and churn of the control plane, which may have negative
      impact to the core functionality of the protocol.  It would be
      useful to have solutions designed to avoid the overhead and churn
      introduced by telemetry flooding or route distribution, so it can
      adapt to large-scale networks and dynamic traffic patterns (e.g.
      AI workloads, cloud WAN bursts).

   *  Local-Only Decision Making: Current load-balancing, flow-control
      and fast reroute (FRR) techniques often act on local information
      and fail to capture downstream or cross- domain network
      conditions, limiting their effectiveness.  The Point of Local
      Repair (PLR) makes its decision based on its local view of the
      topology and network status.  It does not know about the state of
      the entire path of the backup route (e.g., if the backup path
      itself is congested).  It would be helpful to send fast
      notifications to upstream nodes which can perform the action based
      on the view of regional or global network conditions.

   *  Scalability Challenges: High-volume information or frequent
      signaling introduces bandwidth and processing overhead.  At scale,
      this becomes a bottleneck rather than a solution.

4.  Example: AI Training Cluster with Fiber Link Failure

   Consider a large-scale AI/ML training job distributed across multiple
   data centers.  These clusters exchange terabits per second of data
   between GPU nodes, requiring ultra-low latency and high throughput to
   maintain synchronization.

   In such environments, a single fiber link failure or severe
   congestion event can disrupt the entire training run, leading to:

   *  Delays in job completion (hours to days for large models)

   *  Massive energy and compute cost waste due to resynchronization

   *  Degraded convergence accuracy if synchronization windows are
      missed

4.1.  Limitations of Existing Mechanisms

   Today's mechanisms provide partial solutions but are not fast or
   precise enough for these scenarios:






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   *  BFD [RFC5880]: Provides fast forwarding path failure detection.
      It can be used for both link and path failure detection, while it
      cannot be used to detect link or path congestion, nor can it
      notify the failure or congestion to other nodes in the network.
      BFD is preconfigured with periodic message exchange, while fast
      notifications needs to be event-driven.  When the transmit
      interval is set to a small value (e.g., at the level of ms),
      frequent BFD message exchange may become a burden to some systems.

   *  FRR [RFC4090][RFC5714]/Route convergence: Without fast
      notification, the failure detection can take tens of milliseconds,
      followed by either local repair (FRR) or route convergence.  The
      former lacks of global network situation thus may cause congestion
      on the backup paths, while the latter may breach strict
      synchronization deadlines.

   *  ECN: Provides binary congestion feedback to the endpoints, which
      is insufficient for granular congestion spikes on high-speed
      links, and the action can be slow.

   *  Telemetry (e.g., IOAM): Offers detailed information, but relies on
      collection and RTT-based feedback, which delays action.

   *  Receiver/Sender Flow Control: Tied to RTT or packet loss,
      unsuitable for the bursty nature of AI traffic patterns.

   In practice, this means that by the time a fiber link failure is
   detected and recovery mechanisms are invoked, critical GPU
   synchronization barriers may already be missed, forcing rollbacks or
   restarts of the training process.

4.2.  How Fast Notification Helps

   Fast notification mechanisms could improve the response to fiber link
   failures and congestion in AI/ML clusters:

   *  Real-Time Alerts: Nodes adjacent to the failure or congestion
      could immediately (e.g., at 10 ms level) send lightweight
      notifications to nodes whose fowarding paths can be affected.

   *  Action-Oriented Response: Upon receiving the notification, routing
      and load balancing mechanisms could instantly shift traffic to
      backup paths or alternative DC interconnects.

   *  Granularity: Notifications could carry more detailed information
      than "link failure/congestion," e.g., indicating specific link
      utilization, queue buildup or microburst congestion, allowing
      differentiated responses to different traffic flows.



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   *  Complementary: The fast notification solutions are complementary
      to BFD or IOAM, it would bridge the time gap between event onset
      and slower control plane or telemetry-driven responses, and enable
      network-wide optimization.

   By deploying fast notifications, large AI/ML workloads can maintain
   synchronization across data centers even during transient failures or
   congestion, protecting job completion time and resource utilization.

           +-------------------------+       +-------------------------+
           |   Data Center A (GPU)   |-------|   Data Center B (GPU)   |
           +-------------------------+       +-------------------------+
                        |                              |
                        |     High-speed Fiber Link    |
                        +-----------X  (Failure) ------+
                                    |
                              (Failure Event)

        Figure 1: AI Training Cluster with Fiber Link Failure

   Existing Approach:

   *  BFD detects failure after tens of ms

   *  FRR causes congestion on backup paths

   *  Reroute/convergence delays impact GPU sync

   *  Result: Training stalls, job wastes compute

   Fast Notifications Approach:

   *  BFD detects failure after tens of ms

   *  Fast notification alerts upstream nodes of failure or congestion
      in real time

   *  Regional or global TE steers traffic quickly to link without
      causing new congestion

   *  Result: Training continues with minimal disruption

5.  Fast Notification Problem Statement








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5.1.  Information of Fast Notifications

   The information carried in the fast notifications, by the originating
   node, can be one or multiple of the following:

   *  Failure information: This can include the location of failure, and
      the type of failure.

   *  Fine-grained Congestion information: This can include link
      utilization, queue length, or the level of congestion, together
      with the location where the congestion happens.

   *  Fine-grained Performance information: This can include link or
      node delay, jitter, packet loss information etc., together with
      the location where the performance degradation happens.

   *  Path identification information: This can be used to indicate the
      path along which one service flow is being forwarded.

   *  Flow identification information: This can include either the
      identification or the 5-tuple of a flow.

   Other information related to the network status and need to be timely
   actioned may also be carried in the fast notifications.  Thus there
   is a need to work on the information model of Fast Notifications to
   better understand what needs to be carried in the notifications.

5.2.  Recipients of Fast Notifications

   Fast notifications may be consumed by two broad forms of recipients:
   (1) recipient nodes that participate directly in forwarding or
   signaling, and (2) functions and applications that consume
   notifications in order to optimize, monitor, or adapt behaviors.
   Separating these categories clarifies which entities are physical/
   logical nodes versus which are higher-level functional consumers.
















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     +==================+======================+=======================+
     | Node Type        | Role                 | Example Benefit       |
     +==================+======================+=======================+
     | Adjacent Routers | Data-plane neighbors | Enable local repair   |
     | / Switches       | that forward packets | (e.g., FRR, ECMP      |
     |                  |                      | adjustments)          |
     +------------------+----------------------+-----------------------+
     | Non-Adjacent     | Remote upstream      | Accelerated awareness |
     | Routers /        | forwarding elements  | of failure/congestions|
     | Switches         |                      | on specific nodes     |
     +------------------+----------------------+-----------------------+
     | Ingress Routers  | Traffic entry points | Re-map affected flows |
     |                  | of a network         | before forwarding     |
     |                  | domain               | into failed regions   |
     +------------------+----------------------+-----------------------+
     | End Hosts / Edge | Optional             | Adapt sending rate,   |
     | Nodes            | subscribers, policy- | select alternate      |
     |                  | driven               | uplinks               |
     +------------------+----------------------+-----------------------+
     | Network Controler| Optional             | Accelerated awareness |
     | / PCE            | subscribers, policy- | of failure/congestion |
     |                  | driven               | for global TE/LB      |
     +------------------+----------------------+-----------------------+

                    Table 1: Recipient Nodes


























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   +=======================+===============+===========================+
   | Function /            | Role          | Example Benefit           |
   | Application           |               |                           |
   +=======================+===============+===========================+
   | Routing Protocols     | Control-plane | Accelerated path re-      |
   | (OSPF, IS-IS, BGP)    | convergence   | computation after failure |
   +-----------------------+---------------+---------------------------+
   | Traffic Engineering   | Centralized   | Pre-compute new paths     |
   | Controllers (PCE/     | optimization  | before congestion         |
   | SDN)                  |               | propagates                |
   +-----------------------+---------------+---------------------------+
   | Network Operators     | Operational   | Faster troubleshooting,   |
   | (NMS/OSS)             | visibility    | earlier alerting          |
   +-----------------------+---------------+---------------------------+
   | Telemetry /           | Monitoring    | Predictive analytics, ML- |
   | Analytics Systems     | and           | based congestion          |
   |                       | prediction    | forecasting               |
   +-----------------------+---------------+---------------------------+
   | Applications /        | Critical app  | AI workloads, financial   |
   | Services              | consumers     | apps adapt to degraded    |
   |                       |               | links                     |
   +-----------------------+---------------+---------------------------+

                 Table 2: Recipient Functions and Applications



























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                      +-----------------------------+
                      |     Application Plane       |
                      |  - Applications / Services  |
                      |  - End Hosts / Edge Nodes   |
                      +-------------^---------------+
                                    |
                      +-------------|---------------+
                      |  Management Plane           |
                      |  - Operators (NMS/OSS)      |
                      |  - Telemetry / Analytics    |
                      +-------------^---------------+
                                    |
                      +-------------|---------------+
                      |  Control Plane              |
                      |  - Routing Protocols        |
                      |  - TE Controllers (PCE/SDN) |
                      +-------------^---------------+
                                    |
                      +-------------|----------------+
                      |  Data Plane                  |
                      |  - Adjacent Routers/Switches |
                      |  - Non-Adjacent Routers      |
                      |  - Ingress Routers           |
                      +------------------------------+

          Figure 2: Notification Recipients Across Network Planes


   As illustrated above, the latency sensitivity of recipients decreases
   as one moves from the data plane to the application plane.  Recipient
   nodes (e.g., adjacent forwarding elements, ingress routers,etc.)
   often require near-instantaneous notification, while functions and
   applications (e.g., routing protocols, analytics, NMS, etc.) may
   tolerate slightly longer timescales but still benefit from rapid
   awareness compared to existing mechanisms.  The range of recipients
   of the notification depends on the type of recipients, it also
   depends on what type of action is required.  The mechanism to
   determine the type and range of the recipients is something needs
   further consideration.

5.3.  Delivery of Fast Notifications

   Depending on the position and number of the recipient nodes, fast
   notifications may be sent via one of the following delivery modes:

   *  Unicast directly to the recipient node

   *  Multicast to a group of recipient nodes



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   *  Hop-by-hop to a series of receipt nodes along a specified path

   *  Flooding in a specified range of the network

   Additionally, recipient nodes or functions may subscribe to specific
   types of notifications based on their roles or interests.  A
   subscription-based approach enables selective delivery, reduces
   unnecessary signaling overhead, and ensures that each recipient
   receives only the information relevant to its function.  Mechanisms
   supporting both delivery and subscription must guarantee timely,
   reliable, and secure propagation of notifications.  Examples:

   *  Adjacent routers subscribing to all local failure notifications

   *  Centralized controllers subscribing only to congestion alerts
      exceeding defined thresholds

   *  Applications or analytics systems subscribing to performance
      degradation events affecting specific flows or services

   The mechanisms to support the above delivery mode needs to make sure
   the notification is always sent to the targeted recipient noded in a
   timely manner.  It could be based on existing messaging and transport
   mechanisms, or a new protocol may be introduced.

6.  Summary

   Current network mechanisms were not designed for the responsiveness
   and scale required by todays' dynamic environments.  Techniques such
   as load balancing, protection switching, and flow control rely on
   telemetry and feedback loops that are often too slow, too coarse, or
   too resource-intensive.  This results in performance bottlenecks,
   delayed recovery, and inefficiencies in large-scale AI, cloud, and
   WAN deployments.  A fast notification mechanism could help to address
   these gaps by providing lightweight, real-time, actionable alerts
   that complement existing tools and enable faster, more accurate
   network management decisions.

7.  IANA Considerations

   This document has no IANA actions.

8.  Security Considerations

   Fast notifications,






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   if not properly authenticated and rate-limited, could be exploited as
   a vector for Denial-of-Service (DoS) attacks.  An attacker able to
   inject or flood spurious notifications may trigger unnecessary re-
   convergence, path changes or repeated state updates, overwhelming
   both recipient nodes and higher-level applications.  Implementations
   must therefore ensure integrity protection, origin authentication,
   and appropriate rate controls on notification messages.

9.  Acknowledgement

   The authors would like to thank XXX for the valuable comments and
   discussion.

10.  Contributors

   The following people contributed substantially to the content of this
   document.

   Zafar Ali
   Cisco
   zali@cisco.com

   Tianran Zhou
   Huawei
   zhoutianran@huawei.com

   Xuesong Geng
   Huawei
   gengxuesong@huawei.com

11.  References

11.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/info/rfc2119>.

11.2.  Informative References

   [I-D.geng-fantel-fantel-gap-analysis]
              Geng, X., Huo, P., Cheng, W., Li, D., Zhu, Y., and H.
              Zhengxin, "Gap Analysis of Fast Notification for Traffic
              Engineering and Load Balancing", Work in Progress,
              Internet-Draft, draft-geng-fantel-fantel-gap-analysis-01,
              7 July 2025, <https://datatracker.ietf.org/doc/html/draft-
              geng-fantel-fantel-gap-analysis-01>.



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   [RFC3168]  Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
              of Explicit Congestion Notification (ECN) to IP",
              RFC 3168, DOI 10.17487/RFC3168, September 2001,
              <https://www.rfc-editor.org/info/rfc3168>.

   [RFC4090]  Pan, P., Ed., Swallow, G., Ed., and A. Atlas, Ed., "Fast
              Reroute Extensions to RSVP-TE for LSP Tunnels", RFC 4090,
              DOI 10.17487/RFC4090, May 2005,
              <https://www.rfc-editor.org/info/rfc4090>.

   [RFC5714]  Shand, M. and S. Bryant, "IP Fast Reroute Framework",
              RFC 5714, DOI 10.17487/RFC5714, January 2010,
              <https://www.rfc-editor.org/info/rfc5714>.

   [RFC5880]  Katz, D. and D. Ward, "Bidirectional Forwarding Detection
              (BFD)", RFC 5880, DOI 10.17487/RFC5880, June 2010,
              <https://www.rfc-editor.org/info/rfc5880>.

   [RFC9197]  Brockners, F., Ed., Bhandari, S., Ed., and T. Mizrahi,
              Ed., "Data Fields for In Situ Operations, Administration,
              and Maintenance (IOAM)", RFC 9197, DOI 10.17487/RFC9197,
              May 2022, <https://www.rfc-editor.org/info/rfc9197>.

Authors' Addresses

   Jie Dong (editor)
   Huawei Technologies
   Email: jie.dong@huawei.com


   Mike McBride (editor)
   Futurewei
   Email: mmcbride7@gmail.com


   Francois Clad (editor)
   Cisco Systems
   Email: fclad@cisco.com


   Jeffrey Zhang
   Juniper Networks
   Email: zzhang@juniper.net


   Yongqing Zhu
   China Telecom
   Email: zhuyq8@chinatelecom.cn



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   Xiaohu Xu
   China Mobile
   Email: xuxiaohu_ietf@hotmail.com


   Ran Pang
   China Unicom
   Email: pangran@chinaunicom.cn


   Hao Lu
   Tencent
   Email: vickkylu@tencent.com


   Yadong Liu
   Tencent
   Email: zeepliu@tencent.com


   Luis M. Contreras
   Telefonica
   Email: luismiguel.contrerasmurillo@telefonica.com


   Mehmet Durmus
   Turkcell
   Email: mehmet.durmus@turkcell.com.tr























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