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Versions: 00 01 02 03 04 05 06 draft-ietf-alto-cost-calendar

Network Working Group                                S. Randriamasy, Ed.
Internet-Draft                                  Alcatel-Lucent Bell Labs
Intended status: Standards Track                                 R. Yang
Expires: September 10, 2015                              Yale University
                                                                   Q. Wu
                                                                  Huawei
                                                                 L. Deng
                                                            China Mobile
                                                               N. Schwan
                                                      Thales Deutschland
                                                           March 9, 2015


                           ALTO Cost Calendar
                draft-randriamasy-alto-cost-calendar-03

Abstract

   The goal of Application-Layer Traffic Optimization (ALTO) is to
   bridge the gap between network and applications by provisioning
   network related information in order to allow applications to make
   informed decisions.  The present draft proposes to extend the cost
   information provided by the ALTO protocol.  The purpose is to broaden
   the decision possibilities of applications to not only decide 'where'
   to connect to, but also 'when'.  This is useful to applications that
   have a degree of freedom on when to schedule data transfers, such as
   non- instantaneous data replication between data centers or service
   provisioning to end systems with irregular connectivity.  ALTO
   guidance to schedule application traffic can also efficiently help
   for load balancing and resources efficiency.

   The draft proposes a new cost Mode called "Calendar" Mode, that is
   applicable to time-sensitive ALTO metrics and allows Applications to
   carefully schedule their connections or data transfers.  In the
   Calendar Mode, an ALTO Server exposes ALTO Cost Values in JSON arrays
   where each value corresponds to a given time interval.  The time
   intervals as well as other Calendar attributes are specified in the
   IRD.  Besides the functional time-shift enhancement the ALTO Cost
   Calendar also allows to schedule the ALTO requests themselves and
   thus save a number of ALTO transactions.

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].





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Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
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   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
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   This Internet-Draft will expire on September 10, 2015.

Copyright Notice

   Copyright (c) 2015 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
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Motivating Use cases for ALTO Cost Schedule . . . . . . . . .   5
     2.1.  Bulk Data Transfer scheduling . . . . . . . . . . . . . .   5
     2.2.  Endsystems with limited connectivity or access to
           datacenters . . . . . . . . . . . . . . . . . . . . . . .   6
     2.3.  SDN Controller guided access to application endpoints . .   7
     2.4.  Large flow scheduling on extended ALTO topologies . . . .   8
     2.5.  Time-sensitve TE metrics Calendaring  . . . . . . . . . .  10
   3.  Design considerations for an ALTO calendar  . . . . . . . . .  11
     3.1.  Purpose of an ALTO calendar . . . . . . . . . . . . . . .  11
     3.2.  Design requirements for an ALTO calendar  . . . . . . . .  12
   4.  ALTO extensions for a Cost Calendar . . . . . . . . . . . . .  13
     4.1.  ALTO Cost-Mode: Calendar  . . . . . . . . . . . . . . . .  14
     4.2.  ALTO Calendar attributes in the IRD . . . . . . . . . . .  14



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     4.3.  Example of calendared information resources in the IRD  .  15
       4.3.1.  Example IRD with ALTO cost Calendars  . . . . . . . .  16
     4.4.  ALTO Calendar information in ALTO responses . . . . . . .  19
       4.4.1.  Example transaction for a routingcost Calendar  to
               face intermittent connectivity  . . . . . . . . . . .  20
       4.4.2.  Example transaction for a bandwidth calendar  . . . .  22
   5.  Use cases for ALTO Cost Schedule  . . . . . . . . . . . . . .  23
     5.1.  Bulk Data Transfer scheduling . . . . . . . . . . . . . .  24
     5.2.  Endsystems with limited connectivity or access to
           datacenters . . . . . . . . . . . . . . . . . . . . . . .  25
     5.3.  SDN Controller guided access to application endpoints . .  26
     5.4.  Large flow scheduling on extended ALTO topologies . . . .  27
     5.5.  Time-sensitve TE metrics Calendaring  . . . . . . . . . .  28
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  29
     6.1.  Information for IANA on proposed Cost Types . . . . . . .  30
     6.2.  Information for IANA on proposed Endpoint Propeeries  . .  30
   7.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  30
   8.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  30
     8.1.  Normative References  . . . . . . . . . . . . . . . . . .  30
     8.2.  Informative References  . . . . . . . . . . . . . . . . .  30
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  31

1.  Introduction

   IETF is currently standardizing the ALTO protocol which aims for
   providing guidance to overlay applications, that need to select one
   or several hosts from a set of candidates that are able to provide a
   desired resource.  This guidance is based on parameters that affect
   performance and efficiency of the data transmission between the
   hosts, e.g., the topological distance.  The goal of ALTO is to
   improve the Quality of Experience (QoE) in the application while
   simultaneously optimizing resource usage in the underlying network
   infrastructure.

   The ALTO protocol therefore [RFC7285] specifies a Network Map, which
   defines groupings of endpoints in a network region (called a PID) as
   seen by the ALTO server.  The Endpoint Cost Service and the Endpoint
   (EP) Ranking Service then provide rankings for connections between
   the specified network regions and thus incentives for application
   clients to connect to ISP preferred endpoints, e.g. to reduce costs
   imposed to the network provider.  Thereby ALTO intentionally avoids
   the provisioning of realtime information as explained in the ALTO
   Problem Statement [RFC5693] and ALTO Requirements [RFC5693]) drafts
   that write "Such information is better suited to be transferred
   through an in-band technique at the transport layer instead".  Thus
   the current Cost Map and Endpoint Cost Service are providing, for a
   given Cost Type, exactly one rating per link between two PIDs or to
   an Endpoint.  Applications are expected to query one of these two



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   services in order to retrieve the currently valid cost values.  They
   therefore need to plan their ALTO information requests according to
   the estimated frequency of cost value change.

   Since network costs can fluctuate, due to diurnal patterns of traffic
   demand andor network maintenance, an ALTO client should interpret the
   returned costs as those at the query moment.  Providing network costs
   for only the current time, however, may not be sufficient, in
   particular, for applications that can schedule their traffic in a
   span of time, for example, by deferring backup to night during
   traffic trough.

   In case these value changes are predicable over a certain period of
   time and the application does not require immediate data transfer, it
   would save time to get the whole set of cost values over the period
   in one ALTO response and using these values to schedule data
   transfers would allow to optimise the network resources usage and
   QoE.

   In this draft we introduce use cases that describe applications that
   have a degree of freedom on scheduling data transfers over a period
   of time, thus they do not need to start a transfer instantaneously on
   a retrieved request.  For this kind of applications we propose to
   extend the Cost Map and Endpoint Cost Services by adding a calendar
   on the cost values, allowing applications to time-shift data
   transfers.

   This document extends RFC7285 to allow an ALTO server to provide
   network costs for a given duration of time.  A sequence of network
   costs across a time span for a given pair of network locations is
   referred to as an ALTO cost calendar for the pair of network
   locations.  In addition to this functional ALTO enhancement, we
   expect to further gain by gathering multiple Cost Values for one cost
   type as firstly one Cost Map reporting on N Cost Values is less bulky
   than N Cost Maps containing one Cost value each and secondly, this
   reduces N ALTO transactions to a single one.  This is valuable for
   both the storage of these ALTO maps and their transfer.  Similar
   gains can be obtained for the ALTO Endpoint Cost Service.

   In this draft an "ALTO Calendar" is presented as a Cost Mode that is
   applicable to time-sensitive ALTO metrics and allows applications
   using such metrics to carefully schedule their connections or data
   transfers.  In the Calendar Mode, an ALTO Server exposes ALTO Cost
   Values in JSON arrays where each value corresponds to a given time
   interval.  The time intervals as well as other Calendar attributes
   (the ones suggested by Richard) are specified in the IRD and allow
   the ALTO Client to interpret the received ALTO values.  This draft
   proposes a set of Calendar attributes to be added to the IRD, for



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   discussion in the ALTO WG.  In order to support the calendaring of
   Cost values represented in Modes such as 'string' this draft also
   proposes one option, which is to extend the Cost Mode to a
   combination of several indicators, such as 'string' and 'calendar'.

   The remainder of this draft first provides a variety of use cases
   that motivate the need for a 'calendar' cost mode.  It then specifies
   the needed extensions to the ALTO protocol and details some example
   messages.

2.  Motivating Use cases for ALTO Cost Schedule

   This section introduces use cases showing the benefits of providing
   ALTO Cost values in 'calendar' mode.  Most likely, the ALTO Cost
   Calendar would be used for the Endpoint Cost Service, assuming that a
   limited set of feasible Endpoints for a non-real time application is
   already identified, that they do not need to be accessed immediately
   and that their access can be scheduled within a given time period.
   The Cost Map service, filtered or not, is also applicable as long as
   the size of the Map is manageable.

   Last, the ALTO Cost calendar is beneficial to optimizing ALTO
   transactions themselves.  Indeed, let us assume that an Application
   Client is located in an end sytem with limited resources and/or has
   an access to the network that is either intermittent or provides an
   acceptable QoE in limited but predictable time periods.  In that
   case, it needs to both schedule its resources demanding networking
   activities and its ALTO requests.  Instead of having to figure out
   when the cost values may change and having to carefully schedule
   multiple ALTO requests, it could aviod this by relying on Cost
   Shedule attributes that indicate the time granularity, the validity
   and time scope of the cost information, together with the time
   related cost values themselves.

2.1.  Bulk Data Transfer scheduling

   Large Internet Content Providers (ICPs) like Facebook or YouTube, as
   well as CDNs rely on data replication across multiple sites to
   offload the core site and increase user experience through shorter
   latency from a local site.  Typically the usage pattern of these data
   centers or caches follows a location dependent diurnal pattern.

   In the examples above, data needs to be replicated across the various
   locations of a Internet Content Provider (ICP), leading to bulk data
   transfers between datacenters on a diurnal pattern.

   In the mean time, there is a degree of freedom on when the content is
   transmitted from the origin server to the caching node, or from the



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   core site to a local site.  However, scheduling these data transfers
   is a non-trivial task as the transfer should not infer with the user
   peak demand to avoid degradation of user experience and to decrease
   billing costs for the datacenter operator by leveraging off-peak
   hours for the transfer.  This peak demand typically follows a diurnal
   pattern according to the geographic region of the datacenter.

   As a result, it would be very helpful to let these ICPs to have a
   good knowledge about the link utilization patterns between the
   different datacenters from the networks before making a more
   intelligent scheduling decision.  While this usage data today already
   is gathered and also used for the scheduling of data transfer,
   provisioning this data gets increasingly complex with the number of
   CDN nodes and in particular the number of datacenter operators that
   are involved.  For example, privacy concerns prevent that this kind
   of data is shared across administrative domains.  The ALTO Cost
   Calendar specified later in this document avoids this problem by
   presenting an abstracted view of time sensitive utilization maps
   through a dedicated ALTO service to allow ICPs a coherent scheduling
   of such data transfers across administrative domains.

2.2.  Endsystems with limited connectivity or access to datacenters

   Another use case that benefits from the availability of multi-
   timeframe cost information is based on applications that are limited
   by their connectivity either in time or resources or both.  For
   example applications running on devices in remote locations or in
   developing countries that need to synchronize their state with a data
   center periodically, in particular if sometimes there is no
   connection at all.  Example applications is enterprise database
   update, remote learning, remote computation distributed on several
   data center endpoints.

   Wireless connections have a variable quality and may even be
   intermittent.  On the other hand, the wireless network conditions are
   often predicable and have a rapid impact on applications.  Non real
   time applications and time-insensitive data transfers such as client
   patching, archive syncing, etc. can benefit from careful scheduling.
   It is thus desirable to provide ALTO clients with routing costs to
   connection nodes (i.e.  Application Endpoints) over different time
   periods.  This would allow end systems using ALTO aware application
   clients to schedule their connections to application endpoints.

   Another challenge arises with end systems using resources located in
   datacenters and trading content and resources scattered around the
   world.  For non-real time applications, the interaction with
   Endpoints can be scheduled at the time slots corresponding to the
   best possible network conditions in order to improve the QoE.  For



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   instance, resource Ra downloaded from Endpoint EPa at time t1,
   Resource Rb uploaded to EPb at time t2, some batch computation
   involving Ra and Rb done on EPc at time t3 and results R(A,B)
   downloaded to EPd and EPe at time t4.  Example applications are
   similar to the ones cited in the previous paragraph.

     +-----+                                           +-----+
     | EPa |                                           | EPb | <----- Rb
     +-----+                                           +-----+   (t2=50)
        |                   +-------+                     |
        Ra -------------->  | EPc   |                     |
        (time t1=10)        |       |                     |
                            |t3=100 |  <----------------- Rb
                            +-------+
                                | \
                                |  \
                              R(Ra,Rb)
                             (t4=200)
                                |     \
                                |      -------------------.
                                V                         V
                             +-----+                   +-----+
                             | EPd |                   | EPe |
                             +-----+                   +-----+



2.3.  SDN Controller guided access to application endpoints

   The Software Defined Networking (SDN), see [sdnrg], is a model that
   attempts to manage and reconfigure networks in a more flexible way in
   order to better cope with the traffic challenges posed by nowadays
   resources greedy applications.  To this end, one option is "moving
   the control plane out of the network elements into "controllers", see
   [SDN charter, http://www.1-4-5.net/~dmm/sdnrg/sdnrg.html], that
   implements the network control and management.  The SDN Controllers
   are deemed to gather the network state information and provide it in
   an abstracted form to SDN aware applications while gathering their
   requirements in QoE and exchanging other application "management"
   information and commands.

   The relevance of ALTO to perform a number of SDN functions has been
   recently highlighted.  An ALTO Server can assist an SDN Controller by
   hosting abstracted network information that can be provided to SDN
   aware applications via an ALTO Client.  It can also assist other SDN
   Control operations using information in and outside the ALTO scope.





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   The SDN primitive "Get network resources" provides applications with
   informations allowing them to evaluate the expected QoE.  QoE related
   information includes delay and bandwidth at the application endpoints
   as well as on the network paths.  Such information may be provided
   via the ALTO Service by proposed extensions of the ALTO protocol that
   define new ALTO Cost Types allowing to abstract and report QoE to
   applications.

   One key objective of an SDN controller is the ability to balance the
   application traffic whenever possible.  For non real time
   applications, data and resources transfer can be time shifted,
   resources availability may often be predicable and last, strong
   incentives for applications to time shift their traffic may be given
   by network operators appropriately setting routing cost values at
   different time values, according to their policy to cope with network
   occupation over time.

   To achieve this objective, the SDN controller can:

   1.  get the network state history from its controlled network
       elements through its southbound API

   2.  possibly derive an estimation or a prediction of these values
       over given time frames

   3.  compute estimates and/or network provider preferences on end to
       end paths and store their abstraction in an ALTO Server in the
       form of ALTO Cost Calendar values defined for different time
       periods

   4.  deliver these values to the SDN applications via the ALTO
       Endpoint Cost Service, as estimations covering the past and/or
       the future and/or preferences.

   This way:

   o  On one hand, the applications get the best possible QoE, as they
      can pick the best time for them to access one or more Endpoints,

   o  One the other hand the SDN controller achieves load balancing as
      it may guide the application traffic so as to better distribute
      the traffic over time, and thus optimize its resources usage.

2.4.  Large flow scheduling on extended ALTO topologies

   [draft-yang-alto-topology-00] presents initial thinking on extending
   ALTO for topology exposure services, that would provide flexible
   abstractions based on the raw network topology.  Among other



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   features, an ALTO topology may expose several paths between a source
   (src) and destination (dst), or topology details may be provided on
   restricted parts.  This work was presented to the ALTO WG at IETF88.

   The presentation slides [slides-88-alto-5-topology] on
   [draft-yang-alto-topology-00] expose a use case entitled "Large Flow
   Scheduling".  This case includes a "daylife example" where a Google
   Map service proposes multiple routes between 2 points A and B, each
   calculated w.r.t. length and estimated time.  For each of these
   selected paths, the map service exposes a time-sensitive qualitative
   value taking 4 values between Slow and Fast.  A user of this
   application may thus organize its transfer w.r.t. metrics, paths and
   time, provided s/he does not have to commute immediately.

   The use case on Large flow scheduling on extended ALTO topologies in
   the present section illustrates one modality of ALTO topology
   service, that would expose several paths between end to end (src,
   dst) pairs, computed w.r.t. one of more metrics, possibly under given
   constraints.  On top of this enriched topology service, non real-time
   applications may also choose the time of data/resources transfer,
   taking thus advantage of a richer set of decision variables.

   The use case "Large Flow Scheduling" of presentation
   [slides-88-alto-5-topology]can thus be adapted as follows:

   o  Step1 - obtain the set T transfer tasks {(src, dest, data)}

   o  Step2 - identify one or more paths for each (src, dst): several
      information sources exist among which:

      *  (a) ALTO CostMap with a "path" metric, // not specified here

      *  (b) an ALTO Topology Service providing a path computation hint
         (e.g. w.r.t. routingcost and/or other metrics)

   o  Step 3 - while T not empty:

      *  1 - query for example values for some metric 'available
         bandwidth' on paths:

         +  to this end, query the values in the ALTO 'calendar' Mode:
            on the selected (src, dst) for a set of time intervals.
            With this mode, the ALTO client will receive an array of
            values, each applicable to a time slot .

      *  2 - schedule data transfer at the time slots corresponding to
         the preferred value.




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2.5.  Time-sensitve TE metrics Calendaring

   Draft [draft-wu-alto-te-metrics] , proposes to extend the set of ALTO
   metrics with 11 ALTO traffic engineering (TE) metrics to reflect
   measurement on network delay, jitter, packet loss, hop count, and
   bandwidth.  ALTO TE metrics that are time-sensitive, either by nature
   such as bandwidth and delay related metrics, or due to "normally"
   changing network conditions or both.

   The values of ALTO TE metrics are typically collected from routing
   protocols and provided in a non-real time manner.  In "normally"
   changing network conditions, TE metric values remain uniformly
   distributed over given time intervals and can be aggregated over
   bigger time intervals of periodic patterns.  For example, an ALTO
   Server may collect values for e.g. delay from a routing protocol
   produced by measurements done every second over a measurement period
   of 30 seconds.  The ALTO Server may then aggregate these values over
   two measurement periods (i.e. 60 seconds) and repeat the operation as
   it wishes.  Then every hour, the ALTO Server provides these delay
   values in 'calendar' mode, encoded as an array of 60 values, assumed
   to estimate network performance statistics on each minute of this
   hour.

   Another example is Bandwidth Calendaring.  Bandwidth Calendaring
   allows network operators to reserve resources in advance according to
   agreements with their customers, enabling them to transmit data with
   specified starting time and duration, for example, for a scheduled
   bulk data replication between data centers.  Traditionally, this can
   be supported by a Network Management System operation such as path
   pre-establishment and activation on the agreed starting time.
   However, this does not provide efficient network usage since the
   established paths exclude the possibility of being used by other
   services even when they are not used for undertaking any service.

   A Cost calendar provided by an ALTO server can support the scheduled
   bulk data replication application with better efficiency since it can
   alleviate the burden of processing on network elements.  This
   requires the ALTO server to maintain the calendared TE cost metrics
   on the end to end paths associated to data transfer.

   To support cost calendaring for these time-sensitive ALTO TE metrics,
   the network topology and the dynamicity of the traffic need to be
   considered.  For example, a small topology with low density and low
   capacity that carries inpredictable, heavy and bursty traffic has few
   chances to exhibit stationary TE metric value patterns over large
   periods and would benefit to use the ALTO Calendar over smaller time
   slots.  Some ALTO TE metric values, even aggregated over time may
   need to be updated at a frequency that would require doing ALTO



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   request at a pace that would be overload both the ALTO Client and the
   Server.

3.  Design considerations for an ALTO calendar

   This section enumerates a set of challenges in designing the
   calendaring specifications, and will be updated upon discussions in
   the ALTO WG.

   An ALTO Cost calendar provided by the ALTO Server is an array of
   values for a given metric, where each value corresponds to a time
   interval which length is specified for this metric in the IRD,
   together with other attributes describing the time scope of the
   calendar.  Most likely, the ALTO Cost Calendar would be used for the
   Endpoint Cost Service, assuming that a limited set of feasible
   Endpoints for a non-real time application is already identified, that
   they do not need to be accessed immediately and that their access can
   be scheduled within a given time period.  The Cost Map service,
   filtered or not, is also applicable as long as the size of the Map is
   manageable.

   Given a cost calendar (i.e., a sequence of cost values such as [1, 2,
   3, 4]), an ALTO client needs meta information to interpret the values
   (Q1) Which network metric (e.g., routingcost, or latency) do the
   numbers represent (Q2) Are the values absolute values or relative
   ranking order or strings ? (i.e., numerical or ordinal or strings)
   and (Q3) What is the time associated with each value ? RFC7285
   defines CostType, which consists of two fields named cost-metric and
   cost-mode, to provide information for Q1 and Q2.  A design issue in
   providing ALTO cost calendar is to provide information for Q3.

3.1.  Purpose of an ALTO calendar

   A calendar is used to schedule transfers of application data or
   services and has several characteristics:

   o  the Calendar values are assumed to be stationary on each time
      interval,

   o  the ALTO Server may provide values on past time periods that can
      be interpreted as historical experience and used to anticipate
      future cost values,

   o  the ALTO Server may provide stationary values on present or future
      time periods that can be interpreted as predictions on cost
      values,





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   o  the ALTO Server may provide stationary values on time intervals
      covering the past, and/or present and/or future.

   o  for metrics provided with units and claiming to be aggregated from
      network measurements, the values can be interpreted as
      estimations.

   o  For abstracted metrics provided with no units such as the
      'routingcost' defined in the base ALTO protocol or abstracted
      unitless scores on network performances such as some potential
      'bandwidth score' or 'unreliability cost', the values can be
      interpreted as network provider preferences.

   Note that we distinguish between "estimates" that we see as value
   aggregations represented with units such as bytes, seconds,
   percentage and "preferences" that we see as abstracted costs or
   scores w.r.t. a metric or state such as 'routingcost',
   'bandwidthscore', 'link quality'.

   The method used to generate the estimation and aggregation of
   measured values is currently outside the scope of this draft and
   expected to be documented in the applicable metric definition
   document.

3.2.  Design requirements for an ALTO calendar

   TO BE COMPLETED IN FURTHER DRAFT VERSIONS

   An ALTO Calendar can be seen as a cyclic value array pattern that is
   valid for a certain time period with specified beginning date,
   duration and number of time intervals.

   o  needs to convey cyclic network provider preferences expressed
      w.r.t. given ALTO metric values (e.g., hourly, daily, weekly
      measurement/prediction)

   o  needs to convey cyclic network status if the ALTO Server claims to
      provide aggregated information on network status (e.g., hourly,
      daily, weekly measurement/prediction)

   o  needs to be able to convey the result of a particular instance of
      time (e.g., to convey predicted network status during a
      maintenance outage on July 4, 2014 from 5-7pm)

   o  needs at least the following attributes to report on cyclic
      patterns:

      *  generic time zone,



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      *  applicable time interval for each calendar value (measurement
         estimation with units or unitless preference value) : combining
         <nb-int-unit> and <interval-unit> to reflect for example:
         1hour, 2minutes, 1week, 1month

      *  date range of the Calendar, e.g. number of intervals allowing
         to derive the calendar time range in terms of: year, month,
         week, day, hour, min, secs

   o  needs to expose validity period of the calendar: indicating when
      the next ALTO Calendar for this date range should be fetched if
      needed,

   o  needs to provide time stamps:

      *  last-update-time: specifying when the metric values were last
         computed ,

      *  next-update-time: specifying when the calendar values will be
         re-computed, indicating thus when an ALTO client should fetch
         an update if it uses a Calendar.

      *  calendar-start-date: specifying when the current already
         computed calendar starts,

      *  next-calendar-start-date: specifying when the already computed
         calendar will have different values, indicating thus that the
         ALTO client should fetch the next pre-computed calendar

   It may be useful to keep a cyclic network status with date, in case
   of exceptional predicted events such as New Year evening on a Tuesday
   or any worldwide event generating a lot of traffic.Traffic calendars
   may be particularly useful in such cases.

4.  ALTO extensions for a Cost Calendar

   The usage of a time-related ALTO Cost Calendar is rather proactive in
   that it can be used like a "time table" to figure out the best time
   to schedule data transfer and also anticipate predictable events
   including predictable flash crowds.  An ALTO Cost Calendar should be
   viewed as a synthetic abstraction of real measurements that can be
   historic or be a prediction for upcoming time periods.

   Specifications on the cost "calendar" attributes are proposed here
   and will be completed in further versions of this draft, upon
   discussion with the ALTO WG.





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   The format of ALTO requests and responses will be specified in
   further versions of this draft, as in particular it may be necessary
   that the ALTO response indicates the computation and validity dates
   of the provided ALTO Calendar.

4.1.  ALTO Cost-Mode: Calendar

   This draft introduces a new ALTO Cost Mode called "calendar".  This
   mode applies preferably to Costs that can be expressed in a single-
   valued Cost Mode.  In that sense, when the "numerical" mode is
   available for a Cost-Type, the cost expressed in the "calendar" mode
   is an extension of its expression from one value in the "numerical"
   mode to an array of several values varying over time.

   Types of Cost values such as JSONBool can also be expressed in the
   "calendar" mode, as states may be "true" or "false" depending on
   given time periods.  They may be expressed as a single value which is
   either "true" or "false" following a decision rule outside the ALTO
   protocol.

   DISCUSSION: The current draft focuses on Calendars representing
   values encoded in the 'numerical' mode.  However, Calendars should
   also be able to represent time sensitive values represented by
   strings, such as "medium", "high", "low".  To support this, one
   option is to extend the Cost Mode to be a combination (attribute)
   indicators, for example cost-mode : "ordinal;calendar"

   cost-mode : "ordinal;calendar"

   We chose ";" as separator to be consistent with existing formats such
   as the HTTP list of multiple options (e.g., Accept).

4.2.  ALTO Calendar attributes in the IRD

   To ensure that the application client understands the provided
   information in the cost calendar in an unambiguous way, we specify
   the Calendar attributes in the ALTO IRD "meta" information, that
   defines the time scope of the "calendared" cost values.  The Calendar
   attributes in the IRD are meant to carry constant dateless values.

   o  time-interval-size:

      *  expresses the unit in which the duration of an ALTO calendar
         time interval duration is expressed appended to the number of
         these units.  The time unit, ranges from "second" to "year".
         The number is encoded with an integer.  Example values are: "5
         minute" , "2 hour".  These vales mean that each calendar value




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         is provided on a time interval that lasts respectively 5
         minutes and 2 hours.

   o  numb-intervals:

      *  the integer number of values of the cost calendar array, at
         least equal to 1.

   o  repeat:

      *  an integer number representing the number of times that the
         Calendar pattern repeats.  That is : if for example a given
         daily pattern is represented Calendar is made of "num-
         intervals" = 24 cost values each applicable to a time slot
         lasting "time-interval-size" = 1 hour and the value of 'repeat'
         is 5, the client can interpret that 5 daily patterns starting
         from the date indicated in the Server response have identical
         values.

   - Attributes 'time-interval-size' and 'numb-intervals', when
   mutlipled, reflect the duration of the provided calendar.  For
   example an ALTO Server may provide a calendar for ALTO values
   changing every 'time-interval-size' equal to 5 minutes.  If 'numb-
   intervals' has the value 12, then the duration of the provided
   calendar is "1 hour".  Note also that in this example, a 5 minutes
   interval may cover the aggregation of real TE measurements done every
   30 seconds, but this latter aspect is outside the scope of this draft
   as it is to be specified in the definition of the ALTO metric.

   - Attribute 'repeat' reflects the frequancy at which the patterns
   represented by a Calendar may change.  This information is completed
   by the 'start' attribute provided in Server responses to calendar
   requests.

   NOTE that: To cope with existing representation fomats, further
   versions will re-name these attributes.  The current proposal for
   renaming in further versions is to replace "time-interval-size" by
   "interval" and "num-interval" by "count" :

4.3.  Example of calendared information resources in the IRD

   This section describes an example IRD and related ALTO calendar
   transaction in a scenario where an ALTO Server offers the Calendar
   Mode for several Cost Types that are either specified in the base
   ALTO protocol or proposed in other drafts see
   [draft-wu-alto-te-metrics] or suggested here as examples, like a cost
   metric reporting on measured packet loss and called 'TEpktloss.  The




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   provided example transactions are based on the use cases of section
   2.

   These examples describe situations where a client has the choice of
   trading content or resources with several Endpoints and needs to
   decide with which Endpoint it will trade and at what time.  For
   instance, one may assume that the Endpoints are spread over different
   time-zones, or have intermittent access.  The ALTO Calendar mode
   specified below allows these clients to retrieve Endpoint Cost Maps
   valid for a certain timeframe (e.g. 24 hours), and get a set of
   values, each applicable on a specified time interval (e.g. 1 hour).
   Thus the application can optimize the needed data transfer according
   to this information.

   In the example IRD of the present draft, the available Endpoint Costs
   metrics are: "routingcost", "AShopcount", 'TEpktloss' and
   'Availbandwidth'. "routingcost" and "AShopcount" are available in the
   "numerical" Cost Mode.  'TEpktloss' , 'Availbandwidth' and
   "routingcost" as well are available in the "calendar" Cost Mode.

   We suppose that the ALTO Client GETs the IRD on Tuesday July 1st 2014
   at 13:00

   o  The Calendar for 'TEpktloss'': is an hourly pattern that consists
      of 12 values provided each on a time interval of 5 minutes, and
      the values are the same for the next 2 hours.

   o  The Calendar for 'Availbandwidth': is a daily pattern that
      consists of 12 values provided each on time intervals of 2 hours,
      with the first interval starting at 0h00.  This information is
      typically used to enable applications to see which time intervals
      in a day are the most favorable to operate, and which "busy " time
      intervals should be avoided.  The pattern is the same for the next
      "repeat" = 7days.

   o  The Calendar for 'routingcost': is a daily pattern that consists
      of an array of 24 time intervals lasting each 1 hour.  The
      routingcost calendar covers a 1 day period, starting at midnight.
      This may be applicable for networks with poor or intermittent
      connectivity where the operator may integrate monetary as well as
      network performance metrics in the provided 'routingcost'
      values.The pattern is the same for the nex "repeat" = 4 days.

4.3.1.  Example IRD with ALTO cost Calendars

   The example IRD given in this section includes 2 particular URIs:





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   o  "http://alto.example.com/endpointcost/lookup", in which the ALTO
      Server offers the numerical mode for metrics "routingcost" and
      "AShopcount".

   o  "http://alto.example.com/endpointcost/calendar/lookup", in which
      the ALTO Server provides "calendar" mode for metrics 'TEpktloss'
      and 'Availbandwidth' and 'routingcost'.

   For Cost Type 'calendar-routing', this example assumes that the ALTO
   Server has defined 3 different daily patterns each represented by a
   Calendar, to cover the week of Monday June 30th at 00:00 to Sunday
   July 6th 23:59:

   - C1 for Monday, Tuesday, Wednesday, Thursday, (week days)

   - C2 for Saturday, Sunday, (week end)

   - C3 for Friday (maintenance outage on July 4, 2014 from 02:00:00 GMT
   to 04:00:00 GMT, or big holiday such as New Year evening)

   The example ALTO response shown in a further section also illustrates
   how specific calendar attributes allow an ALTO client to fetch 3
   Calendars instead of 7 and thus to reduce the volume of on-the-wire
   data exchange.  For Cost Type 'calendar-routing' , the IRD provides a
   value for attribute 'num-calendars' which is equal to 3.

GET /directory HTTP/1.1
   Host: alto.example.com
   Accept: application/alto-directory+json,application/alto-error+json


HTTP/1.1 200 OK
   Content-Length: [TODO]
   Content-Type: application/alto-directory+json

   {
     "meta" : {
        "cost-types": {
           "num-routingcost": {
              "cost-mode" : "numerical",
              "cost-metric" : "routingcost"
              },
           "num-AShopcount": {
              "cost-mode" : "numerical",
              "cost-metric" : "hopcount"
              },
           "calendar-TEpktloss": {
              "cost-mode"  : "calendar",



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              "cost-metric": "TEpktloss",
              "description": {
                  "time-interval-size" : "5 minute",
                  "numb-intervals" : 12,
                  "repeat" : 2
              }
           },
           "calendar-bw": {
              "cost-mode"  : "calendar",
              "cost-metric": "Availbandwidth",
              "description": {
                  "time-interval-size" : "2 hour",
                  "numb-intervals" : 12,
                  "repeat" : 7
              }
          },
          "calendar-routing": {
             "cost-mode"  : "calendar",
             "cost-metric": "routingcost",
             "description": {
                 "time-interval-size" : "1 hour",
                 "numb-intervals" : 24,
                 "repeat: 4"

         }
         ... other meta ...
       },

    "resources" : {

       ... usual ALTO resources such as Network Map, Cost Maps ...

       "endpoint-cost" : {
         "uri" : "http://alto.example.com/endpointcost/lookup",
         "media-types" : [ "application/alto-endpointcost+json" ],
         "accepts" : [ "application/alto-endpointcostparams+json" ],
         "capabilities" : {
           "cost-constraints" : true,
           "cost-type-names" : [ "num-routingcost", "num-AShopcount" ]
           }
         },
       "endpoint-cost-calendar-map" : {
         "uri" : "http://alto.example.com/endpointcost/calendar/lookup",
         "media-types" : [ "application/alto-endpointcost+json" ],
         "accepts" : [ "application/alto-endpointcostparams+json" ],
         "capabilities" : {
           "cost-constraints" : true,
           "cost-type-names" : [ "calendar-routingcost",



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                                 "calendar-TEpktloss",
                                 "calendar-bw"]
           }
         }
     }
   }



4.4.  ALTO Calendar information in ALTO responses

   ALTO responses convey additional attributes with usually non constant
   values that inform the ALTO Client about the next date at which the
   calendar values stored in the ALTO Server will change and at which
   time updates calendar values will be uploaded in the ALTO Server.  A
   number of Calendar attributes in ALTO responses are dates.  The
   reference time zone for the provided values is GMT.  Indeed, the
   option chosen to express the time format is the HTTP header fields
   formats such as:

                    Date: Tue, 15 Nov 1994 08:12:31 GMT


   o  calendar-start-time:

      *  the date corresponding to the first value in the calendar
         values array

   o  time-interval-size: as defined for the IRD

   o  numb-intervals: as defined for the IRD

   o  repeat: as defined for the IRD

   - Attribute 'calendar-start-time' indicates when the calendar
   provided to the ALTO client starts.  If the 'calendar-start-time'
   date is past, the application can also use the information to compute
   statistics on values provided by ALTO over time to guide
   applications.  Besides estimating some customized prediction the ALTO
   Client may use these values to assess their reliability w.r.t. some
   real measures of QoE.

   Discussion: like for the attributes of the IRD, "calendar-start-time"
   can be renames "start" to comply with existing formats.







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4.4.1.  Example transaction for a routingcost Calendar to face
        intermittent connectivity

   Let us assume an Application Client located in an end sytem with
   limited resources and having an access to the network that is either
   intermittent or provides an acceptable quality in limited but
   possibly predictable time periods.  Therefore, it needs to both
   schedule its resources demanding networking activities and minimize
   its ALTO transactions.

   The Application Client has the choice to trade content or resources
   with a set of Endpoints of moderate 'routingcost', and needs to
   decide with which Endpoint it will trade at what time.  For instance,
   one may assume that the Endpoints are spread on different time-zones,
   or have intermittent access.  In this example, the 'routingcost' is
   assumed to be the time sentitive decision metric, with values
   provided in the ALTO Calendar Mode.

   The ALTO Client embedded in the Application Client queries an ALTO
   Calendar on 'routingcost' and will get the Calendar covering the 24
   hours time period "containing" the date and time of the ALTO client
   request.  We suppose in this example that the ALTO Client sends its
   request on Tuesday July 1st 2014 at 13:15

   The present example also illustrates how attributes "repeat" and
   "calendar-start-time" allow an ALTO client to fetch 3 Calendars
   instead of 7 and thus to reduce the volume of on-the-wire data
   exchange, because the ALTO Server has defined 3 different daily
   patterns each represented by a Calendar, to cover the week of Monday
   June 30th at 00:00 to Sunday July 6th 23:59:

   - C1 for Monday, Tuesday, Wednesday, Thursday, (week days)

   - C2 for Saturday, Sunday, (week end)

   - C3 for Friday (maintenance outage on July 4, 2014 from 5-7pm, or
   holiday such as New Year evening)














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POST endpointcost/calendar/lookup HTTP/1.1
  Host: alto.example.com
  Content-Length: [TODO]
  Content-Type: application/alto-endpointcostparams+json
  Accept: application/alto-endpointcost+json,application/alto-error+json

  {
    "cost-type" : {"cost-mode" : "calendar", "cost-metric" : "routingcost"},
    "endpoints" : {
      "srcs": [ "ipv4:192.0.2.2" ],
      "dsts": [
        "ipv4:192.0.2.89",
        "ipv4:198.51.100.34",
        "ipv4:203.0.113.45"
      ]
    }
  }


  HTTP/1.1 200 OK
  Content-Length: [TODO]
  Content-Type: application/alto-endpointcost+json

  {
    "meta" : {
      "calendar-start-time" : Tue, 1 Jul 2014 00:00:00 GMT,
      "time-interval-size" : "1 hour",
      "numb-intervals" : 24,
      "repeat": 4
    },
    "cost-type" : {"cost-mode" : "calendar", "cost-metric" : "routingcost"},
    "endpoint-cost-calendar-map" : {
        "ipv4:192.0.2.2": {
          "ipv4:192.0.2.89"    : [7, ... 24 values],
          "ipv4:198.51.100.34" : [4, ... 24 values],
          "ipv4:203.0.113.45"  : [2, ... 24 values]
        }
    }
  }


   NOTE also: that the Calendar could enumerate 24*7 hourly values to
   represent the pattern for such a week.








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4.4.2.  Example transaction for a bandwidth calendar

   An example of non-real time information that can be provisioned in a
   'calendar' is the expected path bandwidth.  While the transmission
   rate can be measured in real time by end systems, the operator of a
   data center is in the position of formulating preferences for given
   paths, at given time periods for example to avoid traffic peaks due
   to diurnal usage patterns.  In this example, we assume that an ALTO
   Client requests a bandwidth calendar as specified in the IRD to
   shedule its bulk data transfers as described in the use cases of
   sections 2.1 and 2.5.

   We suppose in this example that the ALTO Client sends its request on
   Tuesday July 1st 2014 at 13:15





































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POST endpointcost/calendar/lookup HTTP/1.1
  Host: alto.example.com
  Content-Length: [TODO]
  Content-Type: application/alto-endpointcostparams+json
  Accept: application/alto-endpointcost+json,application/alto-error+json

  {
    "cost-type" : {"cost-mode" : "calendar", "cost-metric" : "Availbandwidth"},
    "endpoints" : {
      "srcs": [ "ipv4:192.0.2.2" ],
      "dsts": [
        "ipv4:192.0.2.89",
        "ipv4:198.51.100.34",
        "ipv4:203.0.113.45"
      ]
    }
  }


  HTTP/1.1 200 OK
  Content-Length: [TODO]
  Content-Type: application/alto-endpointcost+json

  {
    "meta" : {
      "calendar-start-time" : Tue, 1 Jul 2014 00:00:00 GMT,
      "time-interval-size" : "2 hour",
      "numb-intervals" : 12,
      "repeat" : 7
    },
    "cost-type" : {"cost-mode" : "calendar", "cost-metric" : "Availbandwidth"},
    "endpoint-cost-calendar-map" : {
        "ipv4:192.0.2.2": {
          "ipv4:192.0.2.89"    : [7, ... 12 values],
          "ipv4:198.51.100.34" : [4, ... 12 values],
          "ipv4:203.0.113.45"  : [2, ... 12 values]
        }
    }
  }



5.  Use cases for ALTO Cost Schedule

   This section introduces use cases showing the benefits of providing
   ALTO Cost values in 'calendar' mode.  Most likely, the ALTO Cost
   Calendar would be used for the Endpoint Cost Service, assuming that a
   limited set of feasible Endpoints for a non-real time application is



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   already identified, that they do not need to be accessed immediately
   and that their access can be scheduled within a given time period.
   The Cost Map service, filtered or not, is also applicable as long as
   the size of the Map is manageable.

   Last, the ALTO Cost calendar is beneficial to optimizing ALTO
   transactions themselves.  Indeed, let us assume that an Application
   Client is located in an end sytem with limited resources and/or has
   an access to the network that is either intermittent or provides an
   acceptable QoE in limited but predictable time periods.  In that
   case, it needs to both schedule its resources demanding networking
   activities and its ALTO requests.  Instead of having to figure out
   when the cost values may change and having to carefully schedule
   multiple ALTO requests, it could aviod this by relying on Cost
   Shedule attributes that indicate the time granularity, the validity
   and time scope of the cost information, together with the time
   related cost values themselves.

5.1.  Bulk Data Transfer scheduling

   Large Internet Content Providers (ICPs) like Facebook or YouTube, as
   well as CDNs rely on data replication across multiple sites to
   offload the core site and increase user experience through shorter
   latency from a local site.  Typically the usage pattern of these data
   centers or caches follows a location dependent diurnal pattern.

   In the examples above, data needs to be replicated across the various
   locations of a Internet Content Provider (ICP), leading to bulk data
   transfers between datacenters on a diurnal pattern.

   In the mean time, there is a degree of freedom on when the content is
   transmitted from the origin server to the caching node, or from the
   core site to a local site.  However, scheduling these data transfers
   is a non-trivial task as the transfer should not infer with the user
   peak demand to avoid degradation of user experience and to decrease
   billing costs for the datacenter operator by leveraging off-peak
   hours for the transfer.  This peak demand typically follows a diurnal
   pattern according to the geographic region of the datacenter.

   As a result, it would be very helpful to let these ICPs to have a
   good knowledge about the link utilization patterns between the
   different datacenters from the networks before making a more
   intelligent scheduling decision.  While this usage data today already
   is gathered and also used for the scheduling of data transfer,
   provisioning this data gets increasingly complex with the number of
   CDN nodes and in particular the number of datacenter operators that
   are involved.  For example, privacy concerns prevent that this kind
   of data is shared across administrative domains.  The ALTO Cost



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   Calendar specified later in this document avoids this problem by
   presenting an abstracted view of time sensitive utilization maps
   through a dedicated ALTO service to allow ICPs a coherent scheduling
   of such data transfers across administrative domains.

5.2.  Endsystems with limited connectivity or access to datacenters

   Another use case that benefits from the availability of multi-
   timeframe cost information is based on applications that are limited
   by their connectivity either in time or resources or both.  For
   example applications running on devices in remote locations or in
   developing countries that need to synchronize their state with a data
   center periodically, in particular if sometimes there is no
   connection at all.  Example applications is enterprise database
   update, remote learning, remote computation distributed on several
   data center endpoints.

   Wireless connections have a variable quality and may even be
   intermittent.  On the other hand, the wireless network conditions are
   often predicable and have a rapid impact on applications.  Non real
   time applications and time-insensitive data transfers such as client
   patching, archive syncing, etc. can benefit from careful scheduling.
   It is thus desirable to provide ALTO clients with routing costs to
   connection nodes (i.e.  Application Endpoints) over different time
   periods.  This would allow end systems using ALTO aware application
   clients to schedule their connections to application endpoints.

   Another challenge arises with end systems using resources located in
   datacenters and trading content and resources scattered around the
   world.  For non-real time applications, the interaction with
   Endpoints can be scheduled at the time slots corresponding to the
   best possible network conditions in order to improve the QoE.  For
   instance, resource Ra downloaded from Endpoint EPa at time t1,
   Resource Rb uploaded to EPb at time t2, some batch computation
   involving Ra and Rb done on EPc at time t3 and results R(A,B)
   downloaded to EPd and EPe at time t4.  Example applications are
   similar to the ones cited in the previous paragraph.














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     +-----+                                           +-----+
     | EPa |                                           | EPb | <----- Rb
     +-----+                                           +-----+   (t2=50)
        |                   +-------+                     |
        Ra -------------->  | EPc   |                     |
        (time t1=10)        |       |                     |
                            |t3=100 |  <----------------- Rb
                            +-------+
                                | \
                                |  \
                              R(Ra,Rb)
                             (t4=200)
                                |     \
                                |      -------------------.
                                V                         V
                             +-----+                   +-----+
                             | EPd |                   | EPe |
                             +-----+                   +-----+



5.3.  SDN Controller guided access to application endpoints

   The Software Defined Networking (SDN), see [sdnrg], is a model that
   attempts to manage and reconfigure networks in a more flexible way in
   order to better cope with the traffic challenges posed by nowadays
   resources greedy applications.  To this end, one option is "moving
   the control plane out of the network elements into "controllers", see
   [SDN charter, http://www.1-4-5.net/~dmm/sdnrg/sdnrg.html], that
   implements the network control and management.  The SDN Controllers
   are deemed to gather the network state information and provide it in
   an abstracted form to SDN aware applications while gathering their
   requirements in QoE and exchanging other application "management"
   information and commands.

   The relevance of ALTO to perform a number of SDN functions has been
   recently highlighted.  An ALTO Server can assist an SDN Controller by
   hosting abstracted network information that can be provided to SDN
   aware applications via an ALTO Client.  It can also assist other SDN
   Control operations using information in and outside the ALTO scope.

   The SDN primitive "Get network resources" provides applications with
   informations allowing them to evaluate the expected QoE.  QoE related
   information includes delay and bandwidth at the application endpoints
   as well as on the network paths.  Such information may be provided
   via the ALTO Service by proposed extensions of the ALTO protocol that
   define new ALTO Cost Types allowing to abstract and report QoE to
   applications.



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   One key objective of an SDN controller is the ability to balance the
   application traffic whenever possible.  For non real time
   applications, data and resources transfer can be time shifted,
   resources availability may often be predicable and last, strong
   incentives for applications to time shift their traffic may be given
   by network operators appropriately setting routing cost values at
   different time values, according to their policy to cope with network
   occupation over time.

   To achieve this objective, the SDN controller can:

   1.  get the network state history from its controlled network
       elements through its southbound API

   2.  possibly derive an estimation or a prediction of these values
       over given time frames

   3.  compute estimates and/or network provider preferences on end to
       end paths and store their abstraction in an ALTO Server in the
       form of ALTO Cost Calendar values defined for different time
       periods

   4.  deliver these values to the SDN applications via the ALTO
       Endpoint Cost Service, as estimations covering the past and/or
       the future and/or preferences.

   This way:

   o  On one hand, the applications get the best possible QoE, as they
      can pick the best time for them to access one or more Endpoints,

   o  One the other hand the SDN controller achieves load balancing as
      it may guide the application traffic so as to better distribute
      the traffic over time, and thus optimize its resources usage.

5.4.  Large flow scheduling on extended ALTO topologies

   [draft-yang-alto-topology-00] presents initial thinking on extending
   ALTO for topology exposure services, that would provide flexible
   abstractions based on the raw network topology.  Among other
   features, an ALTO topology may expose several paths between a source
   (src) and destination (dst), or topology details may be provided on
   restricted parts.  This work was presented to the ALTO WG at IETF88.

   The presentation slides [slides-88-alto-5-topology] on
   [draft-yang-alto-topology-00] expose a use case entitled "Large Flow
   Scheduling".  This case includes a "daylife example" where a Google
   Map service proposes multiple routes between 2 points A and B, each



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   calculated w.r.t. length and estimated time.  For each of these
   selected paths, the map service exposes a time-sensitive qualitative
   value taking 4 values between Slow and Fast.  A user of this
   application may thus organize its transfer w.r.t. metrics, paths and
   time, provided s/he does not have to commute immediately.

   The use case on Large flow scheduling on extended ALTO topologies in
   the present section illustrates one modality of ALTO topology
   service, that would expose several paths between end to end (src,
   dst) pairs, computed w.r.t. one of more metrics, possibly under given
   constraints.  On top of this enriched topology service, non real-time
   applications may also choose the time of data/resources transfer,
   taking thus advantage of a richer set of decision variables.

   The use case "Large Flow Scheduling" of presentation
   [slides-88-alto-5-topology]can thus be adapted as follows:

   o  Step1 - obtain the set T transfer tasks {(src, dest, data)}

   o  Step2 - identify one or more paths for each (src, dst): several
      information sources exist among which:

      *  (a) ALTO CostMap with a "path" metric, // not specified here

      *  (b) an ALTO Topology Service providing a path computation hint
         (e.g. w.r.t. routingcost and/or other metrics)

   o  Step 3 - while T not empty:

      *  1 - query for example values for some metric 'available
         bandwidth' on paths:

         +  to this end, query the values in the ALTO 'calendar' Mode:
            on the selected (src, dst) for a set of time intervals.
            With this mode, the ALTO client will receive an array of
            values, each applicable to a time slot .

      *  2 - schedule data transfer at the time slots corresponding to
         the preferred value.

5.5.  Time-sensitve TE metrics Calendaring

   Draft [draft-wu-alto-te-metrics] , proposes to extend the set of ALTO
   metrics with 11 ALTO traffic engineering (TE) metrics to reflect
   measurement on network delay, jitter, packet loss, hop count, and
   bandwidth.  ALTO TE metrics that are time-sensitive, either by nature
   such as bandwidth and delay related metrics, or due to "normally"
   changing network conditions or both.



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   The values of ALTO TE metrics are typically collected from routing
   protocols and provided in a non-real time manner.  In "normally"
   changing network conditions, TE metric values remain uniformly
   distributed over given time intervals and can be aggregated over
   bigger time intervals of periodic patterns.  For example, an ALTO
   Server may collect values for e.g. delay from a routing protocol
   produced by measurements done every second over a measurement period
   of 30 seconds.  The ALTO Server may then aggregate these values over
   two measurement periods (i.e. 60 seconds) and repeat the operation as
   it wishes.  Then every hour, the ALTO Server provides these delay
   values in 'calendar' mode, encoded as an array of 60 values, assumed
   to estimate network performance statistics on each minute of this
   hour.

   Another example is Bandwidth Calendaring.  Bandwidth Calendaring
   allows network operators to reserve resources in advance according to
   agreements with their customers, enabling them to transmit data with
   specified starting time and duration, for example, for a scheduled
   bulk data replication between data centers.  Traditionally, this can
   be supported by a Network Management System operation such as path
   pre-establishment and activation on the agreed starting time.
   However, this does not provide efficient network usage since the
   established paths exclude the possibility of being used by other
   services even when they are not used for undertaking any service.

   A Cost calendar provided by an ALTO server can support the scheduled
   bulk data replication application with better efficiency since it can
   alleviate the burden of processing on network elements.  This
   requires the ALTO server to maintain the calendared TE cost metrics
   on the end to end paths associated to data transfer.

   To support cost calendaring for these time-sensitive ALTO TE metrics,
   the network topology and the dynamicity of the traffic need to be
   considered.  For example, a small topology with low density and low
   capacity that carries inpredictable, heavy and bursty traffic has few
   chances to exhibit stationary TE metric value patterns over large
   periods and would benefit to use the ALTO Calendar over smaller time
   slots.  Some ALTO TE metric values, even aggregated over time may
   need to be updated at a frequency that would require doing ALTO
   request at a pace that would be overload both the ALTO Client and the
   Server.

6.  IANA Considerations

   Information for the ALTO Endpoint property registry maintained by the
   IANA and related to the new Endpoints supported by the acting ALTO
   server.  These definitions will be formulated according to the syntax




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   defined in Section on "ALTO Endpoint Property Registry" of
   [ID-alto-protocol],

   Information for the ALTO Cost Type Registry maintained by the IANA
   and related to the new Cost Types supported by the acting ALTO
   server.  These definitions will be formulated according to the syntax
   defined in Section on "ALTO Cost Type Registry" of [RFC7285],

6.1.  Information for IANA on proposed Cost Types

   When a new ALTO Cost Type is defined, accepted by the ALTO working
   group and requests for IANA registration MUST include the following
   information, detailed in Section 11.2: Identifier, Intended
   Semantics, Security Considerations.

6.2.  Information for IANA on proposed Endpoint Propeeries

   Likewise, an ALTO Endpoint Property Registry could serve the same
   purposes as the ALTO Cost Type registry.  Application to IANA
   registration for Endpoint Properties would follow a similar process.

7.  Acknowledgements

   Thank you to Diego Lopez, He Peng and Haibin Song and the ALTO WG for
   fruitful discussions.

8.  References

8.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.

   [RFC5693]  Seedorf, J. and E. Burger, "Application-Layer Traffic
              Optimization (ALTO) Problem Statement", RFC 5693, October
              2009.

8.2.  Informative References

   [ID-alto-protocol]
              R.Alimi, R. Penno, Y. Yang, Eds., "ALTO Protocol, RFC
              7285", September 2014.

   [RFC7285]  R. Alimi, R. Yang, R. Penno, Eds., "ALTO Protocol",
              September 2014.






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   [article-gslh-alto-sdn]
              V. Gurbani, M. Scharf, T.Lakshman, and V. Hilt, ,
              "Abstracting network state in Software Defined Networks
              (SDN) for rendezvous services, IEEE International
              Conference on Communications (ICC) Workshop on Software
              Defined Networks (SDN)", June 2012.

   [draft-jenkins-alto-cdn-use-cases-01]
              B. Niven-Jenkins (Ed.), G. Watson, N. Bitar, J. Medved, S.
              Previdi, , "Use Cases for ALTO within CDNs, draft-jenkins-
              alto-cdn-use-cases-01", June 2011.

   [draft-randriamasy-multi-cost-alto]
              S. Randriamasy, Ed., W. Roome, N. Schwan, , "Multi-Cost
              ALTO (work in progress), draft-randriamasy-alto-multi-
              cost-07", October 2012.

   [draft-wu-alto-te-metrics]
              Q. Wu, Y. Yang, Y. Lee, D. Dhody, S. Randriamasy, , "ALTO
              Traffic Engineering Cost Metrics (work in progress)",
              October 2014.

   [draft-xie-alto-sdn]
              H. Xie, T. Tsou, D. Lopez, H. Yin, , "Use Cases for ALTO
              with Software Defined Networks (work in progress), draft-
              xie-alto-sdn-extension-use-cases-01", January 2013.

   [draft-yang-alto-topology-00]
              Y. Yang, , "ALTO Topology Considerations (work in
              progress)", July 2013.

   [sdnrg]    "Software Defined Network Research Group,
              http://trac.tools.ietf.org/group/irtf/trac/wiki/sdnrg", .

   [slides-88-alto-5-topology]
              G. Bernstein, Y. Lee, Y. Yang, , , "ALTO Topology Service:
              Use Cases, Requirements and Framework (presentation slides
              IETF88 ALTO WG session),
              http://tools.ietf.org/agenda/88/slides/
              slides-88-alto-5.pdf", November 2013.

Authors' Addresses









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   Sabine Randriamasy (editor)
   Alcatel-Lucent Bell Labs
   Route de Villejust
   NOZAY  91460
   FRANCE

   Email: Sabine.Randriamasy@alcatel-lucent.com


   Richard Yang
   Yale University
   51 Prospect st
   New Haven, CT  06520
   USA

   Email: yry@cs.yale.edu


   Qin Wu
   Huawei
   101 Software Avenue, Yuhua District
   Nanjing, Jiangsu  210012
   China

   Email: sunseawq@huawei.com


   Lingli Deng
   China Mobile
   China

   Email: denglingli@chinamobile.com


   Nico Schwan
   Thales Deutschland

   Email: nico.schwan@thalesgroup.com













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