Use of ALTO for Determining Service Edge
draft-contreras-alto-service-edge-00

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ALTO WG                                                    LM. Contreras
Internet-Draft                                                Telefonica
Intended status: Informational                                 D. Lachos
Expires: May 7, 2020                                       C. Rothenberg
                                                                 Unicamp
                                                        November 4, 2019

                Use of ALTO for Determining Service Edge
                  draft-contreras-alto-service-edge-00

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 7, 2020.

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   carefully, as they describe your rights and restrictions with respect
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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  . . . . . . . . .   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
   the scale.

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   All the available distributed computing capabilities can complicate
   the decision of what infrastructure use for instantiating a given
   function or application.  Such a decision influences not only the
   resources that are consumed in a given computing environment, but
   also the network capacity of the path that connects such environment
   with the rest of the network from traffic source to destination.

   It is then essential for a network operator to have mechanisms
   assisting on the decision by considering a number of constraints
   related to the function or application to be deployed, but also by
   understanding how a given decision on the computing environment for
   the service edge affects to the transport network substrate.

   This document proposes the usage of ALTO [RFC7285] for assisting with
   such a decision.

2.  Computing needs

   A given network function or application typically shows certain
   requirements in terms of processing capabilities (i.e., CPU), as well
   as volatile memory (i.e., RAM) and storage capacity.

   Cloud computing providers, such as Amazon Web Services or Microsoft
   Azure, typically structure their offerings of computing capabilities
   by bundling CPU, RAM and storage units as quotas, instances or
   flavors that can be consumed in an ephemeral or temporal fashion,
   during the actual lifetime of the required function or application.

   This same approach is being taken nowadays for characterizing bundles
   of resources on the so-called Network Function Virtualization
   Infrastructure (NFVI) Points of Presence (PoPs) being deployed by the
   telco operators.  Specifically, the Common Network Function
   Virtualisation Infrastructure Telecom Taskforce (CNTT) [CNTT],
   jointly hosted by GSMA and the Linux Foundation, is intending to
   harmonize the definition of flavors for abstracting capabilities of
   the underlying NFVI facilitating a more efficient utilization of the
   infrastructure and simplifying the integration and certification of
   functions.

   Focusing on the CNTT ongoing work, the flavors or instances are
   characterized according to a number of characteristics:

   o  Type of instance (T): the types of instances are characterized as
      B (Basic), N (Network Intensive), and C (Compute Intensive).

   o  Interface Option (I): it refers to the interface bandwidth.

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   o  Compute flavor (F): it refers to a certain combination of virtual
      CPU, RAM, disk, and bandwidth for the management interface.

   o  Optional storage extension (S): to request additional storage
      capacity.

   o  Optional hardware acceleration characteristics (A): to request
      specific acceleration capabilities for improving the performance
      of the infrastructure.

   The naming convention of an instance is thus encoded as T.I.F.S.A.

3.  Usage of ALTO for determining where to deploy a function or
    application

   ALTO can assist in the selection of convenient flavors or instances
   of the computing substrate by taking into consideration cost metrics.

   A generic and primary approach is to take into account metrics
   related to the computing environment, such as availability of
   resources, unitary cost of those resources, etc.

   Nevertheless, the function or application to be deployed on top of
   such flavor is interconnected outside the computing environment where
   it is deployed, also requiring to guarantee some transport network
   requirements, such as bandwidth, latency, etc.

   The objective then is to leverage on ALTO provide information about
   the more convenient execution environments to deploy virtualized
   network functions or applications, allowing the operator to get a
   coordinated service edge and transport network recommendation.

3.1.  Compute information in ALTO

   CNTT proposes the existence of an infrastructure profiles catalogue
   collecting the instances available to be consumed.  Such kind of
   catalogue could be communicated to ALTO or even incorporated to it.

   ALTO server queries are required to support T.I.F.S.A encoding in
   order to retrieve proper maps from ALTO.  Additionally, filtered
   queries for particular characteristics of a flavor could also be
   supported.

3.2.  Association of compute capabilities to network topology

   It is required to associate the location of the available instances
   with topological information to allow ALTO construct the overall map.

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   At this stage three potential solutions could be considered:

   o  To leverage on (and possibly
      extend) [I-D.ietf-teas-sf-aware-topo-model] for disseminating
      topology information together with notion of function location
      (that would require to be adapted to the existence of available
      compute capabilities).

   o  To extend BGP-LS [RFC7752], already considered as mechanism for
      feeding topology information in ALTO, to advertise computing
      capabilities as well.

   o  To combine information from the infrastructure profiles catalogue
      with topological information by leveraging on the IP prefixes
      allocated to the gateway providing connectivity to the NFVI PoP.

   The viability of these options will be explored in future versions of
   this document.

3.3.  ALTO architecture for determining serve edge

   The following logical architecture defines the usage of ALTO for
   determining service edges.

                            +--------+   Topological   +---------+
                            |        |   Information   |         |
                            |        |<--------------->| e.g.BGP |
                   ALTO     |        |                 |         |
     +--------+  protocol   |        |                 +---------+
     | Client |<----------->|  ALTO  |
     +--------+             | Server |
                            |        |    Computing    +---------+
                            |        |   Information   |  e.g.,  |
                            |        |<--------------->|  Infra. |
                            |        |                 |Catalogue|
                            +--------+                 +---------+

                Figure 1: Service Edge Information Exchange

4.  Definition of flavors in ALTO property map

   The ALTO unified property extension [DRAFT-PM] generalizes the
   concept of endpoint properties to domains of other entities through
   property maps.  In the context of the CNTT domain, an ALTO property

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   map could be used to expose T.I.F.S.A information of potential
   candidate flavors, i.e., potential NFVI PoPs where an application or
   service can be deployed.

   Table 1 below shows an illustrative example of an ALTO property map
   with property values grouped by flavor name.

   +----------+-----------+-------------+------------------+-----+-----+
   |  Flavor  |  Type of  |  Interface  |  Compute flavor  |  S. |  A. |
   |   Name   |  instance |  Option (I) |  (F) {CPU, RAM,  |     |     |
   |          |    (T)    |             |     disk and     |     |     |
   |          |           |             |    bandwidth}    |     |     |
   +----------+-----------+-------------+------------------+-----+-----+
   | Small-1  |   Basic   |  {1, 2, 3,  | {1,512 MB,1 GB,1 | ... | ... |
   |          |           | 4, 5, 6, 7, |      Gbps}       |     |     |
   |          |           |  8, 9 Gbps} |                  |     |     |
   | Small-2  |  Network  |  {1, 2, 3,  | {1,512 MB,1 GB,1 | ... | ... |
   |          | Intensive | 4, 5, 6, 7, |      Gbps}       |     |     |
   |          |           |  8, 9 Gbps} |                  |     |     |
   | Medium-1 |  Network  |   {25, 50,  | {2,4 GB,40 GB,1  | ... | ... |
   |          | Intensive |   75, 100,  |      Gbps}       |     |     |
   |          |           |   125, 150  |                  |     |     |
   |          |           |    Gbps}    |                  |     |     |
   | Large-1  |  Compute  |  {50, 100,  | {4,8 GB,80 GB,1  | ... | ... |
   |          | Intensive |  150, 200,  |      Gbps}       |     |     |
   |          |           |   250, 300  |                  |     |     |
   |          |           |    Gbps}    |                  |     |     |
   | Large-2  |  Compute  |  {100, 200, |   {8,16 GB,160   | ... | ... |
   |          | Intensive |  300, 400,  |    GB,1 Gbps}    |     |     |
   |          |           |   500, 600  |                  |     |     |
   |          |           |    Gbps}    |                  |     |     |
   |   ...    |    ...    |     ...     |       ...        | ... | ... |
   +----------+-----------+-------------+------------------+-----+-----+

                        Table 1: ALTO Property Map

5.  IANA Considerations

   This document includes no request to IANA.

6.  Security Considerations

   TBD.

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7.  Conclusions

   Telco networks will increasingly contain a number of interconnected
   data centers, of different size and characteristics, allowing
   flexibility in the dynamic deployment of functions and applications
   for advance services.  The overall objective of this document is to
   begin a discussion in the ALTO WG regarding the suitability of the
   ALTO protocol for determining where to deploy a function or
   application in distributed computing environments.  The result of
   such discussions will be reflected in future versions of this draft.

8.  References

8.1.  Normative References

   [RFC7285]  Alimi, R., Ed., Penno, R., Ed., Yang, Y., Ed., Kiesel, S.,
              Previdi, S., Roome, W., Shalunov, S., and R. Woundy,
              "Application-Layer Traffic Optimization (ALTO) Protocol",
              RFC 7285, DOI 10.17487/RFC7285, September 2014,
              <https://www.rfc-editor.org/info/rfc7285>.

   [RFC7752]  Gredler, H., Ed., Medved, J., Previdi, S., Farrel, A., and
              S. Ray, "North-Bound Distribution of Link-State and
              Traffic Engineering (TE) Information Using BGP", RFC 7752,
              DOI 10.17487/RFC7752, March 2016,
              <https://www.rfc-editor.org/info/rfc7752>.

   [RFC8189]  Randriamasy, S., Roome, W., and N. Schwan, "Multi-Cost
              Application-Layer Traffic Optimization (ALTO)", RFC 8189,
              DOI 10.17487/RFC8189, October 2017,
              <https://www.rfc-editor.org/info/rfc8189>.

8.2.  Informative References

   [CNTT]     "Common NFVI for Telco Reference Model, Release 2.0",
              September 2019,
              <https://cntt-n.github.io/CNTT/doc/ref_model/>.

   [DRAFT-PM]
              Roome, W., Randriamasy, S., Yang, Y., Zhang, J., and K.
              Gao, "Unified Properties for the ALTO Protocol", draft-
              ietf-alto-unified-props-new-09 (work in progress),
              September 2019.

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   [I-D.ietf-teas-sf-aware-topo-model]
              Bryskin, I., Liu, X., Lee, Y., Guichard, J., Contreras,
              L., Ceccarelli, D., and J. Tantsura, "SF Aware TE Topology
              YANG Model", draft-ietf-teas-sf-aware-topo-model-03 (work
              in progress), March 2019.

Authors' Addresses

   Luis M. Contreras
   Telefonica
   Ronda de la Comunicacion, s/n
   Madrid  28050
   Spain

   Email: luismiguel.contrerasmurillo@telefonica.com
   URI:   http://lmcontreras.com/

   Danny Alex Lachos Perez
   University of Campinas
   Av. Albert Einstein 400
   Campinas, Sao Paulo  13083-970
   Brazil

   Email: dlachosp@dca.fee.unicamp.br
   URI:   https://intrig.dca.fee.unicamp.br/danny-lachos/

   Christian Esteve Rothenberg
   University of Campinas
   Av. Albert Einstein 400
   Campinas, Sao Paulo  13083-970
   Brazil

   Email: chesteve@dca.fee.unicamp.br
   URI:   https://intrig.dca.fee.unicamp.br/christian/

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