Use of ALTO for Determining Service Edge
draft-contreras-alto-service-edge-01

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ALTO WG                                                    LM. Contreras
Internet-Draft                                                Telefonica
Intended status: Informational                                 D. Lachos
Expires: January 14, 2021                                  C. Rothenberg
                                                                 Unicamp
                                                           July 13, 2020

                Use of ALTO for Determining Service Edge
                  draft-contreras-alto-service-edge-01

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.

Status of This Memo

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   This Internet-Draft will expire on January 14, 2021.

Copyright Notice

   Copyright (c) 2020 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
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   (https://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents

Contreras, et al.       Expires January 14, 2021                [Page 1]
Internet-Draft      ALTO for Determining Service Edge          July 2020

   carefully, as they describe your rights and restrictions with respect
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   described in the Simplified BSD License.

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  . . . . . . . . .   5
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   6
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .   6
   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