Agent Communication Framework for Network AIOps
draft-fu-nmop-agent-communication-framework-00
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| Document | Type | Active Internet-Draft (individual) | |
|---|---|---|---|
| Authors | Yu Fu , Sun Qiong , Xin Song , Chongfeng Xie | ||
| Last updated | 2026-01-24 | ||
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| Intended RFC status | (None) | ||
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draft-fu-nmop-agent-communication-framework-00
nmop Y. Fu
Internet-Draft Q. Sun
Intended status: Standards Track X. Song
Expires: 29 July 2026 C. Xie
China Telecom
25 January 2026
Agent Communication Framework for Network AIOps
draft-fu-nmop-agent-communication-framework-00
Abstract
As the development of large model and agent technology, it is a trend
for multi-agent collaboration to solve complex problems. This
document proposes an Agent Communication Framework, a multi-agent
communication and collaboration framework that facilitates the
coordination of heterogeneous multi-agents and supports intelligent
network operations and maintenance (AIOps). Its architecture
includes an AI gateway and an Agent Name Service, along with
capabilities such as monitoring and tracking, as well as security
protection. Agent Communication Framework provides a comprehensive
solution for multi-agent communication and collaboration, laying the
foundation for future interactive, scalable, secure, and controllable
multi-agent network intelligent operations and maintenance.
Status of This Memo
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Copyright Notice
Copyright (c) 2026 IETF Trust and the persons identified as the
document authors. All rights reserved.
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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 . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Requirements Language . . . . . . . . . . . . . . . . . . 3
1.2. Definition and Terminology . . . . . . . . . . . . . . . 3
2. Agent Communication Framework and Components . . . . . . . . 3
2.1. AI Gateway . . . . . . . . . . . . . . . . . . . . . . . 5
2.2. Agent Name Service . . . . . . . . . . . . . . . . . . . 7
2.2.1. Agent Accessing . . . . . . . . . . . . . . . . . . . 7
2.2.2. Agent Addressing . . . . . . . . . . . . . . . . . . 8
2.2.3. Security Protection . . . . . . . . . . . . . . . . . 9
2.2.4. Capabilities Monitoring and Management . . . . . . . 9
2.2.5. Cross-domain synchronization . . . . . . . . . . . . 9
3. Use Case . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4. Security Considerations . . . . . . . . . . . . . . . . . . . 12
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 12
6. Normative References . . . . . . . . . . . . . . . . . . . . 12
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 13
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 13
1. Introduction
As the rapid development of AI technology, network operations and
maintenance have evolved from efficiency improvement to automation,
through the Data-Driven Digital age with the rise of AIOps
(intelligent network operations and maintenance), now striding
towards the Agentic AI stage. In this new phase, the collaborative
capabilities of intelligent agents will drive operations and
maintenance toward a higher level of autonomy. However, current
multi-agent collaboration still lacks reliable mechanisms for agent
addressing, communication, and orchestration scheduling. It
introduces several requirements as below:
• Agent registering and discovering：With the rapid developments of
multi-agent collaborative scenarios, traditional service discovery
mechanisms face several challenges. They are unable to adapt to the
multi-heterogeneous and dynamically changing capability of agents.
There is a lack of a unified capability of registration and discovery
framework for the cross-domain and spans different subject agents,
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result in low efficiency of task-driven precise collaboration. There
is an urgent need to build a global agent capability registration
mechanism, dynamically maintain the real-time capability database of
agents across the network, and generate optimal matching strategies
based on task requirements.
• Cross-domain interconnection: In some task-oriented collaboration
scenarios, it may encounter interoperability challenges—both within
intra-domain and inter-domain use cases. In inter-domain scenario,
agents belonging to different domains must discover, access, and
securely interact with one another to enable effective collaboration.
• Security Operations: To support large-scale deployment of
intelligent agents, a comprehensive operation-level security
framework is required that integrates management, access control,
traceability, and authentication tailored for agent-centric
environments., with security mechanisms and capabilities such as zero
trust, communication encryption and decryption, and supervision
embedded in the protocol.
1.1. Requirements Language
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.
1.2. Definition and Terminology
• ACF：Agent Communication Framework
• ANS：Agent Name Service
• AI Gateway：AI GW
2. Agent Communication Framework and Components
To address the requirements described above, we propose an Agent
Communication Framework for intra-domain and inter-domain agent
communications. It consists of two components: AI Gateway and Agent
Name Service (ANS). It is the “Connection and control Hub” for agent
communication. The overview of the agent communication framework is
shown in Figure 1.
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+---------------------------+ +----------------------------+
| | | |
| Domain1: ACF | | Domain2: ACF |
| | | |
| | | |
| +--------------------+ | | +---------------------+ |
| | | | | | | |
| | Agent Name Service <---+-----+--> Agent Name Service | |
| | | | | | | |
| +---------^----------+ | | +--------^------------+ |
| | | | | |
| | | | | |
| +-----v-----+--<-----+-----+--->--+----v------+ |
| | | | | | | |
| | | | | | | |
| +---v---+ +---v---+ | | +---v---+ +---v-- + |
| | | | | | | | | | | |
| | AI GW | | AI GW | | | | AI GW | | AI GW | |
| | | | | | | | | | | |
| +---^---+ +---^---+ | | +---^---+ +---^---+ |
| | | | | | | |
| | | | | | | |
+------+-----------+--------+ +------+-----------+---------+
| | | |
| | | |
+---v---+ +---v---+ +---v---+ +---v---+
| | | | | | | |
| Agent | | Agent | | Agent | | Agent |
| | | | | | | |
+-------+ +-------+ +-------+ +-------+
As described in Section 1, efficient interconnection among agents
relies on clear identity information and capability-based discovery.
Therefore, a unified identity identification and agent information
management mechanism forms the foundation for the secure agent
interconnection. Agent Communication Framework issue unique identity
IDs for each agent and establish an authentication framework to
ensure the security of mutual visits. They are capable of managing
information for a massive number of agents, able to obtain agent
information through multiple methods to ensure information
comprehensiveness. In Agent Communication Framework, a semantics-
based dynamic agent addressing scheme is proposed to enhance the
accuracy and flexibility of agent interconnection and collaboration,
enabling interoperability across different domains. In Intra-domain
scenarios, the agent communication framework enables the discovery
and management within the domain and presents a unified proxy
externally. Independent AI gateways realize the unified access and
mutual discovery of agents within domains such as edge homes and the
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Internet of Things. In inter-domain scenarios, information
synchronization mechanism needs to be done by designing as an agent
information repository in Agent Name Service (ANS) between different
domains, combining with the existing DNS mechanisms for cross-domain
addressing and discovery of agents.
2.1. AI Gateway
An AI Gateway is a reliable, efficient, and secure interconnection
hub for agents. The main functions of AI Gateway include:
* Service Proxy: Service Proxy function acts as an intelligent
network address translation (NAT) layer that seamlessly translates
between internal and external network addresses, enabling secure
communication between private services and external clients. By
masking the identities and IP addresses of internal agents or
services, it effectively hides the internal network topology from
external access, thereby enhancing security, reducing exposure to
potential threats, and simplifying service exposure management.
* Traffic forwarding and optimization: The AI Gateway provides
intelligent traffic forwarding and optimization capabilities,
including Quality of Service (QoS) guarantees to prioritize
critical workloads, dynamic multi-channel selection for optimal
path routing based on real-time network conditions, and packet
compression to reduce bandwidth consumption and latency.
Additionally, it leverages AI-driven analytics to adaptively
manage traffic flows, ensure reliable delivery, and enhance
overall network efficiency and user experience.
* Security protection: It provides comprehensive security protection
by implementing end-to-end channel encryption to ensure data
confidentiality and integrity during transmission, coupled with
advanced traffic security detection and real-time threat
mitigation mechanisms—such as anomaly detection, intrusion
prevention, and malicious payload filtering—to safeguard against
cyberattacks and unauthorized access.
* Monitoring and auditing: It provides comprehensive monitoring and
auditing capabilities by continuously observing and logging all
interaction behaviors between agents, including request sources,
destinations, timestamps, data payloads (where permitted), and
access patterns.
In addition to the capabilities described above, the AI Gateway also
supports the requirements of high concurrency, high reliability, as
well as scalability.
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* The AI Gateway supports persistent, always online sessions for
heterogeneous agents, enabling seamless dynamic
participation—where agents can join or leave a session at any time
without disrupting the workflow. It ensures session continuity
through intelligent checkpointing and resumption mechanisms,
allowing tasks to resume exactly from the point of interruption in
the event of network disconnections or agent failures, without
requiring the entire task to be restarted. This capability
maintains task integrity, improves resource efficiency, and
enhances reliability in complex, multi-agent collaborative
scenarios.
* The AI Gateway is designed to deliver highly concurrent, secure,
and ultra-low-latency asynchronous communication for multi-agent
systems, supporting scalable workloads with millions of
simultaneous connections. It ensures robust security through end-
to-end encryption and fine-grained access control, while
optimizing message routing and processing to minimize
latency—enabling efficient, real-time coordination among large-
scale heterogeneous agents
* The AI Gateway is designed for high scalability, supporting both
horizontal and vertical expansion to accommodate growing multi-
agent workloads. Horizontally, it enables elastic scaling of
gateways to handle increased traffic and agent density by
dynamically adding or removing nodes based on demand. Vertically,
it implements recursive addressing across hierarchical gateway
layers, allowing seamless inter-layer communication and efficient
routing in large-scale, nested, or federated agent architectures.
Together, these capabilities ensure the system can scale flexibly
and efficiently—both outward across distributed deployments and
upward through logical abstraction layers—while maintaining
performance, consistency, and manageability.
* The AI Gateway supports high-reliability requirements for fully
autonomous, human-intervention-free interactions among agents. It
ensures continuously stable and fault-resilient network
connectivity through redundant pathways, automatic failover
mechanism—thereby preventing communication disruptions that could
otherwise trigger cascading failures across the agent ecosystem.
This reliability is critical to maintaining uninterrupted task
execution and system-wide stability in mission-critical multi-
agent environments.
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2.2. Agent Name Service
Agent Name Service provides access and semantic addressing function
for multi-agents, and combines with the AI Gateway to provide
security protection and monitoring capabilities.
2.2.1. Agent Accessing
* Registration: The Agent Name Service (ANS) provides a secure and
structured access mechanism for intelligent agents through an
integrated registration and identity management mechanism. It
begins with the Registration Module, which receives registration
requests from agents, validates their legitimacy (e.g., through
credentials, tokens, or domain policies), and initiates the
enrollment process. The Security Module then handles
cryptographic identity provisioning by accepting the agent’s
Certificate Signing Request (CSR), verifying its authenticity, and
issuing a signed certificate to establish trusted identity.
Finally, the Registry securely stores each agent’s
metadata—including its unique identifier, certificate,
capabilities—enabling reliable discovery, authentication, and
secure communication across the multi-agents. This end-to-end
workflow ensures that only authorized agents are admitted into the
system, with verifiable identities and consistent governance.
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* Update, Renewal and Revocation: The Agent Name Service (ANS)
supports comprehensive lifecycle management for registered agents
through secure and auditable update, renewal, and revocation
operations. For updates, agents may submit requests to modify
their metadata—such as capabilities, protocols, or agent Card
information. The ANS server performs signature verification to
authenticate the request and ensures backward compatibility; if
the changes introduce incompatibilities, the agent must update its
version number and do re-registration. Upon successful
validation, the ANS updates the corresponding versioned record in
its registry. For certificate renewal, agents initiate a renewal
request before their current certificate expires. The ANS
validates the agent’s identity via cryptographic signature
verification. After confirmation, it issues a new signed
certificate while updating the associated agent entry—ensuring
uninterrupted, trusted operation without service disruption. For
revocation, agents or administrators can request certificate
invalidation in cases of key expiration. After verifying the
authenticity of the revocation request through signature checks,
the ANS permanently removes the agent’s certificate and associated
metadata from the registry, immediately terminating its ability to
access. All operations are executed under strict cryptographic
validation and audit logging, ensuring integrity, traceability,
and continuous security across the agent lifecycle.
2.2.2. Agent Addressing
The Agent Name Service (ANS) provides a millisecond-level Semantic
Addressing Query capability that enables agent discovery—allowing
users or systems to express intent in plain language (e.g., “Poor
mobile signal and unstable broadband at home”) and automatically
resolving it to the most relevant agents (e.g., Home Broadband Agent
and Wireless Network Optimization Agent). Semantic-based addressing
and discovery of agents requires the Agent Name Service (ANS) to
possess comprehensive, detailed descriptive information for all
agents. This functionality is implemented through three coordinated
components:
• The Resolution Module receives semantic resolution requests from
agents and leverages RAG techniques to interpret the query and match
it to appropriate agent. • The Registry then retrieves the
corresponding agent’s metadata—including its capabilities, protocol
details, and certificate—based on the resolved semantic intent. •
Finally, the Security Module cryptographically signs the retrieved
agent information and certificate using the private key, ensuring
authenticity and integrity before returning the signed response to
the requester.
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2.2.3. Security Protection
The Agent Name Service (ANS) incorporates robust security and
governance mechanisms to ensure safe and controlled agent
interactions. It enforces fine-grained permission control at the
agent level through a structured workflow that includes registration
requests, administrative approval, and explicit
authorization—ensuring that only vetted agents gain access to
specific capabilities or resources.
To counter adversarial inputs, ANS integrates prompt injection
prevention by inspecting all incoming instructions or queries for
malicious patterns, obfuscated commands, or attempts to hijack agent
behavior, thereby safeguarding the integrity of agent operations.
Additionally, it implements tiered content security protection to
prevent sensitive information leakage, applying data classification
policies, context-aware filtering, and output sanitization based on
sensitivity levels.
2.2.4. Capabilities Monitoring and Management
The Agent Name Service (ANS) enables real-time monitoring of agent
reference, dynamically constructs a graph of agent relationships to
visualize interaction patterns and dependencies across the domain,
and supports proactive intervention in anomalous or unauthorized
behaviors.
The Agent Name Service (ANS) provides intelligent agent capability
management by systematically evaluating and verifying the functional
competencies, performance characteristics, and operational boundaries
of registered agents. This includes assessing declared capabilities,
validating actual behavior through runtime evidence or sandboxed
testing, and maintaining a trusted, up-to-date profile of each
agent’s verified skills. By ensuring that advertised capabilities
accurately reflect real-world functionality, ANS enables reliable
agent discovery, safe composition, and context-aware orchestration
within dynamic multi-agent domains.
2.2.5. Cross-domain synchronization
The Agent Name Service (ANS) enables cross-domain collaboration among
intelligent agents by securely synchronizing agent information. In
inter-domain scenarios, information synchronization mechanism needs
to be done by designing as an agent information repository in ANS
between different domains, and combining with the existing DNS
mechanisms for cross-domain addressing and discovery of agents.
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3. Use Case
* Case 1: Home Broadband Service Installation
In the scenario of handling home broadband service installation, we
employ a collaborative system comprising 13 agents, including the
Intent Recognition Agent, Domain-Specific Configuration Agent, Master
Control Agent, Service Validation Agent etc.
Phase 1: Service intent recognition
Agent Used: Intent Recognition Agent; Master Control Agent of service
installation
Action: 1.Identify users' service installation requirements by the
Intention Recognition Agent. 2.Automatically send the structured
service intent to the Master Control Agent.
Phase 2: Service Orchestration and Resource Allocation
Agent Used: Master Control Agent of service installation; Service
Orchestration and Resource Allocation Agent
Action: 1.The Master Control Agent sends the service installation
request to the Service Orchestration and Resource Allocation Agent,
completes the planning of the service path and the evaluation and
allocation of resources. 2.The Service Orchestration and Resource
Allocation Agent feedback the service path and resource allocation
plan back to the Master Control Agent.
Phase 3: Data Preparation and Distribution
Agent Used: Master Control Agent of service installation; Domain-
Specific Configuration Agent
Action: 1.The Service installation Master Control Agent initiates
data preparation and configuration requests based on the plan. 2.The
Domain-Specific Configuration Agent generates the systems
corresponding configuration data and completes the automatic
configuration of network elements (NEs) / network management systems.
3.As the completion of the configuration, the results are
automatically back to the Master Control Agent.
Phase 4: Service Validation
Agent Used: Master Control Agent of service installation; Domain-
Specific Configuration Agent; Service Validation Agent
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Action: 1.The Master Control Agent triggers the automated service
validation process. 2.The Service Validation Agent collaborates with
the Domain-Specific Configuration Agent to query the data of
configuration and status, and subsequently performs installation
verification and validation. 3.The validation results are back to
the Master Control Agent, forming a closed-loop validation cycle.
Phase 5: Quality monitoring
Agent Used: Installation and Maintenance Scheduling Agent
Action: 1.The Installation and Maintenance Scheduling Agent performs
continuous monitoring of customer services to ensure the quality of
new installations.
Phase 6: Customer feedback survey
Agent Used: Personal Intelligent Assistant Agent
Action: 1.The Personal Intelligent Assistant Agent schedules the
installation/maintenance engineers for service follow-up and review.
* Case 2: Home Broadband Network Fault Diagnosis
In the scenario of handling home broadband network fault diagnosis,
we employ a collaborative system comprising 13 agents, including the
Intent Recognition Agent, Preprocessing Agent, Single-Domain Root
Cause Analysis Agent, Knowledge Q&A Agent, Fault Handling Agent etc.
Phase 1: User Complaint Intent Recognition and Data Sensing
Agent Used: Intent Recognition Agent; Preprocessing Agent
Action: 1.Identify the type of user complaint by the Intention
Recognition Agent. 2.Automatically trigger the data preprocessing
function of the Preprocessing Agent based on the complaint type to
collect key information such as user devices, alarms, and networks
information. 3.Complete unified perception and aggregation of user-
side data.
Phase 2: Home Broadband Fault Complaint Handling
Agent Used: MSingle-Domain Root Cause Analysis Agent; Perception Data
Collection Agent; Knowledge Q&A Agent; Data Collection Agent
Action: 1.The Single-Domain Root Cause Analysis Agent performs
initial root cause analysis based on existing data.
2.If information is insufficient, it triggers the data recollection
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mechanism of the Perception Data Collection Agent. The Knowledge Q&A
Agent guides the user to supplement key information. The Data
Collection Agent complements the missing data. 3. After multiple
iterations, it outputs a most likely root cause, impact scope, and
recommendations.
Phase 3: Trouble Shooting
Agent Used: Fault Handling Agent; Installation and Maintenance
Scheduling Agent
Action: 1.The Fault Handling Agent supports automatic fault recovery.
2.If automatic repair fails, it triggers the Installation and
Maintenance Scheduling Agent to generate the optimal dispatch plan
based on the location and skills of the installation and maintenance
engineers, as well as the urgency of the fault.
Phase 4: Service Validation
Agent Used: End-to-End Testing Agent
Action: 1.The End-to-End Testing Agent initiates tests to ensure
service consistency.
Phase 5: Quality monitoring
Agent Used: Installation and Maintenance Scheduling Agent
Action: 1.The Installation and Maintenance Scheduling Agent performs
continuous monitoring of customer services to to prevent recurring
faults.
Phase 6: Customer feedback survey
Agent Used: Personal Intelligent Assistant Agent
Action: 1.The Personal Intelligent Assistant Agent schedules the
installation/maintenance engineers for service follow-up and review.
4. Security Considerations
TBD
5. IANA Considerations
This document has no IANA actions.
6. Normative References
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[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>.
[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>.
Acknowledgements
TBD
Authors' Addresses
Yu Fu
China Telecom
Beijing
China
Email: fuy44@chinatelecom.cn
Qing Sun
China Telecom
Beijing
China
Email: sunqiong@chinatelecom.cn
Xin Song
China Telecom
Beijing
China
Email: songx18@chinatelecom.cn
Chongfeng Xie
China Telecom
Beijing
China
Email: xiechf@chinatelecom.cn
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