Network Working Group T. Zhou
Internet-Draft Huawei
Intended status: Experimental D. Li
Expires: 21 April 2025 Tsinghua University
X. Geng
Huawei
18 October 2024
Perceptive Routing Information Model
draft-zhou-rtgwg-perceptive-routing-information-00
Abstract
This docuement defines the information model for perceptive routing,
which could serve as a foundational component in the implementation
of perceptive routing.
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].
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Copyright Notice
Copyright (c) 2024 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminologies . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Perceptive Routing General Process . . . . . . . . . . . . . 3
4. Perceptive Routing Information Model . . . . . . . . . . . . 4
4.1. Local information model of PR Sensing Node . . . . . . . 4
4.1.1. Port Failure . . . . . . . . . . . . . . . . . . . . 5
4.1.2. Congestion . . . . . . . . . . . . . . . . . . . . . 5
4.1.3. Queue Length . . . . . . . . . . . . . . . . . . . . 5
4.1.4. Link SLA . . . . . . . . . . . . . . . . . . . . . . 6
4.2. Network information model of PR Sensing Node . . . . . . 6
4.2.1. On Path Information . . . . . . . . . . . . . . . . . 6
4.2.2. Bottleneck Information . . . . . . . . . . . . . . . 6
4.2.3. Topology Information . . . . . . . . . . . . . . . . 7
4.3. Routing decision information model of PR routing node . . 7
4.3.1. Reroute . . . . . . . . . . . . . . . . . . . . . . . 7
4.3.2. Congestion Control . . . . . . . . . . . . . . . . . 7
4.3.3. ECMP (Equal-Cost Multi-Path) Mode . . . . . . . . . . 8
4.3.4. Hierarchical Routing . . . . . . . . . . . . . . . . 8
4.3.5. Service Routing . . . . . . . . . . . . . . . . . . . 8
5. Security Considerations . . . . . . . . . . . . . . . . . . . 9
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 9
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 9
8. Normative References . . . . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
In a lot of scenarios, especailly in DC, adaptive routing has emerged
as a crucial technique for enhancing network performance and
resilience. Traditional routing methods, which rely on static or
pre-defined paths, often struggle to cope with rapidly changing
network conditions, such as link failures, congestion, and varying
traffic demands. Adaptive routing addresses these challenges by
allowing routing decisions to be adjusted in real time, based on the
current state of the network.
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Adaptive routing systems like Perceptive Routing (PR) continuously
monitor network parameters, such as port status, congestion levels,
and link SLAs, to make informed decisions that improve traffic
distribution and fault tolerance. A standardized information model
could abstract the essential properties and relationships within the
system, allowing different implementations to interact seamlessly.
This model offers a common information model for representing the
state of the network, allowing devices to communicate critical
information such as failures, congestion, and optimal paths,
facilitating dynamic and automated decision-making.
This docuement defines the information model for perceptive routing,
which could serve as a foundational component in the implementation
of perceptive routing.
2. Terminologies
PR-SN: Perceptive Routing Sensing Node, percept local and network
information for routing decisions.
PR-RN: Perceptive Routing Routing Node, use multi-dimensional sensory
information to make routing decisions, including reroute, adjust
speed, load balance, etc.
PR-N: Perceptive Routing Notification, the message from PR-SN to PR-
RN.
3. Perceptive Routing General Process
The perceptive routing (PR) mechanism, akin to the adaptive routing
network (ARN), aims to ensure efficient and resilient routing in
dynamic network environments. PR involves real-time monitoring and
decision-making based on multi-dimensional network status
information, which enables the network to adapt to changes, such as
congestion or link failures, with minimal disruption. Here's a
summary of the general process:
1. Detection of Network Status Changes
Perceptive Routing Sensing Nodes (PR-SN) continuously monitor both
local and network-level conditions to detect any anomalies or changes
in network performance, for example congestion or link/node failure.
When such conditions are detected, PR-SN assesses whether they can be
resolved locally or require further action.
2. Impact Assessment and Notification
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If the PR-SN determines that the local measures (e.g., congestion
mitigation strategies) are insufficient to address the problem, it
generates a Perceptive Routing Notification (PR-N). The PR-N message
contains detailed information about the change in network status
(e.g., the type of failure, affected links/nodes, etc.) and is sent
to the Perceptive Routing Routing Node (PR-RN) or other designated
nodes. These messages inform PR-RN about issues that could affect
network performance, allowing them to take proactive steps.
3. Routing Decision and Mitigation
Upon receiving the PR-N message, PR-RN analyzes the specific
information provided to make appropriate routing decisions. This
decisions includes:
* Rerouting: Selecting an alternative path to avoid the impacted
link or node.
* Traffic load adjustment: Rebalancing traffic flows to prevent
further congestion or link overload.
* Congestion control and ECMP: Adjusting traffic flows across
multiple paths if available, using mechanisms like Equal-Cost
Multi-Path (ECMP).
* Hierarchical routing decisions: In cases of large-scale network
changes, PR-RN may use hierarchical routing strategies to route
traffic across different layers of the network efficiently.
By leveraging real-time data provided by PR-SN and using advanced
decision-making algorithms, PR-RN ensures that traffic is rerouted or
adjusted dynamically, reducing latency, avoiding congested paths, and
enhancing overall network efficiency.
The following sections Define a standardized information model for
this general process.
4. Perceptive Routing Information Model
4.1. Local information model of PR Sensing Node
This section focuses on the attributes collected by a Perceptive
Routing (PR) sensing node that monitors and gathers real-time data
about local conditions.
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4.1.1. Port Failure
This type of attribute represents the status of ports on a node.
This attribute indicates whether a port has failed and can no longer
transmit or receive traffic. Monitoring port failures allows the
network to quickly reroute traffic or trigger failover mechanisms.
The possible attributes could include:
* Port Status: Indicates if the port is active, down, or in a failed
state.
* Failure Cause: Specifies reasons for failure, such as hardware
issues, misconfigurations, or timeouts.
4.1.2. Congestion
This type of attribute represents the level of congestion at the
node, typically measured by monitoring packet delay, packet loss, and
throughput. This attribute informs the system of where congestion
points are forming, helping to reroute traffic or apply congestion
control techniques.
The possible attributes could include:
* Traffic Load: Measures current traffic levels on the link
* Congestion Thresholds: Defines limits for congestion states
* Packet Drop Rate: The rate at which packets are dropped due to
congestion
4.1.3. Queue Length
This type of attribute represents the length of queues in the node.
High queue lengths indicate potential bottlenecks and delays, while
short queues suggest fast packet forwarding. This attribute is vital
for assessing node performance and avoiding network congestion.
The possible attributes could include:
* Queue Depth: Real-time data about the number of packets in the
queue.
* Queue Thresholds: Defines situations where the queue has
overflowed, possible leading to packet loss
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4.1.4. Link SLA
This type of attribute represents the Service Level Agreement (SLA)
associated with the link, including metrics like bandwidth, latency,
jitter, and availability. The node monitors whether the link's
performance is within the agreed SLA parameters and flags any
violations for corrective actions.
The possible attributes could include:
* Link Latency: Measures the round-trip delay across the link.
* Bandwidth Utilization: Tracks the percentage of available
bandwidth being used.
4.2. Network information model of PR Sensing Node
This section covers the attributes about network conditions beyond
the local node, providing insights about paths, bottlenecks, and
topology to assist in making routing decisions.
4.2.1. On Path Information
This type of attribute represents detailed information about the
current paths in use for traffic forwarding, including path metrics
such as latency, jitter, and hop count. This attribute allows the
node to assess the quality of the existing paths and their
suitability for ongoing traffic demands.
The possible attributes could include:
* Hop Count: Number of hops the data takes between source and
destination.
* Latency Per Hop: The time it takes to traverse each node.
4.2.2. Bottleneck Information
This type of attribute identifies and describes network bottlenecks
where traffic is delayed or congested. This can include points where
the capacity of a link is exceeded or where high latency is
introduced due to excessive queuing.
The possible attributes could include:
* Link Utilization: Monitors bandwidth use on specific bottleneck
links.
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* Queue Status: Alerts when queues at a bottleneck link are nearing
full capacity.
4.2.3. Topology Information
This type of attribute rsepresents the structure of the network from
the node's perspective. This attribute includes details such as
connected neighbors, available paths, link states, and node status,
providing a global view of the network for optimizing routing
decisions.
The possible attributes could include:
* Neighboring Nodes: A list of adjacent nodes and their statuses.
* Link Metrics: Performance and quality of links connecting nodes in
the topology.
4.3. Routing decision information model of PR routing node
This section covers the key attributes that influence the decision-
making processes within a routing node. These attributes determine
how traffic is routed, how congestion is managed, and how network
resources are allocated.
4.3.1. Reroute
This type of attribute describes the mechanisms and criteria used to
reroute traffic in response to changes in the network, such as link
failures or congestion events. This attribute ensures that traffic
is dynamically redirected to optimal paths.
The possible attributes could include:
* Reroute Path: The alternative path selected during rerouting.
* Failover Time: Time taken to switch to an alternate path.
4.3.2. Congestion Control
This type of attribute details the strategies and protocols used to
manage congestion at the routing node. This attribute includes
techniques like rate-limiting, traffic shaping, or prioritizing
certain flows to alleviate network congestion.
The possible attributes could include:
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* Congestion Avoidance Policies: Mechanisms to prevent congestion
before it occurs.
* Rate Limiting: Controls the traffic rate to avoid overwhelming the
network.
4.3.3. ECMP (Equal-Cost Multi-Path) Mode
This type of attribute refers to Equal-Cost Multi-Path (ECMP)
routing, where multiple paths with equal cost are used to distribute
traffic evenly across the network. This attribute describes how ECMP
is implemented and the criteria for path selection.
The possible attributes could include:
* Hash Algorithm: Determines how ECMP chooses paths.
* Traffic Distribution: Shows how traffic is split across multiple
paths.
4.3.4. Hierarchical Routing
This type of attribute covers the use of hierarchical routing
techniques to manage larger networks efficiently. This attribute
provides information about how the network is divided into tiers or
areas, with routing decisions optimized within each layer.
The possible attributes could include:
* Routing Layers: Defines the layers of routing, such as access,
aggregation, and core.
* Aggregated Traffic Metrics: Summarizes traffic data for groups of
lower-layer nodes.
4.3.5. Service Routing
This type of attribute describes how the routing node handles
service-specific routing requirements, such as directing traffic
based on application needs (e.g., video streaming, voice, or data).
This attribute ensures that service-level routing objectives are met,
such as prioritizing latency-sensitive traffic.
The possible attributes could include:
* Service Path: The path chosen for traffic according to a specific
service type.
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* Service-Specific SLAs: Monitors SLA adherence based on service-
level routing.
5. Security Considerations
6. IANA Considerations
This document makes no request of IANA.
Note to RFC Editor: this section may be removed on publication as an
RFC.
7. Acknowledgements
8. 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>.
Authors' Addresses
Tianran Zhou
Huawei
Email: zhoutianran@huawei.com
Dan Li
Tsinghua University
Email: tolidan@tsinghua.edu.cn
Xuesong Geng
Huawei
Email: gengxuesong@huawei.com
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