Use of ALTO for Determining Service Edge
draft-contreras-alto-service-edge-02
ALTO WG LM. Contreras
Internet-Draft Telefonica
Intended status: Informational D. Lachos
Expires: May 6, 2021 C. Rothenberg
Unicamp
November 2, 2020
Use of ALTO for Determining Service Edge
draft-contreras-alto-service-edge-02
Abstract
Service providers are starting to deploy and interconnect computing
capabilities across the network for hosting network functions and
applications. In distributed computing environments, both computing
and topological information are necessary in order to determine the
more convenient infrastructure where to deploy such a service or
application. This document raises an initial approach towards the
use of ALTO to provide such information and assist in the selection
of proper execution environments.
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This Internet-Draft will expire on May 6, 2021.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Computing needs . . . . . . . . . . . . . . . . . . . . . . . 3
3. Usage of ALTO for determining where to deploy a function or
application . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.1. Compute information in ALTO . . . . . . . . . . . . . . . 4
3.2. Association of compute capabilities to network topology . 4
3.3. ALTO architecture for determining serve edge . . . . . . 5
4. Definition of flavors in ALTO property map . . . . . . . . . 6
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 6
6. Security Considerations . . . . . . . . . . . . . . . . . . . 7
7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . 7
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 7
8.1. Normative References . . . . . . . . . . . . . . . . . . 7
8.2. Informative References . . . . . . . . . . . . . . . . . 7
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 8
1. Introduction
The advent of virtualization is enabling the operators with a dynamic
instantiation of network functions and applications by using
different techniques on top of commoditized computation
infrastructures, permitting a flexible and on-demand deployment of
services, aligned with the actual needs observed as demanded by the
customers.
Operators are starting to deploy distributed computing environments
in different parts of the network with the objective of addressing
the different service needs in terms of latency, bandwidth,
processing capabilities, etc. This is translated in the emergence of
a number of data centers of different sizes (e.g., large, medium,
small) characterized by distinct dimension of CPUs, memory and
storage capabilities, as well as bandwidth capacity for forwarding
the traffic generated in and out the corresponding data center.
The probable future situation, with the generalization and
proliferation of the edge computing approach, will increase the
potential footprint where a function or application can be deployed.
These different dimensioning rules result in a different unitary cost
per CPU, memory, and storage in each computing environment because of
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