Token Service Flow Awareness: Use Cases and Requirements
draft-wang-token-aware-usecases-requirements-00

Network Working Group                                            J. Wang
Internet-Draft                                              China Mobile
Intended status: Informational                               6 July 2026
Expires: 7 January 2027

        Token Service Flow Awareness: Use Cases and Requirements
            draft-wang-token-aware-usecases-requirements-00

Abstract

   This document outlines the use cases and requirements for token
   service flow awareness, providing the IETF working group with a
   standardized reference to better support the assurance of the user’s
   end-to-end experience.

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   This Internet-Draft will expire on 7 January 2027.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Conventions . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   3
     3.1.  Service Identification  . . . . . . . . . . . . . . . . .   3
     3.2.  Operation Management  . . . . . . . . . . . . . . . . . .   3
     3.3.  Routing . . . . . . . . . . . . . . . . . . . . . . . . .   3
   4.  Requirements  . . . . . . . . . . . . . . . . . . . . . . . .   3
     4.1.  Service Identification  . . . . . . . . . . . . . . . . .   4
     4.2.  Operation Management  . . . . . . . . . . . . . . . . . .   4
     4.3.  Routing . . . . . . . . . . . . . . . . . . . . . . . . .   4
   5.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .   4
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .   4
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   4
   8.  Informative References  . . . . . . . . . . . . . . . . . . .   4
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .   5

1.  Introduction

   In recent years, there has been a significant increase in the use of
   generative AI, LLM MaaS platforms, and autonomous AI Agents as
   mainstream internet services.  Unlike traditional web, video, and
   file transfer traffic, AI services generate unique token-bearing
   flows.  These include prompt/output token streaming, cross-Agent A2A
   collaborative token packets, and authorization tokens carried in JWT/
   OAuth headers.

   AI token flows have distinct business attributes, such as ultra-low
   Time-To-First-Token (TTFT) latency for interactive Agent dialogue,
   longer transmission delay tolerance for offline batch inference, and
   stable cross-domain connectivity for cross-industry multi-Agent
   collaboration.  However, current network traffic classification
   systems only identify generic application domains through SNI and DNS
   fingerprints, lacking fine-grained awareness of token volume, task
   priority, and Agent identity.  This lack of dedicated token flow
   identification capabilities hinders operators from deploying
   differentiated QoS strategies, implementing token-based metering
   billing, and executing compute-aware routing optimization.  As a
   result, there are consequences such as inconsistent dialogue latency,
   unfair bandwidth resource contention, inability to quantify AI
   service revenue, and unmonitored abnormal token consumption attacks.

   Against this background, this document outlines the use cases and
   requirements for token service flow awareness, providing the IETF
   working group with a standardized reference to better support the
   assurance of the user’s end-to-end experience..

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2.  Conventions

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
   "OPTIONAL" in this document are to be interpreted as described in BCP
   14 [RFC2119] [RFC8174] when, and only when, they appear in all
   capitals, as shown here.

3.  Use Cases

   This document categorizes use cases into service identification,
   operation & management and routing,

3.1.  Service Identification

   The core goal of sevice identification is to map raw packet flows to
   standardized token service types to deliver differentiated user
   experience and tiered service packages.  For example, personal multi-
   modal assistants, vehicle-mounted MUI Agents and customer service
   Agents generate low-latency interactive token streams.  After
   identification, the network can implement various optimization
   measures to reduce TTFT jitter.

3.2.  Operation Management

   The use case of operation management focus on full lifecycle
   monitoring, risk control and statistical analysis based on identified
   token flow tags.  Network management platforms aggregate identified
   token flow data to analyze industry distribution of Agent services,
   and forecast token traffic growth for capacity planning of edge
   computing and backbone links.

3.3.  Routing

   The use case of routing realize compute-network collaborative
   steering by leveraging token flow business attributes.  For example,
   after marking interactive token flows, routing planes dynamically
   select nearby edge computing gateway links, avoiding long-distance
   backbone transmission to cut end-to-end latency.  This enables
   latency-priority routing of real-time token streams.

4.  Requirements

   Corresponding to the three use cases, this chapter defines mandatory
   and optional requirements for service identification, operation
   management and routing steering respectively.

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4.1.  Service Identification

   Identification equipment SHALL parse plaintext token count headers in
   SSE/gRPC/MCP streaming protocols, and extract Agent ID, task type and
   authorization token fields.  For fully encrypted TLS traffic, the
   system MUST implement traffic fingerprint recognition based on packet
   interval, burst small-packet characteristics and TTFT statistical
   features to classify token flows without payload decryption.

4.2.  Operation Management

   To ensure the smooth operation of the service, the operations
   management platform should support the ability to record service
   logs.  All identified token flows SHALL generate structured logs
   containing five-tuple, token label, total token volume, start/end
   timestamp and Agent identity information, , stored for no less than
   user service period for audit.

4.3.  Routing

   It should support different routing policies for different services
   to provide differentiated service guarantees and meet the needs of
   different users.  In addition, routing nodes supporting KV context
   cache reuse shall match token flow labels to cache corresponding
   prompt data, reducing repeated token transmission volume and link
   load.

5.  Conclusion

   This document outlines the use cases and requirements for token
   service flow awareness and provides an overview from three
   perspectives: service identification, operation management and
   routing,

6.  Security Considerations

   TBD.

7.  IANA Considerations

   TBD.

8.  Informative 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>.

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   [RFC8174]  Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
              2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
              May 2017, <https://www.rfc-editor.org/info/rfc8174>.

Author's Address

   Jing Wang
   China Mobile
   No.32 XuanWuMen West Street
   Beijing
   100053
   China
   Email: wangjingjc@chinamobile.com

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