Delay-Tolerant Networking E. Birrane
Internet-Draft Johns Hopkins Applied Physics Laboratory
Intended status: Informational March 13, 2017
Expires: September 14, 2017
Asynchronous Management Architecture
draft-birrane-dtn-ama-05
Abstract
This document describes an asynchronous management architecture (AMA)
suitable for providing application-level network management services
in a challenged networking environment. Challenged networks are
those that require fault protection, configuration, and performance
reporting while unable to provide humans-in-the-loop with synchronous
feedback or otherwise preserve transport-layer sessions. In such a
context, networks must exhibit behavior that is both determinable and
autonomous while maintaining compatibility with existing network
management protocols and operational concepts.
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 September 14, 2017.
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to this document. Code Components extracted from this document must
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Purpose . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3. Requirements Language . . . . . . . . . . . . . . . . . . 4
1.4. Organization . . . . . . . . . . . . . . . . . . . . . . 4
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 5
3. Motivation . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1. Challenged Networks . . . . . . . . . . . . . . . . . . . 6
3.2. Current Approaches and Their Limitations . . . . . . . . 7
4. Service Definitions . . . . . . . . . . . . . . . . . . . . . 8
4.1. Configuration . . . . . . . . . . . . . . . . . . . . . . 9
4.2. Reporting . . . . . . . . . . . . . . . . . . . . . . . . 9
4.3. Autonomous Parameterized Procedure Calls . . . . . . . . 10
4.4. Administration . . . . . . . . . . . . . . . . . . . . . 10
5. Desirable Properties . . . . . . . . . . . . . . . . . . . . 11
5.1. Intelligent Push of Information . . . . . . . . . . . . . 11
5.2. Minimize Message Size Not Node Processing . . . . . . . . 12
5.3. Absolute Data Identification . . . . . . . . . . . . . . 12
5.4. Custom Data Definition . . . . . . . . . . . . . . . . . 12
5.5. Autonomous Operation . . . . . . . . . . . . . . . . . . 13
6. Roles and Responsibilities . . . . . . . . . . . . . . . . . 13
6.1. Agent Responsibilities . . . . . . . . . . . . . . . . . 14
6.2. Manager Responsibilities . . . . . . . . . . . . . . . . 15
7. Logical Data Model . . . . . . . . . . . . . . . . . . . . . 15
7.1. EDDs, VARs, and Reporting . . . . . . . . . . . . . . . . 16
7.2. Controls and Macros . . . . . . . . . . . . . . . . . . . 17
7.3. Rules . . . . . . . . . . . . . . . . . . . . . . . . . . 17
7.4. Operators and Literals . . . . . . . . . . . . . . . . . 18
8. System Model . . . . . . . . . . . . . . . . . . . . . . . . 18
8.1. Control and Data Flows . . . . . . . . . . . . . . . . . 18
8.2. Control Flow by Role . . . . . . . . . . . . . . . . . . 19
8.2.1. Notation . . . . . . . . . . . . . . . . . . . . . . 19
8.2.2. Serialized Management . . . . . . . . . . . . . . . . 20
8.2.3. Multiplexed Management . . . . . . . . . . . . . . . 21
8.2.4. Data Fusion . . . . . . . . . . . . . . . . . . . . . 23
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 24
10. Security Considerations . . . . . . . . . . . . . . . . . . . 24
11. Informative References . . . . . . . . . . . . . . . . . . . 24
Author's Address . . . . . . . . . . . . . . . . . . . . . . . . 25
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1. Introduction
The Asynchronous Management Architecture (AMA) provides application-
layer network management services over links where delivery delays
prevent timely communications between a network operator and a
managed device. These delays may be caused by long signal
propagations or frequent link disruptions (such as described in
[RFC4838]) or by non-environmental factors such as unavailability of
network operators, administrative delays, or delays caused by
quality-of-service prioritizations and service-level agreements.
1.1. Purpose
This document describes the motivation, service definitions,
desirable properties, roles/responsibilities, system model, and
logical data model that form the AMA. These descriptions should be
of sufficient specificity that implementations conformant to this
architecture will operate successfully in a challenged networking
environment.
This document is not a prescriptive standardization of a physical
data model or protocol. Instead, it serves as informative guidance
to authors of such models and protocols.
An AMA is necessary as the assumptions inherent to the architecture
and design of synchronous management tools and techniques are not
valid in challenged network scenarios. In these scenarios,
synchronous approaches either patiently wait for periods of bi-
directional connectivity or require the investment of significant
time and resources to evolve a challenged network into a well-
connected, low-latency network. In some cases such evolution is
merely a costly way to over-resource a network. In other cases, such
evolution is impossible given physical limitations imposed by signal
propagation delays, power, transmission technologies, and other
phenomena. Asynchronous management of asynchronous networks enables
large-scale deployments, distributed technical capabilities, and
reduced deployment and operations costs.
The rationale and motivation for asynchronous management is captured
in [BIRRANE1], [BIRRANE2],[BIRRANE3]. The properties and feasibility
of such a system are taken from prototyping work done in accordance
with [I-D.irtf-dtnrg-dtnmp].
1.2. Scope
It is assumed that any challenged network where network management
would be usefully applied supports basic services (where necessary)
such as naming, addressing, integrity, confidentiality,
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authentication, fragmentation, and traditional network/session layer
functions. Therefore, these items are outside of the scope of the
AMA and not covered in this document.
While possible that a challenged network may interface with an
unchallenged network, this document does not address the concept of
network management compatibility with synchronous approaches.
1.3. 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 [RFC2119].
1.4. Organization
The remainder of this document is organized into seven sections that,
together, describe an AMA suitable for enterprise management of
asynchronous networks: terminology, motivation, service definitions,
desirable properties, roles/responsibilities, logical data model, and
system model. The description of each section is as follows.
o Terminology - This section identifies those terms critical to
understanding the proper operation of the AMA. Whenever possible,
these terms align in both word selection and meaning with their
analogs from other management protocols.
o Motivation - This section provides an overall motivation for this
work as providing a novel and useful alternative to current
network management approaches. Specifically, this section
describes common network functions and how synchronous mechanisms
fail to provide these functions in an asynchronous environment.
o Service Definitions - This section defines asynchronous network
management services in terms of terminology, scope, and impact.
o Desirable Properties - This section identifies the properties to
which an asynchronous management system should adhere to
effectively implement service definitions in an asynchronous
environment. These properties guide the subsequent definition of
the system and logical models that comprise the AMA.
o Roles and Responsibilities - This section identifies the roles in
the AMA and their associated responsibilities. It provides the
terminology and context for discussing how network management
services interact.
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o Logical Data Model - This section describes the kinds of data that
should be represented in deployment asynchronous management
system.
o System Model - This section describes data flows amongst various
defined Actor roles. These flows capture how the AMA system works
to provide asynchronous network management services in accordance
with defined desirable properties.
2. Terminology
o Actor - A software service running on either managed or managing
devices for the purpose of implementing management protocols
between such devices. Actors may implement the "Manager" role,
"Agent" role, or both.
o Agent Role (or Agent) - The role associated with a managed device,
responsible for reporting performance data, enforcing
administrative policies, and accepting/performing actions. Agents
exchange information with Managers operating either on the same
device or on a remote managing device.
o Externally Defined Data (EDD) - Information made available to an
Agent by a managed device, but not computed directly by the Agent.
o Variable (VAR) - Information that is computed by an Agent,
typically as a function of EDD values and/or other Variables.
o Controls (CTRLs) - Operations that may be undertaken by an Actor
to change the behavior, configuration, or state of an application
or protocol managed by an AMP.
o Literals (LIT) - Constants, enumerations, and other immutable
definitions.
o Macros - A named, ordered collection of Controls.
o Manager - A role associated with a managing device responsible for
configuring the behavior of, and receiving information from,
Agents. Managers interact with one or more Agents located on the
same device and/or on remote devices in the network.
o Operator (OP) - The enumeration and specification of a
mathematical function used to calculate computed data definitions
and construct expressions to calculate state.
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o Report (RPT) - A named, typed, ordered collection of data values
gathered by one or more Agents and provided to one or more
Managers.
o Rule - A unit of autonomous specification that provides a
stimulus-response relationship between time or state on an Agent
and the Controls to be run as a result of that time or state.
3. Motivation
Challenged networks, to include networks challenged by administrative
or policy delays, cannot guarantee capabilities required to enable
synchronous management techniques. These capabilities include high-
rate, highly-available data, round-trip data exchange, and operators
"in-the-loop". The inability of current approaches to provide
network management services in a challenged network motivates the
need for a new network management architecture focused on
asynchronous, open-loop, autonomous control of network components.
3.1. Challenged Networks
A growing variety of link-challenged networks support packetization
to increase data communications reliability without otherwise
guaranteeing a simultaneous end-to-end path. Examples of such
networks include Mobile Ad-Hoc Networks (MANets), Vehicular Ad-Hoc
Networks (VANets), Space-Terrestrial Internetworks (STINTs), and
heterogeneous networking overlays. Links in such networks are often
unavailable due to attenuations, propagation delays, occultation, and
other limitations imposed by energy and mass considerations. Data
communications in such networks rely on store-and-forward and other
queueing strategies to wait for the connectivity necessary to
usefully advance a packet along its route.
Similarly, there also exist well-resourced networks that incur high
message delivery delays due to non-environmental limitations. For
example, networks whose operations centers are understaffed or where
data volume and management requirements exceed the real-time
cognitive load of operators or the associated operations console
software support. Also, networks where policy restricts user access
to existing bandwidth creates situations functionally similar to link
disruption and delay.
Independent of the reason, when a node experiences an inability to
communicate it must rely on autonomous mechanisms to ensure its safe
operation and ability to usefully re-join the network at a later
time. In cases of sparsely-populated networks, there may never be a
practical concept of "the connected network" as most nodes may be
disconnected most of the time. In such environments, defining a
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network in terms of instantaneous connectivity becomes impractical or
impossible.
Specifically, challenged networks exhibit the following properties
that may violate assumptions built into current approaches to
synchronous network management.
o Links may be uni-directional.
o Bi-directional links may have asymmetric data rates.
o No end-to-end path is guaranteed to exist at any given time
between any two nodes.
o Round-trip communications between any two nodes within any given
time window may be impossible.
3.2. Current Approaches and Their Limitations
Network management tools in unchallenged networks provide mechanisms
for communicating locally-collected data from Agents to Managers,
typically using a "pull" mechanism where data must be explicitly
requested by a Manager in order to be transmitted by an Agent.
Management approaches that rely on timely data exchange, such as
those that rely on negotiated sessions or other synchronized
acknowledgment, do not function in challenged network environments.
Familiar examples of TCP/IP based management via closed-loop,
synchronous messaging do not work when network disruptions increase
in frequency and severity. While no protocol delivers data in the
absence of a networking link, protocols that eliminate or drastically
reduce overhead and end-point coordination require smaller
transmission windows and continue to function when confronted with
scaling delays and disruptions in the network.
A legacy method for management in unchallenged networks today is the
Simple Network Management Protocol (SNMP) [RFC3416]. SNMP utilizes a
request/response model to set and retrieve data values such as host
identifiers, link utilizations, error rates, and counters between
application software on Agents and Managers. Data may be directly
sampled or consolidated into representative statistics.
Additionally, SNMP supports a model for asynchronous notification
messages, called traps, based on predefined triggering events. Thus,
Managers can query Agents for status information, send new
configurations, and be informed when specific events have occurred.
Traps and queryable data are defined in one or more Managed
Information Bases (MIBs) which define the information for a
particular data standard, protocol, device, or application.
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While there is a large installation base for SNMP there are several
aspects of the protocol that make in inappropriate for use in a
challenged networking environment. SNMP relies on sessions with low
round-trip latency to support its "pull" model. The SNMP trap model
provides some Agent-side processing, but with very low fidelity and
traps are typically "fire and forget" requiring the underlying
transport to support reliable, in-order message delivery. Adaptive
modifications to SNMP to support challenged networks would alter the
basic function of the protocol (data models, control flows, and
syntax) so as to be functionally incompatible with existing SNMP
installations. Therefore, this approach is not suitable for an
asynchronous network management system.
The Network Configuration Protocol (NETCONF) provides device-level
configuration capabilities [RFC6241] to replace vendor-specific
command line interface (CLI) configuration software. The XML-based
protocol provides a remote procedure call (RPC) syntax such that any
exposed functionality on an Agent can be exercised via a software
application interface. NETCONF places no specific functional
requirements or constraints on the capabilities of the Agent, which
makes it a very flexible tool for configuring a homogeneous network
of devices.
NETCONF places specific constraints on any underlying transport
protocol: a long-lived, reliable, low-latency sequenced data delivery
session. This is a fundamental requirement given the RPC-nature of
the operating concept, and it is unsustainable in a challenged
network. Aspects of the data modeling associated with NETCONF may
apply to an asynchronous network management system, such that some
modeling tools may be used, even if the network control plane cannot.
Just as the concept of a loosely-confederated set of nodes changes
the definition of a network, it also changes the operational concept
of what it means to manage a network. When a network stops being a
single entity exhibiting a single behavior, "network management"
becomes large-scale "node management". Individual nodes must share
the burden of implementing desirable behavior without reliance on a
single oracle of configuration or other coordinating function such as
an operator-in-the-loop.
4. Service Definitions
This section identifies the services that must exist between Managers
and Agents within an AMA. These services include configuration,
reporting, parameterized control, and administration.
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4.1. Configuration
Configuration services update Agent data associated with managed
applications and protocols. Some configuration data might be defined
in the context of an application or protocol, such that any network
using that application or protocol would understand that data. Other
configuration data may be defined tactically for use in a specific
network deployment and not available to other networks even if they
use the same applications or protocols.
New configurations received by an Agent must be validated to ensure
that they do not conflict with other configurations or would
otherwise prevent the Agent from effectively working with other
Actors in its region. With no guarantee of round-trip data exchange,
Agents cannot rely on remote Managers to correct erroneous or stale
configurations from harming the flow of data through a challenged
network.
Examples of configuration service behavior include the following.
o Creating a new datum as a function of other well-known data:
C = A + B.
o Creating a new report as a unique, ordered collection of known
data:
RPT = {A, B, C}.
o Storing pre-defined, parameterized responses to potential future
conditions:
IF (X > 3) THEN RUN CMD(PARM).
4.2. Reporting
Reporting services populate report templates with values collected or
computed by an Agent. The resultant reports are sent to one or more
Managers by the Agent. The term "reporting" is used in place of the
term "monitoring", as monitoring implies a timeliness and regularity
that cannot be guaranteed by a challenged network. Reports sent by
an Agent provide best-effort information to receiving Managers.
Since a Manager is not actively "monitoring" an Agent, the Agent must
make its own determination on when to send what Reports based on its
own local time and state information. Agents should produce Reports
of varying fidelity and with varying frequency based on thresholds
and other information set as part of configuration services.
Examples of reporting service behavior include the following.
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o Generate Report R1 every hour (time-based production).
o Generate Report R2 when X > 3 (state-based production).
4.3. Autonomous Parameterized Procedure Calls
Similar to an RPC call, some mechanism MUST exist to allow a
procedure to be run on an Agent to effect behavior or otherwise
change the Agent's internal state. Since there is no guarantee that
a Manager will be in contact with an Agent at any given time, the
decisions of whether and when a procedure should be run MUST be made
locally and autonomously by the Agent. Two types of automation
triggers are identified in the AMA: triggers based on the general
state of the Agent and triggers based on an Agent's notion of time.
As such, the autonomous execution of procedures can be viewed as a
stimulus-response system, where the stimulus is the positive
evaluation of a state or time based predicate and the response is the
function to be executed.
The autonomous nature of procedure execution by an Agent implies that
the full suite of information necessary to run a procedure may not be
known by a Manager in advance. To address this situation, a
parameterization mechanism MUST be available so that required data
can be provided at the time of execution on the Agent rather than at
the time of definition/configuration by the Manager.
Autonomous, parameterized procedure calls provide a powerful
mechanism for Managers to "manage" an Agent asynchronously during
periods of no communication by pre-configuring responses to events
that may be encountered by the Agent at a future time.
Examples of potential behavior include the following.
o Updating local routing information based on instantaneous link
analysis.
o Managing storage on the device to enforce quotas.
o Applying or modifying local security policy.
4.4. Administration
Administration services enforce the potentially complex mapping of
configuration, reporting, and control services amongst Agents and
Managers in the network. Fine-grained access control specifying
which Managers may apply which services to which Agents may be
necessary in networks dealing with multiple administrative entities
or overlay networks crossing multiple administrative boundaries.
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Whitelists, blacklists, key-based infrastructures, or other schemes
may be used for this purpose.
Examples of administration service behavior include the following.
o Agent A1 only Sends reports for Protocol P1 to Manager M1.
o Agent A2 only accepts a configurations for Application Y from
Managers M2 and M3.
o Agent A3 accepts services from any Manager providing the proper
authentication token.
Note that the administrative enforcement of access control is
different from security services provided by the networking stack
carrying AMP messages.
5. Desirable Properties
This section describes those design properties that are desirable
when defining an architecture that must operate across challenged
links in a network. These properties ensure that network management
capabilities are retained even as delays and disruptions in the
network scale. Ultimately, these properties are the driving design
principles for the AMA.
5.1. Intelligent Push of Information
Pull management mechanisms require that a Manager send a query to an
Agent and then wait for the response to that query. This practice
implies a control-session between entities and increases the overall
message traffic in the network. Challenged networks cannot guarantee
timely roundtrip data-exchange and, in extreme cases, are comprised
solely of uni-directional links. Therefore, pull mechanisms must be
avoided in favor of push mechanisms.
Push mechanisms, in this context, refer to Agents making their own
determinations relating to the information that should be sent to
Managers. Such mechanisms do not require round-trip communications
as Managers do not request each reporting instance; Managers need
only request once, in advance, that information be produced in
accordance with a pre-determined schedule or in response to a pre-
defined state on the Agent. In this way information is "pushed" from
Agents to Managers and the push is "intelligent" because it is based
on some internal evaluation performed by the Agent.
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5.2. Minimize Message Size Not Node Processing
Protocol designers must balance message size versus message
processing time at sending and receiving nodes. Verbose
representations of data simplify node processing whereas compact
representations require additional activities to generate/parse the
compacted message. There is no asynchronous management advantage to
minimizing node processing time in a challenged network. However,
there is a significant advantage to smaller message sizes in such
networks. Compact messages require smaller periods of viable
transmission for communication, incur less re-transmission cost, and
consume less resources when persistently stored en-route in the
network. AMPs should minimize PDUs whenever practical, to include
packing and unpacking binary data, variable-length fields, and pre-
configured data definitions.
5.3. Absolute Data Identification
Elements within the management system must be uniquely identifiable
so that they can be individually manipulated. Identification schemes
that are relative to system configuration make data exchange between
Agents and Managers difficult as system configurations may change
faster than nodes can communicate.
Consider the following common technique for approximating an
associative array lookup. A manager wishing to do an associative
lookup for some key K1 will (1) query a list of array keys from the
agent, (2) find the key that matches K1 and infer the index of K1
from the returned key list, and (3) query the discovered index on the
agent to retrieve the desired data.
Ignoring the inefficiency of two pull requests, this mechanism fails
when the Agent changes its key-index mapping between the first and
second query. Rather than constructing an artificial mapping from K1
to an index, an AMP must provide an absolute mechanism to lookup the
value K1 without an abstraction between the Agent and Manager.
5.4. Custom Data Definition
Custom definition of new data from existing data (such as through
data fusion, averaging, sampling, or other mechanisms) provides the
ability to communicate desired information in as compact a form as
possible. Specifically, an Agent should not be required to transmit
a large data set for a Manager that only wishes to calculate a
smaller, inferred data set. The Agent should calculate the smaller
data set on its own and transmit that instead. Since the
identification of custom data sets is likely to occur in the context
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of a specific network deployment, AMPs must provide a mechanism for
their definition.
5.5. Autonomous Operation
AMA network functions must be achievable using only knowledge local
to the Agent. Rather than directly controlling an Agent, a Manager
configures an engine of the Agent to take its own action under the
appropriate conditions in accordance with the Agent's notion of local
state and time.
Such an engine may be used for simple automation of pre-defined tasks
or to support semi-autonomous behavior in determining when to run
tasks and how to configure or parameterize tasks when they are run.
Wholly autonomous operations MAY be supported where required.
Generally, autonomous operations should provide the following
benefits.
o Distributed Operation - The concept of pre-configuration allows
the Agent to operate without regular contact with Managers in the
system. The initial configuration (and periodic update) of the
system remains difficult in a challenged network, but an initial
synchronization on stimuli and responses drastically reduces needs
for centralized operations.
o Deterministic Behavior - Such behavior is necessary in critical
operational systems where the actions of a platform must be well
understood even in the absence of an operator in the loop.
Depending on the types of stimuli and responses, these systems may
be considered simple automation or semi-autonomous behavior, both
of which imply the ability of a frequently-out-of-contact Manager
to better predict the state of an Agent than if controls were to
be run by an independent, fully autonomous system.
o Engine-Based Behavior - Several operational systems are unable to
deploy "mobile code" based solutions due to network bandwidth,
memory or processor loading, or security concerns. Engine-based
approaches are preferred as they can be flexible without incurring
a set of problematic requirements or concerns.
6. Roles and Responsibilities
By definition, Agents reside on managed devices and Managers reside
on managing devices. This section describes how these roles
participate in the network management functions outlined in the prior
section.
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6.1. Agent Responsibilities
Application Support
Agents MUST collect all data, execute all procedures,
populate all reports and run operations required by each
application which the Agent claims to manage. Agents MUST
report supported applications so that Managers in a network
understands what information is understood by what Agent.
Local Data Collection
Agents MUST collect from local firmware (or other on-board
mechanisms) and report all data defined for the management of
applications for which they have been configured.
Autonomous Control
Agents MUST determine, without Manager intervention, whether
a procedure should be invoked. Agents MAY also invoke
procedures on other devices for which they act as proxy.
User Data Definition
Agents MUST provide mechanisms for operators in the network
to use configuration services to create customized data
definitions in the context of a specific network or network
use-case. Agents MUST allow for the creation, listing, and
removal of such definitions in accordance with whatever
security models are deployed within the particular network.
Where applicable, Agents MUST verify the validity of these
definitions when they are configured and respond in a way
consistent with the logging/error-handling policies of the
Agent and the network.
Autonomous Reporting
Agents MUST determine, without real-time Manager
intervention, whether and when to populate and transmit a
given report targeted to one or more Managers in the network.
Consolidate Messages
Agents SHOULD produce as few messages as possible when
sending information. For example, rather than sending
multiple messages, each with one report to a Manager, an
Agent SHOULD prefer to send a single message containing
multiple reports.
Regional Proxy
Agents MAY perform any of their responsibilities on behalf of
other network nodes that, themselves, do not have an Agent.
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In such a configuration, the Agent acts as a proxy for these
other network nodes.
6.2. Manager Responsibilities
Agent Capabilities Mapping
Managers MUST understand what applications are managed by the
various Agents with which they communicate. Managers should
not attempt to request, invoke, or refer to application
information for applications not managed by an Agent.
Data Collection
Managers MUST receive information from Agents by
asynchronously configuring the production of reports and then
waiting for, and collecting, responses from Agents over time.
Managers MAY try to detect conditions where Agent information
has not been received within operationally relevant timespans
and react in accordance with network policy.
Custom Definitions
Managers should provide the ability to define custom data
definitions. Any custom definitions MUST be transmitted to
appropriate Agents and these definitions MUST be remembered
to interpret the reporting of these custom values from Agents
in the future.
Data Translation
Managers should provide some interface to other network
management protocols. Managers MAY accomplish this by
accumulating a repository of push-data from high-latency
parts of the network from which data may be pulled by low-
latency parts of the network.
Data Fusion
Managers MAY support the fusion of data from multiple Agents
with the purpose of transmitting fused data results to other
Managers within the network. Managers MAY receive fused
reports from other Managers pursuant to appropriate security
and administrative configurations.
7. Logical Data Model
The AMA logical data model captures the types of information that
should be collected and exchanged to implement necessary roles and
responsibilities. The data model presented in this section does not
presuppose a specific mapping to a physical data model or encoding
technique; it is included to provide a way to logically reason about
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the types of data that should be exchanged in an asynchronously
managed network.
The elements of the AMA logical data model are described as follows.
7.1. EDDs, VARs, and Reporting
There are three fundamental representations of data in the AMA: (1)
data which are sampled/calculated external to the network management
system, (2) data which are calculated internal to the network
management system, and (3) ordered collections of data items used for
reporting.
Data that is sampled/calculated external to the network management
system is defined as "externally defined data" (EDD). EDD values
represent the most useful information in the management system as
they are provided by the applications or protocol being managed on
the Agent. It is RECOMMENDED that EDD values be strongly typed to
avoid issues with interpreting the data value. It is also
RECOMMENDED that the timeliness/staleness of the data value be
considered when using the data in the context of autonomous action on
the Agent.
Data that is calculated internal to the network management system is
defined as a "variable" (VAR). VARs allow the creation of new data
values for use in the network management system. New value
definitions are useful for storing user-defined information, storing
the results of complex calculations for easier re-use, and providing
a mechanism for combining information from multiple external sources.
It is RECOMMENDED that VARs be strongly typed to avoid issues with
interpreting the data value. In cases where a VAR definition relies
on other VAR definitions, mechanisms to prevent circular references
MUST be included in any actual data model or implementation.
Ordered collections of EDD values and VARs should be produced by
Agents and sent to Managers as a way of communicating Agent state.
Such an ordered collection is called a "report" (RPT). It is
RECOMMENDED that the structure of a RPT be given in a template that
can be synchronized between an Agent and a Manager so that RPTs
themselves do not need to be self-describing. A RPT may include EDD
values, VARs, and also other RPTs. In cases where a RPT includes
another RPT, mechanisms to prevent circular references MUST be
included in any actual data model or implementation.
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7.2. Controls and Macros
Low-latency, high-availability approaches to network management use
mechanisms such as (or similar to) remote procedure calls (RPCs) to
cause some action to be performed on an Agent. The AMA requires
similar capabilities, though without requiring that the Manager be in
the processing loop of the Agent.
A "control" (CTRL) represents a parameterized, pre-defined procedure
that can be run on an Agent. CTRLs do not have a return code as
there is not the same concept of sequential execution in an
asynchronous model. Parameters can be provided when running a
command from a Manager, pre-configured as part of an autonomy
response on the Agent, or auto-generated as needed on the Agent. The
success or failure of a control MAY be inferred by reports generated
for that purpose.
Often, a series of controls must be executed in concert to achieve a
particular outcome. A "macro" (MACRO) represents an ordered
collection of controls (or other macros). In cases where a MACRO
includes another MACRO, mechanisms to prevent circular references and
maximum nesting levels MUST be included in any actual data model or
implementation.
7.3. Rules
The AMA data model contains EDD values and VARs that capture the
state of applications on an Agent. The model also contains controls
and macros to perform actions on an Agent. A mechanism is needed to
relate these two capabilities; to perform an action on the Agent in
response to the state of the Agent.
One way of mapping Agent state to Agent actions is via a stimulus-
response system. A "rule" represents a stimulus-response pairing in
the following form.
IF predicate THEN response
The predicate is a logical expression that evaluates to true if the
rule stimulus is present and evaluates to false otherwise. The
response may be any control or macro known to the Agent. An example
of a time-based predicate is to perform some activity every 24 hours
(e.g., (((CUR_TIME - START_TIME) % 24Hrs) == 0)). An example of a
state-based predicate is to perform some activity if a given EDD
value exceeds a pre-defined threshold such as a measured temperature
exceeds 80 degrees centigrade (e.g., (TEMP > 80.0))
Rules should be allowed to construct their stimuli from the full set
of EDD values and VARs available to the network management system.
Similarly, macro responses should be allowed to include controls from
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all applications known by the Agent. This enables an expressive
capability to have multiple applications monitored and managed by the
Agent.
7.4. Operators and Literals
Actions such as computing a VAR value or describing a rule predicate
require calculating mathematical expressions. An element of an
expression will be one of four types of data: an EDD value, a VAR
value, a mathematical operations, and literal values.
An "operator" (OP) represents a mathematical operation in an
expression. OPs should support multiple operands based on the
operation supported. A common set of OPs SHOULD be defined for any
Agent and systems MAY choose to allow individual applications to
define new OPs to assist in the generation of new VAR values and
predicates for managing that application. OPs may be simple binary
operations such as "A + B" or more complex functions such as sin(A)
or avg(A,B,C,D).
A "literal" (LIT) represents a constant value, such as simple numbers
(e.g., 4), well-known mathematical numbers (e.g., PI, E), or other
useful data such as Epoch times. LITs should be strongly typed to
avoid any misinterpretation of their data value.
8. System Model
This section describes the notional data flows and control flows that
illustrate how Managers and Agents within an AMA cooperate to perform
network management services.
8.1. Control and Data Flows
The AMA identifies three significant data flows: control flows from
Managers to Agents, reports flows from Agents to Managers, and fusion
reports from Managers to other Managers. These data flows are
illustrated in Figure 1.
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AMA Control and Data Flows
+---------+ +------------------------+ +---------+
| Node A | | Node B | | Node C |
| | | | | |
|+-------+| |+-------+ +-------+| |+-------+|
|| ||=====>>||Manager|====>>| ||====>>|| ||
|| ||<<=====|| B |<<====|Agent B||<<====|| ||
|| || |+--++---+ +-------+| ||Manager||
|| Agent || +---||-------------------+ || C ||
|| A || || || ||
|| ||<<=========||==========================|| ||
|| ||===========++========================>>|| ||
|+-------+| |+-------+|
+---------+ +---------+
Figure 1
In this data flow, the Agent on node A receives Controls from
Managers on nodes B and C, and replies with Report Entries back to
these Managers. Similarly, the Agent on node B interacts with the
local Manager on node B and the remote Manager on node C. Finally,
the Manager on node B may fuse Report Entries received from Agents at
nodes A and B and send these fused Report Entries back to the Manager
on node C.
From this figure it is clear that there exist many-to-many
relationships amongst Managers, amongst Agents, and between Agents
and Managers. Note that Agents and Managers are roles, not
necessarily differing software applications. Node A may represent a
single software application fulfilling only the Agent role, whereas
node B may have a single software application fulfilling both the
Agent and Manager roles. The specifics of how these roles are
realized is an implementation matter.
8.2. Control Flow by Role
This section describes three common configurations of Agents and
Managers and the flow of messages between them. These configurations
involve local and remote management and data fusion.
8.2.1. Notation
The notation outlined in Table 1 describes the types of control
messages exchanged between Agents and Managers.
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+-------------+--------------------------------------+--------------+
| Term | Definition | Example |
+-------------+--------------------------------------+--------------+
| EDD# | EDD definition. | EDD1 |
| | | |
| V# | Custom data definition. | V1 = EDD1 + |
| | | V0. |
| | | |
| DEF([ACL], | Define id from expression. Allow | DEF([*], V1, |
| ID,EXPR) | managers in access control list | EDD1 + EDD2) |
| | (ACL) to request this id. | |
| | | |
| PROD(P,ID) | Produce ID according to predicate P. | PROD(1s, |
| | P may be a time period (1s) or an | EDD1) |
| | expression (EDD1 > 10). | |
| | | |
| RPT(ID) | A report identified by ID. | RPT(EDD1) |
+-------------+--------------------------------------+--------------+
Table 1: Terminology
8.2.2. Serialized Management
This is a nominal configuration of network management where a Manager
interacts with a set of Agents. The control flows for this are
outlined in Figure 2.
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Serialized Management Control Flow
+----------+ +---------+ +---------+
| Manager | | Agent A | | Agent B |
+----+-----+ +----+----+ +----+----+
| | |
|-----PROD(1s, EDD1)--->| | (1)
|----------------------------PROD(1s, EDD1)-->|
| | |
| | |
|<-------RPT(EDD1)------| | (2)
|<----------------------------RPT(EDD1)-------|
| | |
| | |
|<-------RPT(EDD1)------| |
|<----------------------------RPT(EDD1)-------|
| | |
| | |
|<-------RPT(EDD1)------| |
|<----------------------------RPT(EDD1)-------|
| | |
In a simple network, a Manager interacts with multiple Agents.
Figure 2
In this figure, the Manager configures Agents A and B to produce EDD1
every second in (1). At some point in the future, upon receiving and
configuring this message, Agents A and B then build a Report Entry
containing EDD1 and send those reports back to the Manager in (2).
8.2.3. Multiplexed Management
Networks spanning multiple administrative domains may require
multiple Managers (for example, one per domain). When a Manager
defines custom Reports/Variables to an Agent, that definition may be
tagged with an access control list (ACL) to limit what other Managers
will be privy to this information. Managers in such networks should
synchronize with those other Managers granted access to their custom
data definitions. When Agents generate messages, they MUST only send
messages to Managers according to these ACLs, if present. The
control flows in this scenario are outlined in Figure 3.
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Multiplexed Management Control Flow
+-----------+ +-------+ +-----------+
| Manager A | | Agent | | Manager B |
+-----+-----+ +---+---+ +-----+-----+
| | |
|---DEF(A,V1,EDD1*2)-->|<-DEF(B, V2, EDD2*2)--| (1)
| | |
|---PROD(1s, V1)------>|<---PROD(1s, V2)------| (2)
| | |
|<--------RPT(V1)------| | (3)
| |--------RPT(V2)------>|
|<--------RPT(V1)------| |
| |--------RPT(V2)------>|
| | |
| |<---PROD(1s, V1)------| (4)
| | |
| |---ERR(V1 no perm.)-->|
| | |
|--DEF(*,V3,EDD3*3)--->| | (5)
| | |
|---PROD(1s, V3)------>| | (6)
| | |
| |<----PROD(1s, V3)-----|
| | |
|<--------RPT(V3)------|--------RPT(V3)------>| (7)
|<--------RPT(V1)------| |
| |--------RPT(V2)------>|
|<-------RPT(V3)-------|--------RPT(V3)------>|
|<-------RPT(V1)-------| |
| |--------RPT(V2)------>|
Complex networks require multiple Managers interfacing with Agents.
Figure 3
In more complex networks, any Manager may choose to define custom
Reports and Variables, and Agents may need to accept such definitions
from multiple Managers. Variable definitions may include an ACL that
describes who may query and otherwise understand these definitions.
In (1), Manager A defines V1 only for A while Manager B defines V2
only for B. Managers may, then, request the production of Report
Entries containing these definitions, as shown in (2). Agents
produce different data for different Managers in accordance with
configured production rules, as shown in (3). If a Manager requests
the production of a custom definition for which the Manager has no
permissions, a response consistent with the configured logging policy
on the Agent should be implemented, as shown in (4). Alternatively,
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as shown in (5), a Manager may define custom data with no
restrictions allowing all other Managers to request and use this
definition. This allows all Managers to request the production of
Report Entries containing this definition, shown in (6) and have all
Managers receive this and other data going forward, as shown in (7).
8.2.4. Data Fusion
In some networks, Agents do not individually transmit their data to a
Manager, preferring instead to fuse reporting data with local nodes
prior to transmission. This approach reduces the number and size of
messages in the network and reduces overall transmission energy
expenditure. The AMA supports fusion of NM reports by co-locating
Agents and Managers on nodes and offloading fusion activities to the
Manager. This process is illustrated in Figure 4.
Data Fusion Control Flow
+-----------+ +-----------+ +---------+ +---------+
| Manager A | | Manager B | | Agent B | | Agent C |
+---+-------+ +-----+-----+ +----+----+ +----+----+
| | | |
|--DEF(A,V0,EDD1+AD2)->| | | (1)
|--PROD(EDD1&AD2,V0)-->| | |
| | | |
| |--PROD(1s,EDD1)->| | (2)
| |------------------PROD(1s, EDD2)->|
| | | |
| |<---RPT(EDD1)----| | (3)
| |<------------------RPT(EDD2)------|
| | | |
|<-----RPT(A,V0)-------| | | (4)
| | | |
Data fusion occurs amongst Managers in the network.
Figure 4
In this example, Manager A requires the production of a Variable V0,
from node B, as shown in (1). The Manager role understands what data
is available from what agents in the subnetwork local to B,
understanding that EDD1 is available locally and EDD2 is available
remotely. Production messages are produced in (2) and data collected
in (3). This allows the Manager at node B to fuse the collected
Report Entries into V0 and return it in (4). While a trivial
example, the mechanism of associating fusion with the Manager
function rather than the Agent function scales with fusion
complexity, though it is important to reiterate that Agent and
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Manager designations are roles, not individual software components.
There may be a single software application running on node B
implementing both Manager B and Agent B roles.
9. IANA Considerations
At this time, this protocol has no fields registered by IANA.
10. Security Considerations
Security within an AMA MUST exist in two layers: transport layer
security and access control.
Transport-layer security addresses the questions of authentication,
integrity, and confidentiality associated with the transport of
messages between and amongst Managers and Agents in the AMA. This
security is applied before any particular Actor in the system
receives data and, therefore, is outside of the scope of this
document.
Finer grain application security is done via ACLs which are defined
via configuration messages and implementation specific.
11. Informative References
[BIRRANE1]
Birrane, E. and R. Cole, "Management of Disruption-
Tolerant Networks: A Systems Engineering Approach", 2010.
[BIRRANE2]
Birrane, E., Burleigh, S., and V. Cerf, "Defining
Tolerance: Impacts of Delay and Disruption when Managing
Challenged Networks", 2011.
[BIRRANE3]
Birrane, E. and H. Kruse, "Delay-Tolerant Network
Management: The Definition and Exchange of Infrastructure
Information in High Delay Environments", 2011.
[I-D.irtf-dtnrg-dtnmp]
Birrane, E. and V. Ramachandran, "Delay Tolerant Network
Management Protocol", draft-irtf-dtnrg-dtnmp-01 (work in
progress), December 2014.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<http://www.rfc-editor.org/info/rfc2119>.
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[RFC3416] Presuhn, R., Ed., "Version 2 of the Protocol Operations
for the Simple Network Management Protocol (SNMP)",
STD 62, RFC 3416, DOI 10.17487/RFC3416, December 2002,
<http://www.rfc-editor.org/info/rfc3416>.
[RFC4838] Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst,
R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant
Networking Architecture", RFC 4838, April 2007.
[RFC6241] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
<http://www.rfc-editor.org/info/rfc6241>.
Author's Address
Edward J. Birrane
Johns Hopkins Applied Physics Laboratory
Email: Edward.Birrane@jhuapl.edu
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