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Versions: (draft-ersue-opsawg-coman-use-cases) 00 01 02 03 04 05 RFC 7548

Internet Engineering Task Force                            M. Ersue, Ed.
Internet-Draft                              Nokia Solutions and Networks
Intended status: Informational                              D. Romascanu
Expires: August 18, 2014                                           Avaya
                                                        J. Schoenwaelder
                                                               A. Sehgal
                                                Jacobs University Bremen
                                                       February 14, 2014


       Management of Networks with Constrained Devices: Use Cases
                  draft-ietf-opsawg-coman-use-cases-01

Abstract

   This document discusses the use cases concerning the management of
   networks, where constrained devices are involved.  A problem
   statement, deployment options and the requirements on the networks
   with constrained devices can be found in the companion document on
   "Management of Networks with Constrained Devices: Problem Statement
   and Requirements".

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
   working documents as Internet-Drafts.  The list of current Internet-
   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
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on August 18, 2014.

Copyright Notice

   Copyright (c) 2014 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



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   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.  Access Technologies  . . . . . . . . . . . . . . . . . . . . .  5
     2.1.  Constrained Access Technologies  . . . . . . . . . . . . .  5
     2.2.  Mobile Access Technologies . . . . . . . . . . . . . . . .  5
   3.  Use Cases  . . . . . . . . . . . . . . . . . . . . . . . . . .  7
     3.1.  Environmental Monitoring . . . . . . . . . . . . . . . . .  7
     3.2.  Infrastructure Monitoring  . . . . . . . . . . . . . . . .  7
     3.3.  Industrial Applications  . . . . . . . . . . . . . . . . .  8
     3.4.  Energy Management  . . . . . . . . . . . . . . . . . . . . 10
     3.5.  Medical Applications . . . . . . . . . . . . . . . . . . . 12
     3.6.  Building Automation  . . . . . . . . . . . . . . . . . . . 13
     3.7.  Home Automation  . . . . . . . . . . . . . . . . . . . . . 15
     3.8.  Transport Applications . . . . . . . . . . . . . . . . . . 15
     3.9.  Vehicular Networks . . . . . . . . . . . . . . . . . . . . 17
     3.10. Community Network Applications . . . . . . . . . . . . . . 18
     3.11. Military Operations  . . . . . . . . . . . . . . . . . . . 19
   4.  IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 21
   5.  Security Considerations  . . . . . . . . . . . . . . . . . . . 22
   6.  Contributors . . . . . . . . . . . . . . . . . . . . . . . . . 23
   7.  Acknowledgments  . . . . . . . . . . . . . . . . . . . . . . . 24
   8.  Informative References . . . . . . . . . . . . . . . . . . . . 25
   Appendix A.  Open Issues . . . . . . . . . . . . . . . . . . . . . 26
   Appendix B.  Change Log  . . . . . . . . . . . . . . . . . . . . . 27
     B.1.  draft-ietf-opsawg-coman-use-cases-00 -
           draft-ietf-opsawg-coman-use-cases-01 . . . . . . . . . . . 27
     B.2.  draft-ersue-constrained-mgmt-03 -
           draft-ersue-opsawg-coman-use-cases-00  . . . . . . . . . . 27
     B.3.  draft-ersue-constrained-mgmt-02-03 . . . . . . . . . . . . 27
     B.4.  draft-ersue-constrained-mgmt-01-02 . . . . . . . . . . . . 28
     B.5.  draft-ersue-constrained-mgmt-00-01 . . . . . . . . . . . . 29
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 30











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1.  Introduction

   Small devices with limited CPU, memory, and power resources, so
   called constrained devices (aka. sensor, smart object, or smart
   device) can be connected to a network.  Such a network of constrained
   devices itself may be constrained or challenged, e.g., with
   unreliable or lossy channels, wireless technologies with limited
   bandwidth and a dynamic topology, needing the service of a gateway or
   proxy to connect to the Internet.  In other scenarios, the
   constrained devices can be connected to a non-constrained network
   using off-the-shelf protocol stacks.  Constrained devices might be in
   charge of gathering information in diverse settings including natural
   ecosystems, buildings, and factories and send the information to one
   or more server stations.

   Network management is characterized by monitoring network status,
   detecting faults, and inferring their causes, setting network
   parameters, and carrying out actions to remove faults, maintain
   normal operation, and improve network efficiency and application
   performance.  The traditional network management application
   periodically collects information from a set of elements that are
   needed to manage, processes the data, and presents them to the
   network management users.  Constrained devices, however, often have
   limited power, low transmission range, and might be unreliable.  They
   might also need to work in hostile environments with advanced
   security requirements or need to be used in harsh environments for a
   long time without supervision.  Due to such constraints, the
   management of a network with constrained devices offers different
   type of challenges compared to the management of a traditional IP
   network.

   This document aims to understand the use cases for the management of
   a network, where constrained devices are involved.  The document
   lists and discusses diverse use cases for the management from the
   network as well as from the application point of view.  The
   application scenarios discussed aim to show where networks of
   constrained devices are expected to be deployed.  For each
   application scenario, we first briefly describe the characteristics
   followed by a discussion on how network management can be provided,
   who is likely going to be responsible for it, and on which time-scale
   management operations are likely to be carried out.

   A problem statement, deployment and management topology options as
   well as the requirements on the networks with constrained devices can
   be found in the companion document [COM-REQ].

   This documents builds on the terminology defined in
   [I-D.ietf-lwig-terminology] and [COM-REQ].



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   [I-D.ietf-lwig-terminology] is a base document for the terminology
   concerning constrained devices and constrained networks.  Some use
   cases specific to IPv6 over Low-Power Wireless Personal Area Networks
   (6LoWPANs) can be found in [RFC6568].















































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2.  Access Technologies

   Besides the management requirements imposed by the different use
   cases, the access technologies used by constrained devices can impose
   restrictions and requirements upon the Network Management System
   (NMS) and protocol of choice.

   It is possible that some networks of constrained devices might
   utilize traditional non-constrained access technologies for network
   access, e.g., local area networks with plenty of capacity.  In such
   scenarios, the constrainedness of the device presents special
   management restrictions and requirements rather than the access
   technology utilized.

   However, in other situations constrained or mobile access
   technologies might be used for network access, thereby causing
   management restrictions and requirements to arise as a result of the
   underlying access technologies.

2.1.  Constrained Access Technologies

   Due to resource restrictions, embedded devices deployed as sensors
   and actuators in the various use cases utilize low-power low data-
   rate wireless access technologies such as IEEE 802.15.4, DECT ULE or
   BT-LE for network connectivity.

   In such scenarios, it is important for the NMS to be aware of the
   restrictions imposed by these access technologies to efficiently
   manage these constrained devices.  Specifically, such low-power low
   data-rate access technologies typically have small frame sizes.  So
   it would be important for the NMS and management protocol of choice
   to craft packets in a way that avoids fragmentation and reassembly of
   packets since this can use valuable memory on constrained devices.

   Devices using such access technologies might operate via a gateway
   that translates between these access technologies and more
   traditional Internet protocols.  A hierarchical approach to device
   management in such a situation might be useful, wherein the gateway
   device is in-charge of devices connected to it, while the NMS
   conducts management operations only to the gateway.

2.2.  Mobile Access Technologies

   Machine to machine (M2M) services are increasingly provided by mobile
   service providers as numerous devices, home appliances, utility
   meters, cars, video surveillance cameras, and health monitors, are
   connected with mobile broadband technologies.  Different
   applications, e.g., in a home appliance or in-car network, use



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   Bluetooth, Wi-Fi or Zigbee locally and connect to a cellular module
   acting as a gateway between the constrained environment and the
   mobile cellular network.

   Such a gateway might provide different options for the connectivity
   of mobile networks and constrained devices:

   o  a smart phone with 3G/4G and WLAN radio might use BT-LE to connect
      to the devices in a home area network,

   o  a femtocell might be combined with home gateway functionality
      acting as a low-power cellular base station connecting smart
      devices to the application server of a mobile service provider,

   o  an embedded cellular module with LTE radio connecting the devices
      in the car network with the server running the telematics service,

   o  an M2M gateway connected to the mobile operator network supporting
      diverse IoT connectivity technologies including ZigBee and CoAP
      over 6LoWPAN over IEEE 802.15.4.

   Common to all scenarios above is that they are embedded in a service
   and connected to a network provided by a mobile service provider.
   Usually there is a hierarchical deployment and management topology in
   place where different parts of the network are managed by different
   management entities and the count of devices to manage is high (e.g.
   many thousands).  In general, the network is comprised by manifold
   type and size of devices matching to different device classes.  As
   such, the managing entity needs to be prepared to manage devices with
   diverse capabilities using different communication or management
   protocols.  In case the devices are directly connected to a gateway
   they most likely are managed by a management entity integrated with
   the gateway, which itself is part of the Network Management System
   (NMS) run by the mobile operator.  Smart phones or embedded modules
   connected to a gateway might be themselves in charge to manage the
   devices on their level.  The initial and subsequent configuration of
   such a device is mainly based on self-configuration and is triggered
   by the device itself.

   The gateway might be in charge of filtering and aggregating the data
   received from the device as the information sent by the device might
   be mostly redundant.









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3.  Use Cases

3.1.  Environmental Monitoring

   Environmental monitoring applications are characterized by the
   deployment of a number of sensors to monitor emissions, water
   quality, or even the movements and habits of wildlife.  Other
   applications in this category include earthquake or tsunami early-
   warning systems.  The sensors often span a large geographic area,
   they can be mobile, and they are often difficult to replace.
   Furthermore, the sensors are usually not protected against tampering.

   Management of environmental monitoring applications is largely
   concerned with the monitoring whether the system is still functional
   and the roll-out of new constrained devices in case the system looses
   too much of its structure.  The constrained devices themselves need
   to be able to establish connectivity (auto-configuration) and they
   need to be able to deal with events such as loosing neighbors or
   being moved to other locations.

   Management responsibility typically rests with the organization
   running the environmental monitoring application.  Since these
   monitoring applications must be designed to tolerate a number of
   failures, the time scale for detecting and recording failures is for
   some of these applications likely measured in hours and repairs might
   easily take days.  However, for certain environmental monitoring
   applications, much tighter time scales may exist and might be
   enforced by regulations (e.g., monitoring of nuclear radiation).

3.2.  Infrastructure Monitoring

   Infrastructure monitoring is concerned with the monitoring of
   infrastructures such as bridges, railway tracks, or (offshore)
   windmills.  The primary goal is usually to detect any events or
   changes of the structural conditions that can impact the risk and
   safety of the infrastructure being monitored.  Another secondary goal
   is to schedule repair and maintenance activities in a cost effective
   manner.

   The infrastructure to monitor might be in a factory or spread over a
   wider area but difficult to access.  As such, the network in use
   might be based on a combination of fixed and wireless technologies,
   which use robust networking equipment and support reliable
   communication.  It is likely that constrained devices in such a
   network are mainly C2 devices and have to be controlled centrally by
   an application running on a server.  In case such a distributed
   network is widely spread, the wireless devices might use diverse
   long-distance wireless technologies such as WiMAX, or 3G/LTE, e.g.



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   based on embedded hardware modules.  In cases, where an in-building
   network is involved, the network can be based on Ethernet or wireless
   technologies suitable for in-building usage.

   The management of infrastructure monitoring applications is primarily
   concerned with the monitoring of the functioning of the system.
   Infrastructure monitoring devices are typically rolled out and
   installed by dedicated experts and changes are rare since the
   infrastructure itself changes rarely.  However, monitoring devices
   are often deployed in unsupervised environments and hence special
   attention must be given to protecting the devices from being
   modified.

   Management responsibility typically rests with the organization
   owning the infrastructure or responsible for its operation.  The time
   scale for detecting and recording failures is likely measured in
   hours and repairs might easily take days.  However, certain events
   (e.g., natural disasters) may require that status information be
   obtained much more quickly and that replacements of failed sensors
   can be rolled out quickly (or redundant sensors are activated
   quickly).  In case the devices are difficult to access, a self-
   healing feature on the device might become necessary.

3.3.  Industrial Applications

   Industrial Applications and smart manufacturing refer to tasks such
   as networked control and monitoring of manufacturing equipment, asset
   and situation management, or manufacturing process control.  For the
   management of a factory it is becoming essential to implement smart
   capabilities.  From an engineering standpoint, industrial
   applications are intelligent systems enabling rapid manufacturing of
   new products, dynamic response to product demands, and real-time
   optimization of manufacturing production and supply chain networks.
   Potential industrial applications (e.g., for smart factories and
   smart manufacturing) are:

   o  Digital control systems with embedded, automated process controls,
      operator tools, as well as service information systems optimizing
      plant operations and safety.

   o  Asset management using predictive maintenance tools, statistical
      evaluation, and measurements maximizing plant reliability.

   o  Smart sensors detecting anomalies to avoid abnormal or
      catastrophic events.

   o  Smart systems integrated within the industrial energy management
      system and externally with the smart grid enabling real-time



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      energy optimization.

   Management of Industrial Applications and smart manufacturing may in
   some situations involve Building Automation tasks such as control of
   energy, HVAC (heating, ventilation, and air conditioning), lighting,
   or access control.  Interacting with management systems from other
   application areas might be important in some cases (e.g.,
   environmental monitoring for electric energy production, energy
   management for dynamically scaling manufacturing, vehicular networks
   for mobile asset tracking).

   Sensor networks are an essential technology used for smart
   manufacturing.  Measurements, automated controls, plant optimization,
   health and safety management, and other functions are provided by a
   large number of networked sectors.  Data interoperability and
   seamless exchange of product, process, and project data are enabled
   through interoperable data systems used by collaborating divisions or
   business systems.  Intelligent automation and learning systems are
   vital to smart manufacturing but must be effectively integrated with
   the decision environment.  Wireless sensor networks (WSN) have been
   developed for machinery Condition-based Maintenance (CBM) as they
   offer significant cost savings and enable new functionalities.
   Inaccessible locations, rotating machinery, hazardous areas, and
   mobile assets can be reached with wireless sensors.  WSNs can provide
   today wireless link reliability, real-time capabilities, and quality-
   of-service and enable industrial and related wireless sense and
   control applications.

   Management of industrial and factory applications is largely focused
   on the monitoring whether the system is still functional, real-time
   continuous performance monitoring, and optimization as necessary.
   The factory network might be part of a campus network or connected to
   the Internet.  The constrained devices in such a network need to be
   able to establish configuration themselves (auto-configuration) and
   might need to deal with error conditions as much as possible locally.
   Access control has to be provided with multi-level administrative
   access and security.  Support and diagnostics can be provided through
   remote monitoring access centralized outside of the factory.

   Management responsibility is typically owned by the organization
   running the industrial application.  Since the monitoring
   applications must handle a potentially large number of failures, the
   time scale for detecting and recording failures is for some of these
   applications likely measured in minutes.  However, for certain
   industrial applications, much tighter time scales may exist, e.g. in
   real-time, which might be enforced by the manufacturing process or
   the use of critical material.




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3.4.  Energy Management

   The EMAN working group developed an energy management framework
   [I-D.ietf-eman-framework] for devices and device components within or
   connected to communication networks.  This document observes that one
   of the challenges of energy management is that a power distribution
   network is responsible for the supply of energy to various devices
   and components, while a separate communication network is typically
   used to monitor and control the power distribution network.  Devices
   that have energy management capability are defined as Energy Devices
   and identified components within a device (Energy Device Components)
   can be monitored for parameters like Power, Energy, Demand and Power
   Quality.  If a device contains batteries, they can be also monitored
   and managed.

   Energy devices differ in complexity and may include basic sensors or
   switches, specialized electrical meters, or power distribution units
   (PDU), and subsystems inside the network devices (routers, network
   switches) or home or industrial appliances.  An Energy Management
   System is a combination of hardware and software used to administer a
   network with the primary purpose being Energy Management.  The
   operators of such a system are either the utility providers or
   customers that aim to control and reduce the energy consumption and
   the associated costs.  The topology in use differs and the deployment
   can cover areas from small surfaces (individual homes) to large
   geographical areas.  The EMAN requirements document [RFC6988]
   discusses the requirements for energy management concerning
   monitoring and control functions.

   It is assumed that Energy Management will apply to a large range of
   devices of all classes and networks topologies.  Specific resource
   monitoring like battery utilization and availability may be specific
   to devices with lower physical resources (device classes C0 or C1).

   Energy Management is especially relevant to the Smart Grid.  A Smart
   Grid is an electrical grid that uses data networks to gather and to
   act on energy and power-related information in an automated fashion
   with the goal to improve the efficiency, reliability, economics, and
   sustainability of the production and distribution of electricity.  A
   Smart Grid provides sustainable and reliable generation,
   transmission, distribution, storage and consumption of electrical
   energy based on advanced energy and information technology.  Smart
   Grids enable the following specific application areas: Smart
   transmission systems, Demand Response/Load Management, Substation
   Automation, Advanced Distribution Management, Advanced Metering
   Infrastructure (AMI), Smart Metering, Smart Home and Building
   Automation, E-mobility, etc.




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   Smart Metering is a good example of Smart Grid based Energy
   Management applications.  Different types of possibly wireless small
   meters produce all together a large amount of data, which is
   collected by a central entity and processed by an application server,
   which may be located within the customer's residence or off-site in a
   data-center.  The communication infrastructure can be provided by a
   mobile network operator as the meters in urban areas will have most
   likely a cellular or WiMAX radio.  In case the application server is
   located within the residence, such meters are more likely to use WiFi
   protocols to interconnect with an existing network.

   An AMI network is another example of the Smart Grid that enables an
   electric utility to retrieve frequent electric usage data from each
   electric meter installed at a customer's home or business.  This is
   unlike Smart Metering, in which case the customer or their agents
   install appliance level meters, because an AMI infrastructure is
   typically managed by the utility providers.  With an AMI network, a
   utility can also receive immediate notification of power outages when
   they occur, directly from the electric meters that are experiencing
   those outages.  In addition, if the AMI network is designed to be
   open and extensible, it could serve as the backbone for communicating
   with other distribution automation devices besides meters, which
   could include transformers and reclosers.

   Each meter in the AMI network typically contains constrained devices
   of the C2 type.  Each meter uses the constrained devices to connect
   to mesh networks with a low-bandwidth radio.  These radios can be 50,
   150, or 200 kbps at raw link speed, but actual network throughput may
   be significantly lower due to forward error correction, multihop
   delays, MAC delays, lossy links, and protocol overhead.  Usage data
   and outage notifications can be sent by these meters to the utility's
   headend systems, typically located in a data center managed by the
   utility, which include meter data collection systems, meter data
   management systems, and outage management systems.

   Meters in an AMI network, unlike in Smart Metering, act as traffic
   sources and routers as well.  Typically, smaller amounts of traffic
   (read requests, configuration) flow "downstream" from the headend to
   the mesh, and larger amounts of traffic flow "upstream" from the mesh
   to the headend.  However, during a firmware update operation for
   example, larger amounts of traffic might flow downstream while
   smaller amounts flow upstream.  The mesh network is anchored by a
   collection of higher-end devices that bridge the constrained network
   with a backhaul link that connects to a less-constrained network via
   cellular, WiMAX, or Ethernet.  These higher-end devices might be
   installed on utility poles that could be owned and managed by a
   different entity than the utility company.




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   While a Smart Metering solution is likely to have a smaller number of
   devices within a single household, AMI network installations could
   contain 1000 meters per router, i.e., the higher-end device.  Meters
   in a local network that use a specific router form a Local Meter
   Network (LMN).  When powered on, meters discover nearby LMNs, select
   the optimal LMN to join, and the meters in that LMN to route through.
   However, in a Smart Metering application the meters are likely to
   connect directly to a less-constrained network, thereby not needing
   to form such local mesh networks.

   Encryption key sharing in both types of network is also likely to be
   important for providing confidentiality for all data traffic.  In AMI
   networks the key may be obtained by a meter only after an end-to-end
   authentication process based on certificates, ensuring that only
   authorized and authenticated meters are allowed to join the LMN.
   Smart Metering solution could adopt a similar approach or the
   security may be implied due to the encrypted WiFi networks they
   become part of.

   These examples demonstrate that the Smart Grid, and Energy Management
   in general, is built on a distributed and heterogeneous network and
   can use a combination of diverse networking technologies, such as
   wireless Access Technologies (WiMAX, Cellular, etc.), wireline and
   Internet Technologies (e.g., IP/MPLS, Ethernet, SDH/PDH over Fiber
   optic) as well as low-power radio technologies enabling the
   networking of smart meters, home appliances, and constrained devices
   (e.g., BT-LE, ZigBee, Z-Wave, Wi-Fi).  The operational effectiveness
   of the Smart Grid is highly dependent on a robust, two-way, secure,
   and reliable communications network with suitable availability.

   The management of such a network requires end-to-end management of
   and information exchange through different types of networks.
   However, as of today there is no integrated energy management
   approach and no common information model available.  Specific energy
   management applications or network islands use their own management
   mechanisms.

3.5.  Medical Applications

   Constrained devices can be seen as an enabling technology for
   advanced and possibly remote health monitoring and emergency
   notification systems, ranging from blood pressure and heart rate
   monitors to advanced devices capable to monitor implanted
   technologies, such as pacemakers or advanced hearing aids.  Medical
   sensors may not only be attached to human bodies, they might also
   exist in the infrastructure used by humans such as bathrooms or
   kitchens.  Medical applications will also be used to ensure
   treatments are being applied properly and they might guide people



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   losing orientation.  Fitness and wellness applications, such as
   connected scales or wearable heart monitors, encourage consumers to
   exercise and empower self-monitoring of key fitness indicators.
   Different applications use Bluetooth, Wi-Fi or Zigbee connections to
   access the patient's smartphone or home cellular connection to access
   the Internet.

   Constrained devices that are part of medical applications are managed
   either by the users of those devices or by an organization providing
   medical (monitoring) services for physicians.  In the first case,
   management must be automatic and or easy to install and setup by
   average people.  In the second case, it can be expected that devices
   be controlled by specially trained people.  In both cases, however,
   it is crucial to protect the privacy of the people to which medical
   devices are attached.  Even though the data collected by a heart beat
   monitor might be protected, the pure fact that someone carries such a
   device may need protection.  As such, certain medical appliances may
   not want to participate in discovery and self-configuration protocols
   in order to remain invisible.

   Many medical devices are likely to be used (and relied upon) to
   provide data to physicians in critical situations since the biggest
   market is likely elderly and handicapped people.  As such, fault
   detection of the communication network or the constrained devices
   becomes a crucial function that must be carried out with high
   reliability and, depending on the medical appliance and its
   application, within seconds.

3.6.  Building Automation

   Building automation comprises the distributed systems designed and
   deployed to monitor and control the mechanical, electrical and
   electronic systems inside buildings with various destinations (e.g.,
   public and private, industrial, institutions, or residential).
   Advanced Building Automation Systems (BAS) may be deployed
   concentrating the various functions of safety, environmental control,
   occupancy, security.  More and more the deployment of the various
   functional systems is connected to the same communication
   infrastructure (possibly Internet Protocol based), which may involve
   wired or wireless communications networks inside the building.

   Building automation requires the deployment of a large number (10-
   100.000) of sensors that monitor the status of devices, and
   parameters inside the building and controllers with different
   specialized functionality for areas within the building or the
   totality of the building.  Inter-node distances between neighboring
   nodes vary between 1 to 20 meters.  Contrary to home automation, in
   building management the devices are expected to be managed assets and



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   known to a set of commissioning tools and a data storage, such that
   every connected device has a known origin.  The management includes
   verifying the presence of the expected devices and detecting the
   presence of unwanted devices.

   Examples of functions performed by such controllers are regulating
   the quality, humidity, and temperature of the air inside the building
   and lighting.  Other systems may report the status of the machinery
   inside the building like elevators, or inside the rooms like
   projectors in meeting rooms.  Security cameras and sensors may be
   deployed and operated on separate dedicated infrastructures connected
   to the common backbone.  The deployment area of a BAS is typically
   inside one building (or part of it) or several buildings
   geographically grouped in a campus.  A building network can be
   composed of subnets, where a subnet covers a floor, an area on the
   floor, or a given functionality (e.g., security cameras).

   Some of the sensors in Building Automation Systems (for example fire
   alarms or security systems) register, record and transfer critical
   alarm information and therefore must be resilient to events like loss
   of power or security attacks.  This leads to the need that some
   components and subsystems operate in constrained conditions and are
   separately certified.  Also in some environments, the malfunctioning
   of a control system (like temperature control) needs to be reported
   in the shortest possible time.  Complex control systems can
   misbehave, and their critical status reporting and safety algorithms
   need to be basic and robust and perform even in critical conditions.

   Building Automation solutions are deployed in some cases in newly
   designed buildings, in other cases it might be over existing
   infrastructures.  In the first case, there is a broader range of
   possible solutions, which can be planned for the infrastructure of
   the building.  In the second case the solution needs to be deployed
   over an existing structure taking into account factors like existing
   wiring, distance limitations, the propagation of radio signals over
   walls and floors.  As a result, some of the existing WLAN solutions
   (e.g., IEEE 802.11 or IEEE 802.15) may be deployed.  In mission-
   critical or security sensitive environments and in cases where link
   failures happen often, topologies that allow for reconfiguration of
   the network and connection continuity may be required.  Some of the
   sensors deployed in building automation may be very simple
   constrained devices for which class 0 or class 1 may be assumed.

   For lighting applications, groups of lights must be defined and
   managed.  Commands to a group of light must arrive within 200 ms at
   all destinations.  The installation and operation of a building
   network has different requirements.  During the installation, many
   stand-alone networks of a few to 100 nodes co-exist without a



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   connection to the backbone.  During this phase, the nodes are
   identified with a network identifier related to their physical
   location.  Devices are accessed from an installation tool to connect
   them to the network in a secure fashion.  During installation, the
   setting of parameters to common values to enable interoperability may
   occur (e.g., Trickle parameter values).  During operation, the
   networks are connected to the backbone while maintaining the network
   identifier to physical location relation.  Network parameters like
   address and name are stored in DNS.  The names can assist in
   determining the physical location of the device.

3.7.  Home Automation

   Home automation includes the control of lighting, heating,
   ventilation, air conditioning, appliances, entertainment and home
   security devices to improve convenience, comfort, energy efficiency,
   and security.  It can be seen as a residential extension of building
   automation.  However, unlike a building automation system, the
   infrastructure in a home is operated in a considerably more ad-hoc
   manner, with no centralized management system akin to a Building
   Automation System (BAS) available.

   Home automation networks need a certain amount of configuration
   (associating switches or sensors to actors) that is either provided
   by electricians deploying home automation solutions, by third party
   home automation service providers (e.g., small specialized companies
   or home automation device manufacturers) or by residents by using the
   application user interface provided by home automation devices to
   configure (parts of) the home automation solution.  Similarly,
   failures may be reported via suitable interfaces to residents or they
   might be recorded and made available to services providers in charge
   of the maintenance of the home automation infrastructure.

   The management responsibility lies either with the residents or it
   may be outsourced to electricians and/or third parties providing
   management of home automation solutions as a service.  A varying
   combination of electricians, service providers or the residents may
   be responsible for different aspects of managing the infrastructure.
   The time scale for failure detection and resolution is in many cases
   likely counted in hours to days.

3.8.  Transport Applications

   Transport Application is a generic term for the integrated
   application of communications, control, and information processing in
   a transportation system.  Transport telematics or vehicle telematics
   are used as a term for the group of technologies that support
   transportation systems.  Transport applications running on such a



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   transportation system cover all modes of the transport and consider
   all elements of the transportation system, i.e. the vehicle, the
   infrastructure, and the driver or user, interacting together
   dynamically.  The overall aim is to improve decision making, often in
   real time, by transport network controllers and other users, thereby
   improving the operation of the entire transport system.  As such,
   transport applications can be seen as one of the important M2M
   service scenarios with the involvement of manifold small devices.

   The definition encompasses a broad array of techniques and approaches
   that may be achieved through stand-alone technological applications
   or as enhancements to other transportation communication schemes.
   Examples for transport applications are inter and intra vehicular
   communication, smart traffic control, smart parking, electronic toll
   collection systems, logistic and fleet management, vehicle control,
   and safety and road assistance.

   As a distributed system, transport applications require an end-to-end
   management of different types of networks.  It is likely that
   constrained devices in a network (e.g. a moving in-car network) have
   to be controlled by an application running on an application server
   in the network of a service provider.  Such a highly distributed
   network including mobile devices on vehicles is assumed to include a
   wireless access network using diverse long distance wireless
   technologies such as WiMAX, 3G/LTE or satellite communication, e.g.
   based on an embedded hardware module.  As a result, the management of
   constrained devices in the transport system might be necessary to
   plan top-down and might need to use data models obliged from and
   defined on the application layer.  The assumed device classes in use
   are mainly C2 devices.  In cases, where an in-vehicle network is
   involved, C1 devices with limited capabilities and a short-distance
   constrained radio network, e.g.  IEEE 802.15.4 might be used
   additionally.

   Management responsibility typically rests within the organization
   running the transport application.  The constrained devices in a
   moving transport network might be initially configured in a factory
   and a reconfiguration might be needed only rarely.  New devices might
   be integrated in an ad-hoc manner based on self-management and
   -configuration capabilities.  Monitoring and data exchange might be
   necessary to do via a gateway entity connected to the back-end
   transport infrastructure.  The devices and entities in the transport
   infrastructure need to be monitored more frequently and can be able
   to communicate with a higher data rate.  The connectivity of such
   entities does not necessarily need to be wireless.  The time scale
   for detecting and recording failures in a moving transport network is
   likely measured in hours and repairs might easily take days.  It is
   likely that a self-healing feature would be used locally.



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3.9.  Vehicular Networks

   Networks involving mobile nodes, especially transport vehicles, are
   emerging.  Such networks are used to provide inter-vehicle
   communication services, or even tracking of mobile assets, to develop
   intelligent transportation systems and drivers and passengers
   assistance services.  Constrained devices are deployed within a
   larger single entity, the vehicle, and must be individually managed.

   Vehicles can be either private, belonging to individuals or private
   companies, or public transportation.  Scenarios consisting of
   vehicle-to-vehicle ad-hoc networks, a wired backbone with wireless
   last hops, and hybrid vehicle-to-road communications are expected to
   be common.

   Besides the access control and security, depending on the type of
   vehicle and service being provided, it would be important for a NMS
   to be able to function with different architectures, since different
   manufacturers might have their own proprietary systems.

   Unlike some mobile networks, most vehicular networks are expected to
   have specific patterns in the mobility of the nodes.  Such patterns
   could possibly be exploited, managed and monitored by the NMS.

   The challenges in the management of vehicles in a mobile application
   are manifold.  Firstly, the issues caused through the device mobility
   need to be taken into consideration.  The up-to-date position of each
   node in the network should be reported to the corresponding
   management entities, since the nodes could be moving within or
   roaming between different networks.  Secondly, a variety of
   troubleshooting information, including sensitive location
   information, needs to be reported to the management system in order
   to provide accurate service to the customer.

   The NMS must also be able to handle partitioned networks, which would
   arise due to the dynamic nature of traffic resulting in large inter-
   vehicle gaps in sparsely populated scenarios.  Constant changes in
   topology must also be contended with.

   Auto-configuration of nodes in a vehicular network remains a
   challenge since based on location, and access network, the vehicle
   might have different configurations that must be obtained from its
   management system.  Operating configuration updates, while in remote
   networks also needs to be considered in the design of a network
   management system."






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3.10.  Community Network Applications

   Community networks are comprised of constrained routers in a multi-
   hop mesh topology, communicating over a lossy, and often wireless
   channel.  While the routers are mostly non-mobile, the topology may
   be very dynamic because of fluctuations in link quality of the
   (wireless) channel caused by, e.g., obstacles, or other nearby radio
   transmissions.  Depending on the routers that are used in the
   community network, the resources of the routers (memory, CPU) may be
   more or less constrained - available resources may range from only a
   few kilobytes of RAM to several megabytes or more, and CPUs may be
   small and embedded, or more powerful general-purpose processors.
   Examples of such community networks are the FunkFeuer network
   (Vienna, Austria), FreiFunk (Berlin, Germany), Seattle Wireless
   (Seattle, USA), and AWMN (Athens, Greece).  These community networks
   are public and non-regulated, allowing their users to connect to each
   other and - through an uplink to an ISP - to the Internet.  No fee,
   other than the initial purchase of a wireless router, is charged for
   these services.  Applications of these community networks can be
   diverse, e.g., location based services, free Internet access, file
   sharing between users, distributed chat services, social networking
   etc, video sharing etc.

   As an example of a community network, the FunkFeuer network comprises
   several hundred routers, many of which have several radio interfaces
   (with omnidirectional and some directed antennas).  The routers of
   the network are small-sized wireless routers, such as the Linksys
   WRT54GL, available in 2011 for less than 50 Euros.  These routers,
   with 16 MB of RAM and 264 MHz of CPU power, are mounted on the
   rooftops of the users.  When new users want to connect to the
   network, they acquire a wireless router, install the appropriate
   firmware and routing protocol, and mount the router on the rooftop.
   IP addresses for the router are assigned manually from a list of
   addresses (because of the lack of autoconfiguration standards for
   mesh networks in the IETF).

   While the routers are non-mobile, fluctuations in link quality
   require an ad hoc routing protocol that allows for quick convergence
   to reflect the effective topology of the network (such as NHDP
   [RFC6130] and OLSRv2 [I-D.ietf-manet-olsrv2] developed in the MANET
   WG).  Usually, no human interaction is required for these protocols,
   as all variable parameters required by the routing protocol are
   either negotiated in the control traffic exchange, or are only of
   local importance to each router (i.e. do not influence
   interoperability).  However, external management and monitoring of an
   ad hoc routing protocol may be desirable to optimize parameters of
   the routing protocol.  Such an optimization may lead to a more stable
   perceived topology and to a lower control traffic overhead, and



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   therefore to a higher delivery success ratio of data packets, a lower
   end-to-end delay, and less unnecessary bandwidth and energy usage.

   Different use cases for the management of community networks are
   possible:

   o  One single Network Management Station, e.g. a border gateway
      providing connectivity to the Internet, requires managing or
      monitoring routers in the community network, in order to
      investigate problems (monitoring) or to improve performance by
      changing parameters (managing).  As the topology of the network is
      dynamic, constant connectivity of each router towards the
      management station cannot be guaranteed.  Current network
      management protocols, such as SNMP and Netconf, may be used (e.g.,
      using interfaces such as the NHDP-MIB [RFC6779]).  However, when
      routers in the community network are constrained, existing
      protocols may require too many resources in terms of memory and
      CPU; and more importantly, the bandwidth requirements may exceed
      the available channel capacity in wireless mesh networks.
      Moreover, management and monitoring may be unfeasible if the
      connection between the network management station and the routers
      is frequently interrupted.

   o  A distributed network monitoring, in which more than one
      management station monitors or manages other routers.  Because
      connectivity to a server cannot be guaranteed at all times, a
      distributed approach may provide a higher reliability, at the cost
      of increased complexity.  Currently, no IETF standard exists for
      distributed monitoring and management.

   o  Monitoring and management of a whole network or a group of
      routers.  Monitoring the performance of a community network may
      require more information than what can be acquired from a single
      router using a network management protocol.  Statistics, such as
      topology changes over time, data throughput along certain routing
      paths, congestion etc., are of interest for a group of routers (or
      the routing domain) as a whole.  As of 2012, no IETF standard
      allows for monitoring or managing whole networks, instead of
      single routers.

3.11.  Military Operations

   The challenges of configuration and monitoring of networks faced by
   military agencies can be different from the other use cases since the
   requirements and operating conditions of military networks are quite
   different.

   With technology advancements, military networks nowadays have become



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   large and consist of varieties of different types of equipment that
   run different protocols and tools that obviously increase complexity
   of the tactical networks.  In many scenarios, configurations are,
   most likely, manually performed.  Furthermore, some legacy and even
   modern devices do not even support IP networking.  Majority of
   protocols and tools developed by vendors that are being used are
   proprietary which makes integration more difficult.

   The main reason for this disjoint operation scenario is that most
   military equipment is developed with specific tasks requirements in
   mind, rather than interoperability of the varied equipment types.
   For example, the operating conditions experienced by high altitude
   equipment is significantly different from that used in desert
   conditions and interoperation of tactical equipment with
   telecommunication equipment was not an expected outcome.

   Currently, most military networks operate with a fixed Network
   Operations Center (NOC) that physically manages the configuration and
   evaluation of all field devices.  Once configured, the devices might
   be deployed in fixed or mobile scenarios.  Any configuration changes
   required would need to be appropriately encrypted and authenticated
   to prevent unauthorized access.

   Hierarchical management of devices is a common requirement of
   military operations as well since local managers may need to respond
   to changing conditions within their platoon, regiment, brigade,
   division or corps.  The level of configuration management available
   at each hierarchy must also be closely governed.

   Since most military networks operate in hostile environments, a high
   failure rate and disconnection rate should be tolerated by the NMS,
   which must also be able to deal with multiple gateways and disjoint
   management protocols.

   Multi-national military operations are becoming increasingly common,
   requiring the interoperation of a diverse set of equipment designed
   with different operating conditions in mind.  Furthermore, different
   militaries are likely to have a different set of standards, best
   practices, rules and regulation, and implementation approaches that
   may contradict or conflict with each other.  The NMS should be able
   to detect these and handle them in an acceptable manner, which may
   require human intervention.









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4.  IANA Considerations

   This document does not introduce any new code-points or namespaces
   for registration with IANA.

   Note to RFC Editor: this section may be removed on publication as an
   RFC.












































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5.  Security Considerations

   In several use cases, constrained devices are deployed in unsafe
   environments, where attackers can gain physical access to the
   devices.  As a consequence, it is crucial to properly protect any
   security credentials that may be stored on the device (e.g., by using
   hardware protection mechanisms).  Furthermore, it is important that
   any credentials leeking from a single device do not simplify the
   attack on other (similar) devices.  In particular, security
   credentials should never be shared.

   Since constrained devices often have limited computational resources,
   care should be taken in choosing efficient but cryptographically
   strong crytographic algorithms.  Designers of constrained devices
   that have a long expected lifetime need to ensure that cryptographic
   algorithms can be updated once devices have been deployed.  The
   ability to perform secure firmware and software updates is an
   important management requirement.

   Several use cases generate sensitive data or require the processing
   of sensitive data.  It is therefore an important requirement to
   properly protect access to the data in order to protect the privacy
   of humans using Internet-enabled devices.  For certain types of data,
   protection during the transmission over the network may not be
   sufficient and methods should be investigated that provide protection
   of data while it is cached or stored (e.g., when using a store-and-
   forward transport mechanism).
























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6.  Contributors

   Following persons made significant contributions to and reviewed this
   document:

   o  Ulrich Herberg (Fujitsu Laboratories of America) contributed the
      Section 3.10 on Community Network Applications.

   o  Peter van der Stok contributed to Section 3.6 on Building
      Automation.

   o  Zhen Cao contributed to Section 2.2 Mobile Access Technologies.

   o  Gilman Tolle contributed the Section 3.4 on Automated Metering
      Infrastructure.

   o  James Nguyen and Ulrich Herberg contributed to Section 3.11 on
      Military operations.

































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7.  Acknowledgments

   Following persons reviewed and provided valuable comments to
   different versions of this document:

   Dominique Barthel, Carsten Bormann, Zhen Cao, Benoit Claise, Bert
   Greevenbosch, Ulrich Herberg, James Nguyen, Zach Shelby, and Peter
   van der Stok.

   The editors would like to thank the reviewers and the participants on
   the Coman maillist for their valuable contributions and comments.








































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8.  Informative References

   [RFC6130]  Clausen, T., Dearlove, C., and J. Dean, "Mobile Ad Hoc
              Network (MANET) Neighborhood Discovery Protocol (NHDP)",
              RFC 6130, April 2011.

   [RFC6568]  Kim, E., Kaspar, D., and JP. Vasseur, "Design and
              Application Spaces for IPv6 over Low-Power Wireless
              Personal Area Networks (6LoWPANs)", RFC 6568, April 2012.

   [RFC6779]  Herberg, U., Cole, R., and I. Chakeres, "Definition of
              Managed Objects for the Neighborhood Discovery Protocol",
              RFC 6779, October 2012.

   [RFC6988]  Quittek, J., Chandramouli, M., Winter, R., Dietz, T., and
              B. Claise, "Requirements for Energy Management", RFC 6988,
              September 2013.

   [I-D.ietf-lwig-terminology]
              Bormann, C., Ersue, M., and A. Keranen, "Terminology for
              Constrained Node Networks", draft-ietf-lwig-terminology-07
              (work in progress), February 2014.

   [I-D.ietf-eman-framework]
              Claise, B., Schoening, B., and J. Quittek, "Energy
              Management Framework", draft-ietf-eman-framework-15 (work
              in progress), February 2014.

   [I-D.ietf-manet-olsrv2]
              Clausen, T., Dearlove, C., Jacquet, P., and U. Herberg,
              "The Optimized Link State Routing Protocol version 2",
              draft-ietf-manet-olsrv2-19 (work in progress), March 2013.

   [COM-REQ]  Ersue, M., "Constrained Management: Problem statement and
              Requirements", draft-ietf-opsawg-coman-probstate-reqs
              (work in progress), January 2014.















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Appendix A.  Open Issues

   o  Section 3.11 should be replaced by a different use case motivating
      similar requirements or perhaps deleted if the IETF prefers to not
      work on specific requirements coming from military use cases.

   o  Section 3.8 and Section 3.9 should be merged.












































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Appendix B.  Change Log

B.1.  draft-ietf-opsawg-coman-use-cases-00 -
      draft-ietf-opsawg-coman-use-cases-01

   o  Reordered some use cases to improve the flow.

   o  Added "Vehicular Networks".

   o  Shortened the Military Operations use case.

   o  Started adding substance to the security considerations section.

B.2.  draft-ersue-constrained-mgmt-03 -
      draft-ersue-opsawg-coman-use-cases-00

   o  Reduced the terminology section for terminology addressed in the
      LWIG and Coman Requirements drafts.  Referenced the other drafts.

   o  Checked and aligned all terminology against the LWIG terminology
      draft.

   o  Spent some effort to resolve the intersection between the
      Industrial Application, Home Automation and Building Automation
      use cases.

   o  Moved section section 3.  Use Cases from the companion document
      [COM-REQ] to this draft.

   o  Reformulation of some text parts for more clarity.

B.3.  draft-ersue-constrained-mgmt-02-03

   o  Extended the terminology section and removed some of the
      terminology addressed in the new LWIG terminology draft.
      Referenced the LWIG terminology draft.

   o  Moved Section 1.3. on Constrained Device Classes to the new LWIG
      terminology draft.

   o  Class of networks considering the different type of radio and
      communication technologies in use and dimensions extended.

   o  Extended the Problem Statement in Section 2. following the
      requirements listed in Section 4.

   o  Following requirements, which belong together and can be realized
      with similar or same kind of solutions, have been merged.



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      *  Distributed Management and Peer Configuration,

      *  Device status monitoring and Neighbor-monitoring,

      *  Passive Monitoring and Reactive Monitoring,

      *  Event-driven self-management - Self-healing and Periodic self-
         management,

      *  Authentication of management systems and Authentication of
         managed devices,

      *  Access control on devices and Access control on management
         systems,

      *  Management of Energy Resources and Data models for energy
         management,

      *  Software distribution (group-based firmware update) and Group-
         based provisioning.

   o  Deleted the empty section on the gaps in network management
      standards, as it will be written in a separate draft.

   o  Added links to mentioned external pages.

   o  Added text on OMA M2M Device Classification in appendix.

B.4.  draft-ersue-constrained-mgmt-01-02

   o  Extended the terminology section.

   o  Added additional text for the use cases concerning deployment
      type, network topology in use, network size, network capabilities,
      radio technology, etc.

   o  Added examples for device classes in a use case.

   o  Added additional text provided by Cao Zhen (China Mobile) for
      Mobile Applications and by Peter van der Stok for Building
      Automation.

   o  Added the new use cases 'Advanced Metering Infrastructure' and
      'MANET Concept of Operations in Military'.

   o  Added the section 'Managing the Constrainedness of a Device or
      Network' discussing the needs of very constrained devices.




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   o  Added a note that the requirements in [COM-REQ] need to be seen as
      standalone requirements and the current document does not
      recommend any profile of requirements.

   o  Added a section in [COM-REQ] for the detailed requirements on
      constrained management matched to management tasks like fault,
      monitoring, configuration management, Security and Access Control,
      Energy Management, etc.

   o  Solved nits and added references.

   o  Added Appendix A on the related development in other bodies.

   o  Added Appendix B on the work in related research projects.

B.5.  draft-ersue-constrained-mgmt-00-01

   o  Splitted the section on 'Networks of Constrained Devices' into the
      sections 'Network Topology Options' and 'Management Topology
      Options'.

   o  Added the use case 'Community Network Applications' and 'Mobile
      Applications'.

   o  Provided a Contributors section.

   o  Extended the section on 'Medical Applications'.

   o  Solved nits and added references.






















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Authors' Addresses

   Mehmet Ersue (editor)
   Nokia Solutions and Networks

   Email: mehmet.ersue@nsn.com


   Dan Romascanu
   Avaya

   Email: dromasca@avaya.com


   Juergen Schoenwaelder
   Jacobs University Bremen

   Email: j.schoenwaelder@jacobs-university.de


   Anuj Sehgal
   Jacobs University Bremen

   Email: a.sehgal@jacobs-university.de



























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