Dear Brian,
Thank you very much for taking the time to review our draft and for
confirming the correctness of the GRASP objective definition. As the
author of GRASP, your feedback is extremely valuable to us.
We really appreciate your suggestion about using the graspy
demonstration implementation. We have already started looking into
it, and we plan to build an FPM ASA (Failover Path Manager
Autonomic Service Agent) prototype using graspy to simulate the
GRASP negotiation procedures described in Section 5.1 of our draft
— specifically, the M_DISCOVERY, M_REQ_NEG, and M_END exchange
sequence for distributing node-protection-info to path nodes.
While studying the graspy codebase — particularly the graspi.py API
wrapper and the existing ASA examples such as Briggs.py and Gray.py
— we noticed that the current examples mainly demonstrate the flood
and synchronize mechanisms. Our use case relies more heavily on the
request_negotiate / negotiate_step pattern for targeted, per-node
protection information distribution. We believe this could serve as
a useful additional example of GRASP negotiation in practice.
We do have a couple of questions where your guidance would be
particularly helpful:
1. In our design, the Path Initiator needs to distribute different
node-protection-info to each node along the primary path
(each
node receives its own role, upstream/downstream neighbors,
and
backup path if applicable). We are using individual GRASP
negotiation sessions for this. Would you consider this the
idiomatic way to use GRASP for such per-node configuration,
or
would you suggest an alternative approach such as using flood
with filtering?
2. For the SRv6 operational details — the bounce-back strategy is
essentially a data plane fast reroute mechanism that works in
two phases: (a) in-flight packets are bounced upstream to the
nearest Anchor node upon failure detection, and (b) the
Anchor
node re-encapsulates them onto a pre-computed backup SRv6
path.
GRASP is only used during the setup phase to distribute the
protection state, not during the actual failover. We would be
happy to provide a more detailed explanation of the SRv6
aspects
if that would be helpful.
We will share our graspy-based simulation results once the prototype
is ready. Thank you again for your encouragement and the excellent
graspy tool.
Best regards,
Lintong Du
(on behalf of all co-authors)
Beijing University of Posts and Telecommunications
杜林潼
北京邮电大学/研博生/计算机学院（国家示范性软件学院）
北京
------------------ Original ------------------
From: "Brian E Carpenter";
Date: 2026年3月7日(星期六) 上午6:32
To: "Anima WG"; "draft-du-anima-srv6-failover-grasp";
Subject: Re: I-D Action: draft-du-anima-srv6-failover-grasp-00.txt
Hi,
I had a quick look at this draft and so far its definition of a GRASP objective
looks correct to me. I don't understand SRV6 operations well enough to comment
on the details of the use case.
I'll just remind the authors that they could simulate the use case using the
demonstration implementation of of GRASP, open source at
https://github.com/becarpenter/graspy/
Regards/Ngā mihi
Brian Carpenter
On 02-Mar-26 03:21, [email protected] wrote:
> Internet-Draft draft-du-anima-srv6-failover-grasp-00.txt is now available.
>
> Title: Autonomic SRv6 Network Fast
Failover Using Bounce-back Strategy with GRASP
> Authors: Lintong Du
>
Xiangyang Gong
>
Xirong Que
>
Fang Deng
> Name:
draft-du-anima-srv6-failover-grasp-00.txt
> Pages: 15
> Dates: 2026-03-01
>
> Abstract:
>
> This document specifies an autonomic fast failover
mechanism for SRv6
> networks using a bounce-back strategy. It
uses GRASP to distribute
> failover protection information, enabling data
plane fast reroute
> without control plane reconvergence.
>
> The IETF datatracker status page for this Internet-Draft is:
> https://datatracker.ietf.org/doc/draft-du-anima-srv6-failover-grasp/
>
> There is also an HTML version available at:
> https://www.ietf.org/archive/id/draft-du-anima-srv6-failover-grasp-00.html
>
> Internet-Drafts are also available by rsync at:
> rsync.ietf.org::internet-drafts
>
>
> _______________________________________________
> I-D-Announce mailing list -- [email protected]
> To unsubscribe send an email to [email protected]
_______________________________________________
Anima mailing list -- [email protected]
To unsubscribe send an email to [email protected]
