Internet Engineering Task Force H. Zhu
Internet-Draft Huazhong University of Science and Technology
Intended status: Informational 25 February 2025
Expires: 29 August 2025
Architecture for Service Flow Characteristics and Modal Mapping Based on
SDN and ALTO Protocol
draft-xsaopig-nmop-service-flow-modal-mapping-01
Abstract
This Internet-Draft specifies a comprehensive framework for mapping
service flow characteristics to network modal resources in multi-
modal intelligent computing networks. It introduces the use of the
ALTO protocol for collecting service flow data and leverages an SDN
architecture to separate control and data planes. The ALTO protocol
facilitates the acquisition of diverse network state information,
including data from several SDN domains and dynamic network
environments, directly from controllers while keeping the provider's
internal details confidential. It then transmits the controller's
decisions using a proven method. The document details methods for
characteristic identification, intelligent mapping, and continuous
optimization, enabling dynamic resource allocation and improved
network performance. The framework is designed to support scalable,
efficient, and secure operations in environments with complex network
loads and diverse service requirements.
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/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on 29 August 2025.
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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
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
extracted from this document must include Revised BSD License text as
described in Section 4.e of the Trust Legal Provisions and are
provided without warranty as described in the Revised BSD License.
Table of Contents
1. Status of This Memo . . . . . . . . . . . . . . . . . . . . . 3
2. Copyright Notice . . . . . . . . . . . . . . . . . . . . . . 3
3. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
4. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
5. Terms and Definitions . . . . . . . . . . . . . . . . . . . . 4
6. Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . 4
7. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 4
8. Architecture . . . . . . . . . . . . . . . . . . . . . . . . 5
8.1. Infrastructure Layer . . . . . . . . . . . . . . . . . . 6
8.2. Data Collection Layer . . . . . . . . . . . . . . . . . . 7
8.3. Data Processing Layer . . . . . . . . . . . . . . . . . . 7
8.4. Analysis & Optimization Layer . . . . . . . . . . . . . . 7
9. Service Feature-Network Modal Mapping . . . . . . . . . . . . 7
9.1. Service Feature Definition . . . . . . . . . . . . . . . 7
9.2. Modal Definition . . . . . . . . . . . . . . . . . . . . 7
9.3. Mapping Workflow . . . . . . . . . . . . . . . . . . . . 7
10. Security Considerations . . . . . . . . . . . . . . . . . . . 8
11. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
12. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
12.1. Normative References . . . . . . . . . . . . . . . . . . 8
12.2. Informative References . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 9
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Author's Address . . . . . . . . . . . . . . . . . . . . . . . . 9
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1. 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 available at
https://datatracker.ietf.org/drafts/current/. Internet-Drafts are
draft documents valid for a maximum of six months and may be updated,
replaced, or obsoleted by other documents at any time. It is
inappropriate to use Internet-Drafts as reference material or to cite
them other than as "work in progress." This Internet-Draft will
expire on 17 August 2025.
2. 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 Provisions Relating to IETF
Documents (https://trustee.ietf.org/license-info) in effect on the
date of publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
include Revised BSD License text as described in Section 4.e of the
Trust Legal Provisions and are provided without warranty as described
in the Revised BSD License.
3. Introduction
This standard aims to provide a comprehensive and systematic
specification for mapping service flow characteristics to network
modal resources in multi-modal intelligent computing networks. By
introducing the ALTO protocol to collect service flow characteristic
data and adopting an SDN architecture that separates the control
plane from the data plane, this standard supports the creation of
stable and efficient mapping templates between application service
flows and modal resources.
4. Scope
This standard applies to designers, developers, and operators of
multi-modal intelligent computing networks, particularly those
requiring handling of complex network loads, computing resource
demands, and data transmission efficiency in vertical industries. It
defines methods for extracting critical service flow characteristics
from applications and achieving effective mapping to network modal
resources based on these characteristics.
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5. Terms and Definitions
Intelligent Computing: AI-oriented computing capabilities for
training and executing AI models.
Multi-Modal Intelligent Computing Network: A network integrating
multiple modalities to serve diverse application scenarios, with
computing as the core and network as the foundation.
Service Flow: A continuous data transmission process generated by an
application or service, including unidirectional (e.g., client-server
requests) or multi-directional interactions (e.g., video
conferencing).
Service Flow Characteristics: Metrics describing application
behavior, including throughput, latency, packet loss rate, CPU/GPU
utilization, and storage capacity usage across three dimensions:
storage, network forwarding, and computing.
Elastic Perception Feature Vector: A scalable vector representation
dynamically adjusting granularity to characterize multi-dimensional
service flow characteristics for flexible resource allocation.
Network Modality: A specific network type or configuration optimized
for functions such as high bandwidth, low latency, or concurrency.
Modal Resource: Basic units constituting multi-modal networks (e.g.,
computing nodes, switching devices).
Feature-Modal Mapping Mechanism: A technical framework for matching
service flow characteristics with optimal modal resource
combinations.
6. Abbreviations
SDN: Software-Defined Networking
ALTO: Application-Layer Traffic Optimization Protocol
7. Overview
This standard addresses challenges in multi-modal intelligent
computing networks, including dynamic workloads, heterogeneous
service requirements, and frequent resource state changes. Key
objectives:
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1. Characteristic Identification: Use AI algorithms (e.g., graph
matching, reinforcement learning) to analyze service flow
characteristics.
2. Intelligent Mapping: Build an SDN/ALTO-based framework for
dynamic resource allocation.
3. Continuous Optimization: Implement feedback loops to refine
configurations based on real-time monitoring.
8. Architecture
The architecture design refers to[SDN_ALTO_MPTCP]. The architecture
comprises four layers:
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+------------------------+ +-------------------------+
| Data Collection Layer | | Infrastructure |
| +---------------+ | (Polling/Event | +-------------------+ |
| | ALTO Server | | Triggering) | | Computing Network | |
| +---------------+ |<-Monitoring data->| | Resource Nodes | |
| ( Network topology, | | +-------------------+ |
| traffic distribution, | | ( Monitoring/ |
| link delay/bandwidth, | | configuring resources ) |
| resource utilization ) | +-------------------------+
+------------------------+ ^
^ |
| |
+-Service Flow Characteristics-+ +--Configuring policies--+
| |
v v
+-----------------Control Plane ( ALTO Client )-----------------+
| +---------------------------+ +---------------------------+ |
| | Data Processing Layer | | Analysis & Decision Layer | |
| | +-----------------------+ | | +------------------+ | |
| | | Flow Rules generation | | | | Analytical Model | | |
| | +-----------------------+ | | +------------------+ | |
| | | Link management | | | | Decision Module | | |
| | +-----------------------+ | | +------------------+ | |
| +---------------------------+ +---------------------------+ |
+---------------------------------------------------------------+
^
|
+--Flow rules--+
|
v
+-------------Data Plane-----------+
| +------------------------------+ |
| | Infrastructure | |
| | +------------+ | |
| | | SDN switch | | |
| | +------------+ | |
| | ( Forwarding flow rules | |
| | and obtain network status ) | |
| +------------------------------+ |
+----------------------------------+
Figure 1
8.1. Infrastructure Layer
Provides hardware resources (computing nodes, switches) to support
feature extraction and configuration.
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8.2. Data Collection Layer
Collects real-time metrics: network topology, traffic distribution,
link latency, CPU/GPU utilization, and storage I/O. Supports
polling/event-driven mechanisms via SNMP, NetFlow, etc.
8.3. Data Processing Layer
Constructs service feature topology graphs using adjacency matrices.
Nodes represent computing/storage metrics; edges represent network
forwarding metrics. Employs distributed stream processing and graph
databases.
8.4. Analysis & Optimization Layer
Performs deep analysis using graph neural networks and reinforcement
learning to identify optimization strategies (e.g., topology
adjustments, load balancing).
9. Service Feature-Network Modal Mapping
9.1. Service Feature Definition
Defined as three vectors:
* Storage: Node-level metrics (e.g., disk I/O).
* Network Forwarding: Link-level metrics (e.g., latency).
* Compute: Node-level metrics (e.g., CPU utilization).
9.2. Modal Definition
A three-dimensional tensor: {Service Capability, Controllable
Resources, Operational Logic}.
9.3. Mapping Workflow
The mapping workflow consists of:
1. Feature Extraction: Collect real-time metrics across storage,
compute, and network dimensions.
2. Topology Construction: Generate feature graphs with node/edge
attributes.
3. Modal Matching: Align service features with modal resources using
graph-matching algorithms.
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4. Optimization: Adjust configurations (e.g., path rerouting, load
migration).
5. Feedback: Continuously monitor performance and update mapping
rules.
Technical Requirements:
* Use distributed optimization frameworks for real-time
coordination.
* Apply reinforcement learning for adaptive decision-making.
10. Security Considerations
The transmission control model employed in this document relies on
the default security mechanisms provided by SDN and ALTO protocols.
This draft does not alter the default encryption and authentication
models as specified in [RFC7149], [RFC7285], [RFC7286] and [RFC7971].
Therefore, the overall security of the service flow mapping system
depends on the secure configuration and proper deployment of these
underlying protocols.
11. IANA Considerations
This memo includes no request to IANA.
12. References
12.1. Normative References
[RFC7149] Boucadair, M. and C. Jacquenet, "Software-Defined
Networking: A Perspective from within a Service Provider
Environment", RFC 7149, March 2014,
<https://www.rfc-editor.org/info/rfc7149>.
[RFC7285] Alimi, R., Penno, R., Yang, Y., Kiesel, S., Previdi, S.,
Roome, W., Shalunov, S., and R. Woundy, "Application-Layer
Traffic Optimization (ALTO) Protocol", RFC 7285, September
2014, <http://www.rfc-editor.org/info/rfc7285>.
[RFC7286] Kiesel, S., Stiemerling, M., Schwan, N., Scharf, M., and
H. Song, "Application-Layer Traffic Optimization (ALTO)
Server Discovery", RFC 7286, November 2014,
<http://www.rfc-editor.org/info/rfc7286>.
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[RFC7971] Stiemerling, M., Kiesel, S., Scharf, M., Seidel, H., and
S. Previdi, "Application-Layer Traffic Optimization (ALTO)
Deployment Considerations", RFC 7971, October 2016,
<https://www.rfc-editor.org/info/rfc7971>.
12.2. Informative References
[SDN_ALTO_MPTCP]
Xing, Z., Di, X., and H. Qi, "The SDN-based MPTCP-aware
and MPQUIC-aware Transmission Control Model using ALTO",
IEEE ICC 2012, 2024, <https://datatracker.ietf.org/doc/
draft-xing-nmop-sdn-controller-aware-mptcp-mpquic/>.
[SDN_ALTO] Gurbani, V. K., Scharf, M., Lakshman, T. V., Hilt, V., and
E. Marocco, "Abstracting network state in Software Defined
Networks (SDN) for rendezvous services", IEEE ICC 2012,
2012, <https://doi.org/10.1109/ICC.2012.6364858>.
Authors' Addresses
Huanxing Zhu Huazhong University of Science and Technology Wuhan,
China Email: huanxingzhu@hust.edu.cn
Acknowledgements
[REPLACE/DELETE] Optional acknowledgements go here.
Contributors
[REPLACE/DELETE] Optional contributors go here.
Author's Address
Huanxing Zhu
Huazhong University of Science and Technology
Wuhan
China
Email: huanxingzhu@hust.edu.cn
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