ROLL                                                             D. Popa
Internet-Draft                                               J. Jetcheva
Intended status: Standards Track                                   Itron
Expires: January 26, 2012                                      N. Dejean
                                                              Elster SAS
                                                              R. Salazar
                                                                  J. Hui
                                                           July 25, 2011

Applicability Statement for the Routing Protocol for Low Power and Lossy
                     Networks (RPL) in AMI Networks


   This document discusses the applicability of RPL in Advanced Metering
   Infrastructure (AMI) networks.

Status of this Memo

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   provisions of BCP 78 and BCP 79.

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   This Internet-Draft will expire on January 26, 2012.

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   Copyright (c) 2011 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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   ( in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect

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   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
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Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
     1.1.  Electric Metering  . . . . . . . . . . . . . . . . . . . .  3
     1.2.  Gas and Water Metering . . . . . . . . . . . . . . . . . .  4
     1.3.  Routing Protocol for LLNs (RPL)  . . . . . . . . . . . . .  4
     1.4.  Requirements Language  . . . . . . . . . . . . . . . . . .  5
   2.  Deployment Scenarios . . . . . . . . . . . . . . . . . . . . .  5
     2.1.  Network Topology . . . . . . . . . . . . . . . . . . . . .  5
     2.2.  Traffic Characteristics  . . . . . . . . . . . . . . . . .  6
       2.2.1.  Meter Data Management  . . . . . . . . . . . . . . . .  6
       2.2.2.  Distribution Automation  . . . . . . . . . . . . . . .  7
       2.2.3.  Emerging Applications  . . . . . . . . . . . . . . . .  7
   3.  Using RPL to Meet Functional Requirements  . . . . . . . . . .  7
   4.  RPL Profile  . . . . . . . . . . . . . . . . . . . . . . . . .  8
     4.1.  RPL Features . . . . . . . . . . . . . . . . . . . . . . .  8
       4.1.1.  RPL Instances  . . . . . . . . . . . . . . . . . . . .  8
       4.1.2.  Storing vs. Non-Storing Mode . . . . . . . . . . . . .  8
       4.1.3.  DAO Policy . . . . . . . . . . . . . . . . . . . . . .  8
       4.1.4.  Path Metrics . . . . . . . . . . . . . . . . . . . . .  9
       4.1.5.  Objective Function . . . . . . . . . . . . . . . . . .  9
       4.1.6.  DODAG Repair . . . . . . . . . . . . . . . . . . . . .  9
       4.1.7.  Multicast  . . . . . . . . . . . . . . . . . . . . . . 10
       4.1.8.  Security . . . . . . . . . . . . . . . . . . . . . . . 10
     4.2.  RPL Options  . . . . . . . . . . . . . . . . . . . . . . . 10
     4.3.  Recommended Configuration Defaults and Ranges  . . . . . . 10
   5.  Manageability Considerations . . . . . . . . . . . . . . . . . 11
   6.  Security Considerations  . . . . . . . . . . . . . . . . . . . 11
   7.  Other Related Protocols  . . . . . . . . . . . . . . . . . . . 12
   8.  IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 12
   9.  Security Considerations  . . . . . . . . . . . . . . . . . . . 12
   10. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 12
   11. References . . . . . . . . . . . . . . . . . . . . . . . . . . 12
     11.1. Informative References . . . . . . . . . . . . . . . . . . 12
     11.2. Normative References . . . . . . . . . . . . . . . . . . . 13
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 13

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1.  Introduction

   Advanced Metering Infrastructure (AMI) systems enable the
   measurement, configuration, and control of energy, gas and water
   consumption and distribution, through two-way scheduled, on
   exception, and on-demand communication.

   AMI networks are composed of millions of endpoints, including meters,
   distribution automation elements, and home area network devices.
   They are typically inter-connected using some combination of wireless
   technologies and power-line communications, along with backhaul
   network providing connectivity to "command-and-control" management
   software applications at the utility company back office.

1.1.  Electric Metering

   In many deployments, in addition to measuring energy consumption, the
   electric meter network plays a central role in the Smart Grid since
   it enables the utility company to control and query the electric
   meters themselves and also since it can serve as a backhaul for all
   other devices in the Smart Grid, e.g., water and gas meters,
   distribution automation and home area network devices.  Electric
   meters may also be used as sensors to monitor electric grid quality
   and to support applications such as Electric Vehicle charging.

   Electric meter networks are composed of millions of smart meters (or
   nodes), each of which is resource-constrained in terms of processing
   power, storage capabilities, and communication bandwidth, due to a
   combination of factors including Federal Communications Commission
   (FCC) or other continents' regulations on spectrum use, American
   National Standards Institute (ANSI) standards or other continents'
   regulation on meter behavior and performance, on heat emissions
   within the meter, form factor and cost considerations.  This results
   in a compromise between range and throughput, with effective link
   throughput of tens to a few hundred kilobits per second per link, a
   potentially significant portion of which is taken up by protocol and
   encryption overhead when strong security measures are in place.

   Electric meters are often interconnected into multi-hop mesh
   networks, each of which is connected to a backhaul network leading to
   the utility network through a network aggregation point (NAP).  These
   kinds of networks increase coverage and reduce installation cost,
   time and complexity, as well as operational costs, as compared to
   single-hop wireless networks, relying on a wireline or cellular
   backhaul.  Each electric meter mesh typically has on the order of
   several thousand wireless endpoints, with densities varying based on
   the area and the terrain.  Apartment buildings in urban centers may
   have hundreds of meters in close proximity, whereas rural areas may

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   have sparse node distributions and include nodes that only have one
   or two network neighbors.  Paths in the mesh between a network device
   and the nearest aggregation point may be composed of several hops or
   even tens of hops.

1.2.  Gas and Water Metering

   While electric meters typically consume electricity from the same
   electric feed that they are monitoring, gas and water meters
   typically run on a modest source of stored energy (i.e. batteries).

   In some scenarios, gas and water meters are integrated into the same
   AMI network as the electric meters and may operate as network
   endpoints (rather than routers) in order to prolong their own
   lifetime.  In other scenarios, such meters may not have the luxury of
   relying on a powered routing infrastructure but must communicate
   through other energy-constrained devices (i.e., through other gas and
   water meters) to reach a NAP.  In some cases, battery-powered meters
   need to communicate directly with a sparsely deployed network
   infrastructure, requiring them to use high transmit power levels (and
   thus more energy) in order to achieve the necessary range to reach
   the infrastructure.  In all of these types of networks, the routing
   protocol must operate with energy consumption in mind.

   RPL is designed to operate in energy-constrained environments and
   includes energy-saving mechanisms (e.g.  Trickle timers) and energy-
   aware metrics.  Its ability to support multiple different metrics and
   constraints at the same time enables it to run efficiently in
   heterogeneous networks composed of nodes and links with vastly
   different characteristics.  [I-D.ietf-roll-routing-metrics].

1.3.  Routing Protocol for LLNs (RPL)

   RPL provides routing functionality for mesh networks composed of a
   large number of resource-constrained devices, interconnected by low
   power and lossy links, and communicating with the external network
   infrastructure through a common aggregation point (e.g., a border

   RPL builds a Directed Acyclic Graph (DAG) routing structure rooted at
   the aggregation point, ensures loop-free routing, and provides
   support for alternate routes, as well as, for a wide range of routing
   metrics and policies.

   This note describes the applicability of RPL (as defined in
   [I-D.ietf-roll-rpl]) to AMI deployments.  RPL was designed to meet
   the following application requirements:

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   o  Routing Requirements for Urban Low-Power and Lossy Networks

   o  Industrial Routing Requirements in Low-Power and Lossy Networks

   o  Home Automation Routing Requirements in Low-Power and Lossy
      Networks [RFC5826].

   o  Building Automation Routing Requirements in Low-Power and Lossy
      Networks [RFC5867].

   The Routing Requirements for Urban Low-Power and Lossy Networks are
   applicable to AMI networks as well.

   The terminology used in this document is defined in

1.4.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in RFC 2119 [RFC2119].

2.  Deployment Scenarios

2.1.  Network Topology

   AMI networks are composed of millions of endpoints distributed across
   both urban and rural environments.  Such endpoints include electric,
   gas, and water meters, distribution automation elements, and home
   area network devices.  Devices in the network communicate directly
   with other devices in close proximity using a variety of low-power
   and/or lossy link technologies that are both wired and wireless (e.g.
   IEEE 802.15.4, IEEE P1901.2, and WiFi).  In addition to serving as
   sources and destinations of packets, many network elements typically
   also forward packets to reduce the need for dedicated network
   infrastructure and the associated deployment and operational costs.

   In a typical AMI deployment, groups of meters within physical
   proximity form routing domains, each in the order of a 1,000 to
   10,000 meters.  These routing domains are connected to the larger IP
   infrastructure through one or more LLN Border Routers (LBRs), which
   provide Wide Area Network (WAN) connectivity through various
   traditional network technologies, e.g., Ethernet, Cellular, private

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   Powered from the main line, electric meters have less energy
   constraints than battery powered devices and can afford the
   additional resources required to route packets.  In mixed
   environments, electric meters provide the routing topology while gas
   and water meters operate as leaf nodes.  However, in the absence of a
   co-located electric meter network, gas and water meters must either
   connect directly to the larger IP network infrastructure or form
   their own routing topology, albeit with energy consumption in mind.

   Meter networks may also serve as transit networks for other types of
   devices, including distribution automation elements (e.g., sensors
   and actuators), and in-home devices.  These other devices may utilize
   a different link-layer technology than the one used in the meter

2.2.  Traffic Characteristics

2.2.1.  Meter Data Management

   Meter Data Management (MDM) applications typically require every
   smart meter to communicate with a few head-end servers deployed in a
   utility data center.  As a result, all smart metering traffic
   typically goes through the LBRs, with the vast majority of traffic
   flowing from smart meter devices to the head-end servers, i.e., in a
   Multipoint-to-Point (MP2P) fashion.

   Smart meters may generate traffic according to a schedule (e.g.,
   periodic meter reads), in response to on-demand queries (e.g., on-
   demand meter reads), or in response to events (e.g., power outages,
   leak detections).  Such traffic is typically unicast since it is sent
   to a single head-end server.

   Head-end servers generate traffic to configure smart metering devices
   or initiate queries, and use unicast and multicast to efficiently
   communicate with a single device (i.e., Point-to-Point (P2P)
   communication) or groups of devices respectively (i.e., Point-to-
   Multipoint (P2MP) communication).  The head-end server may send a
   single small packet at a time (e.g., a meter read request, or small
   configuration change) or many consecutive large packets (e.g., a
   firmware upgrade across one or even thousands of devices).

   While smart metering applications typically do not have hard real-
   time constraints, they are often subject to stringent latency and
   reliability service level agreements.

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2.2.2.  Distribution Automation

   Distribution Automation (DA) applications typically involve a small
   number of devices that communicate with each other in a Point-to-
   Point (P2P) fashion.  The DA devices may or may not be in close
   physical proximity.

   DA applications typically have more stringent latency requirements
   than MDM applications.

2.2.3.  Emerging Applications

   There are a number of emerging applications such as electric vehicle
   charging.  These applications may require P2P communication and may
   eventually have more stringent latency requirements than MDM

3.  Using RPL to Meet Functional Requirements

   The functional requirements for most AMI deployments are similar to
   those listed in [RFC5548]:

   o  The routing protocol MUST be capable of supporting the
      organization of a large number of nodes into regions containing on
      the order of 10^2 to 10^4 nodes each.

   o  The routing protocol MUST provide mechanisms to support
      configuration of the routing protocol itself.

   o  The routing protocol SHOULD support and utilize the large number
      of highly directed flows to a few head-end servers to handle

   o  The routing protocol MUST dynamically compute and select effective
      routes composed of low-power and lossy links.  Local network
      dynamics SHOULD NOT impact the entire network.  The routing
      protocol MUST compute multiple paths when possible.

   o  The routing protocol MUST support multicast and anycast
      addressing.  The routing protocol SHOULD support formation and
      identification of groups of field devices in the network.

   RPL supports:

   o  Large-scale networks characterized by highly directed traffic
      flows between each smart meter and the head-end servers in the
      utility network.  To this end, RPL builds a Directed Acyclic Graph

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      (DAG) rooted at each LBR.

   o  Zero-touch configuration.  This is done through in-band methods
      for configuring RPL variables using DIO messages.

   o  The use of links with time-varying quality characteristics.  This
      is accomplished by allowing the use of metrics that effectively
      capture the quality of a path (e.g., Expected Transmission Count
      (ETX)) and by limiting the impact of changing local conditions by
      discovering and maintaining multiple DAG parents, and by using
      local repair mechanisms when DAG links break.

4.  RPL Profile

   This section outlines a RPL profile for a representative AMI

4.1.  RPL Features

4.1.1.  RPL Instances

   RPL operation is defined for a single RPL instance.  However,
   multiple RPL instances can be supported in multi-service networks
   where different applications may require the use of different routing
   metrics and constraints, e.g., a network carrying both MDM and DA

4.1.2.  Storing vs. Non-Storing Mode

   In most scenarios, electric meters are powered by the electric grid
   they are monitoring and are not energy-constrained.  Instead, the
   capabilities of an electric meter are primarily determined by cost.
   As a result, different AMI deployments can vary significantly in
   terms of the memory, computation, and communication trade-offs that
   they embody.  For this reason, the use of RPL storing or non-storing
   mode SHOULD be deployment specific.

   When meters are memory constrained and cannot adequately store route
   tables to support downward routing, non-storing mode is preferred.
   However, when nodes are capable of adequately storing such routing
   tables, storing mode can lead to reduced overhead and shorter route
   repair latency.

4.1.3.  DAO Policy

   Two-way communication is a requirement in AMI systems.  As a result,
   nodes SHOULD send DAO messages to establish downward paths from the

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   root to themselves.

4.1.4.  Path Metrics

   Smart metering deployments utilize link technologies that can exhibit
   significant packet loss.  To characterize a path over such link
   technologies, AMI deployments can use the Expected Transmission Count
   (ETX) metric as defined in[I-D.ietf-roll-routing-metrics].

   For water- and gas-only networks that cannot rely on a powered
   infrastructure, energy constraints may require simpler metrics that
   do not require as much energy to compute.  In particular, hop count
   and link quality level may be more suitable in such deployments.
   Other possible metrics to use may be vendor-specific or defined at a
   later time in companion RFCs.

4.1.5.  Objective Function

   RPL relies on an Objective Function for selecting parents and
   computing path costs and rank.  This objective function is decoupled
   from the core RPL mechanisms and also from the metrics in use in the
   network.  Two basic objective functions for RPL have been defined at
   the time of this writing, OF0 and MRHOF, both of which define the
   selection of a preferred parent and backup parents, and are suitable
   for a basic AMI deployment.  Neither of these supports multiple
   metrics that might be required in heterogeneous networks (i.e.
   networks composed of devices with different energy constraints).  A
   new objective function can be defined to meet this requirement.

4.1.6.  DODAG Repair

   To effectively handle time-varying link characteristics and
   availability, AMI deployments SHOULD utilize the local repair
   mechanisms in RPL.

   The first mechanism for local repair when a node loses connectivity
   to its parents is to detach from a DODAG then re-attach to the same
   or to a different DODAG at a later time.  While detached, a node
   advertises an infinite rank value so that its children can select a
   different parent.  This process is known as poisoning and described
   in Section of [I-D.ietf-roll-rpl].  While RPL provides an
   option to form a local DODAG, doing so in AMI deployments is of
   little benefit since AMI applications typically communicate through a
   LBR.  After the detached node has made sufficient effort to send
   notification to its children that it is detached, the node can rejoin
   the same DODAG with a higher rank value.  Note that when joining a
   different DODAG, the node need not perform poisoning.

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   The second local repair mechanism controls how much a node can
   increase its rank within a given DODAG Version.  Setting the
   DAGMaxRankIncrease to a non-zero value enables this mechanism, and
   setting it to a value of less than infinity limits the cost of count-
   to-infinity scenarios when they occur.

   The third local repair mechanism enables loop detection, and is
   implemented by including the rank value of the transmitting node in
   packets forwarded towards the root (in the packet's RPL Packet
   Information option [I-D.ietf-6man-rpl-option]).  Note that loop
   detection is not needed when sending packets using strict source

4.1.7.  Multicast

   RPL defines multicast support for its storing mode of operation.  The
   DODAG structure built for unicast packet dissemination is used for
   multicast distribution as well.  In particular, multicast forwarding
   state creation is done through DAO messages with multicast target
   options sent along the DODAG towards the root.  Thereafter nodes with
   forwarding state for a particular group forward multicast packets
   along the DODAG by copying them to all children from which they have
   received a DAO with a multicast target option for the group.

   Multicast support for RPL in non-storing mode will be defined in
   companion RFCs.

4.1.8.  Security

   AMI deployments operate in areas that do not provide any physical
   security.  For this reason, the link technologies used within AMI
   deployments typically provide security mechanisms to ensure
   confidentiality, integrity, and freshness.  As a result, AMI
   deployments may not need to implement RPL's security mechanisms and
   could rely on link-layer security features.

4.2.  RPL Options

4.3.  Recommended Configuration Defaults and Ranges

   o  AMI deployments can involve densities of hundreds of devices
      within communication range.  As a result, such networks SHOULD set
      the DIOIntervalMin to 16 or more, resulting in a Trickle Imin of 1
      minute or more.  In networks with low-energy consumption
      requirements, DIOIntervalMin SHOULD be set to a higher value.

   o  AMI deployments SHOULD set DIOIntervalDoublings to a value that
      gives a Trickle Imax of 2 hours or more.  In networks with low-

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      energy consumption requirements, DIOIntervalDoublings SHOULD be
      set to a value that results in a Trickle Imax of several (e.g., 2)

   o  AMI deployments SHOULD set DIORedundancyConstant to a value of 10
      or more.

   o  AMI deployments SHOULD set MinHopRankIncrease to 256, resulting in
      8 bits of resolution (e.g. for the ETX metric).

   o  To enable local repair, AMI deployments SHOULD set MaxRankIncrease
      to a value that allows a device to move a small number of hops
      away from the root.  With a MinHopRankIncrease of 256, a
      MaxRankIncrease of 1024 would allow a device to move up to 4 hops

5.  Manageability Considerations

   Network manageability is a critical aspect of smart grid network
   deployment and operation.  With millions of devices participating in
   the smart grid network, many requiring real-time reachability,
   automatic configuration, and lightweight network health monitoring
   and management, are crucial for achieving network availability and
   efficient operation.

   RPL enables automatic and consistent configuration of RPL routers
   through parameters specified by the DODAG root and dissemintated
   through DIO packets.  The use of Trickle for scheduling DIO
   transmissions ensures lightweight yet timely propagation of important
   network and parameter updates.

   RPL specifies a number of variables and events that can be tracked
   for purposes of network fault and performance monitoring of RPL
   routers.  Depending on the memory and processing capabilities of each
   smart grid device, various subsets of these can be employed in the

   The CoRE Working Group is developing lightweight resource management
   mechanisms for LLNs that are applicable to smart grid RPL networks as

6.  Security Considerations

   Smart grid networks are subject to stringent security requirements as
   they are considered a critical national infrastructure component.  At
   the same time, since they are composed of large numbers of resource-

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   constrained devices inter-connected with limited-throughput links,
   many available security mechanisms are not practical for use in such
   networks.  As a result, the choice of security mechanisms is highly
   dependent on the device and network capabilities characterizing a
   particular deployment.

   In contrast to other types of LLNs, in smart grid networks
   centralized administrative control and access to a permanent secure
   infrastructure is available.  As a result link-layer security
   mechanisms are typically in place and using RPL's secure mode is not
   necessary.  Smart grid networks are often secured at other layers as
   well, including end-to-end at the application layer.

7.  Other Related Protocols

   This document contains no other related protocols.

8.  IANA Considerations

   This memo includes no request to IANA.

9.  Security Considerations

   This memo includes no security considerations.

10.  Acknowledgements

   The authors would like to acknowledge the review, feedback, and
   comments from Dominique Barthel.

11.  References

11.1.  Informative References

              Hui, J. and J. Vasseur, "RPL Option for Carrying RPL
              Information in Data-Plane Datagrams",
              draft-ietf-6man-rpl-option-03 (work in progress),
              March 2011.

              Vasseur, J., Kim, M., Pister, K., Dejean, N., and D.
              Barthel, "Routing Metrics used for Path Calculation in Low

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              Power and Lossy Networks",
              draft-ietf-roll-routing-metrics-19 (work in progress),
              March 2011.

              Winter, T., Thubert, P., Brandt, A., Clausen, T., Hui, J.,
              Kelsey, R., Levis, P., Pister, K., Struik, R., and J.
              Vasseur, "RPL: IPv6 Routing Protocol for Low power and
              Lossy Networks", draft-ietf-roll-rpl-19 (work in
              progress), March 2011.

              Vasseur, J., "Terminology in Low power And Lossy
              Networks", draft-ietf-roll-terminology-05 (work in
              progress), March 2011.

   [RFC5548]  Dohler, M., Watteyne, T., Winter, T., and D. Barthel,
              "Routing Requirements for Urban Low-Power and Lossy
              Networks", RFC 5548, May 2009.

   [RFC5673]  Pister, K., Thubert, P., Dwars, S., and T. Phinney,
              "Industrial Routing Requirements in Low-Power and Lossy
              Networks", RFC 5673, October 2009.

   [RFC5826]  Brandt, A., Buron, J., and G. Porcu, "Home Automation
              Routing Requirements in Low-Power and Lossy Networks",
              RFC 5826, April 2010.

   [RFC5867]  Martocci, J., De Mil, P., Riou, N., and W. Vermeylen,
              "Building Automation Routing Requirements in Low-Power and
              Lossy Networks", RFC 5867, June 2010.

11.2.  Normative References

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

Authors' Addresses

   Daniel Popa
   52 rue Camille Desmoulins
   Issy-les-Moulineaux, Cedex, 92448


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   Jorjeta Jetcheva
   2111 N Molter Rd.
   Liberty Lake, WA


   Nicolas Dejean
   Elster SAS
   Espace Concorde, 120 impasse JB Say
   Perols, 34470


   Ruben Salazar
   30000 Mill Creek Ave # 100
   Alpharetta, GA  30022


   Jonathan W. Hui
   170 West Tasman Drive
   San Jose, California  95134

   Phone: +408 424 1547

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