[ippm] Need your feedback on the proposed IP Layer Metrics to enable the IP networks to dynamically optimize the forwarding of 5G edge computing service without requiring any information from Applications themselves.

Linda Dunbar <linda.dunbar@futurewei.com> Wed, 28 October 2020 17:35 UTC

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From: Linda Dunbar <linda.dunbar@futurewei.com>
To: "ippm@ietf.org" <ippm@ietf.org>
Thread-Topic: Need your feedback on the proposed IP Layer Metrics to enable the IP networks to dynamically optimize the forwarding of 5G edge computing service without requiring any information from Applications themselves.
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Date: Wed, 28 Oct 2020 17:35:46 +0000
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Subject: [ippm] Need your feedback on the proposed IP Layer Metrics to enable the IP networks to dynamically optimize the forwarding of 5G edge computing service without requiring any information from Applications themselves.
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IPPM experts:


https://datatracker.ietf.org/doc/draft-dunbar-ippm-5g-edge-compute-ip-layer-metrics/ describes the IP Layer metrics and methods to measure the Edge Computing Servers running status and environment for IP networks to select the optimal Edge Computing server location in 5G Edge Computing (EC) environment. This document also describes the method of incorporating those measurements with IP routing cost to come up with a more optimal criteria in selecting ANYCAST locations.

There are many network techniques and protocols to optimize forwarding and ensuring QoS for applications, such as DSCP/DiffServ, Traffic Engineered (TE) solutions, Segment Routing, etc. But the reality is that most application servers don't expose their internal logics to network operators. Their communications are generally encrypted. Most of them do not even respond to PING or ICMP messages initiated by routers or network gears.
The proposed IP Layer Metrics and algorithms enable the  IP networks to dynamically optimize the forwarding of 5G edge computing service without any knowledge above IP layer.
In a way, the proposed IP Layer Metrics and algorithm enable the IP networks  to be more aware of Application behavior without dependency on getting information from  Applications themselves.

In a nutshell, the draft proposed an algorithm to compute the Load Measurement Index at each location of the App Server, the method to derive Capacity Index of each location, and the Site preference. The draft also proposes an algorithm for ingress node to choose the ANYCAST location based on Load Measurement, The Capacity Index, the site preference Index and network delay.

We greatly appreciate your feedback on those proposed IP Layer metrics.

A little bit background:
In 5G Edge Computing environment, one Application can have multiple Application Servers hosted in different Edge Computing data centers that are close in proximity. Those Edge Computing (mini) data centers are usually very close to, or co-located with, 5G base stations, with the goal to minimize latency and optimize the user experience.

Increasingly, Anycast is used by various application providers and CDNs because it is possible to dynamically load balance across multiple locations of the same address based on network conditions.  Application Server location selection using Anycast address leverages the proximity information present in the network (routing) layer and eliminates the single point of failure and bottleneck at the DNS resolvers and application layer load balancers. Another benefit of using ANYCAST address is removing the dependency on UEs that use their cached IP addresses instead of querying DNS when they move to a new location.

But selection of an ANYCAST location purely based on the network condition can encounter issue of the location selected by IP routing information being overutilized while there are available underutilized locations close by.
That is why we propose those IP Layer metrics to better optimize the forwarding for 5G Edge Computing services.

Thank you very much
Linda Dunbar