TVR (Time-Variant Routing) Requirements
draft-ietf-tvr-requirements-02
| Document | Type | Active Internet-Draft (tvr WG) | |
|---|---|---|---|
| Authors | Daniel King , Luis M. Contreras , Brian Sipos | ||
| Last updated | 2024-03-04 | ||
| Replaces | draft-kcs-tvr-requirements | ||
| RFC stream | Internet Engineering Task Force (IETF) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Additional resources | Mailing list discussion | ||
| Stream | WG state | WG Document | |
| Document shepherd | Edward J. Birrane | ||
| IESG | IESG state | I-D Exists | |
| Consensus boilerplate | Unknown | ||
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | edward.birrane@jhuapl.edu |
draft-ietf-tvr-requirements-02
Network Working Group D. King
Internet-Draft Lancaster University
Intended status: Informational L. M. Contreras
Expires: 5 September 2024 Telefonica
B. Sipos
JHU/APL
4 March 2024
TVR (Time-Variant Routing) Requirements
draft-ietf-tvr-requirements-02
Abstract
Time-Variant Routing (TVR) refers to the calculation of a path or
subpath through a network where the time of message transmission (or
receipt) is part of the overall route computation. This means that,
all things being equal, a TVR computation might produce different
results depending on the time that the computation is performed
without other detectable changes to the network topology or other
cost functions associated with the route.
This document introduces requirements where TVR computations could
improve message exchange in a network.
About This Document
This note is to be removed before publishing as an RFC.
Status information for this document may be found at
https://datatracker.ietf.org/doc/draft-ietf-tvr-requirements/.
Discussion of this document takes place on the Time Variant Routing
Working Group mailing list (mailto:tvr@ietf.org), which is archived
at https://mailarchive.ietf.org/arch/browse/tvr/. Subscribe at
https://www.ietf.org/mailman/listinfo/tvr/.
Source for this draft and an issue tracker can be found at
https://github.com/danielkinguk/tvr-requirements.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Conventions and Definitions . . . . . . . . . . . . . . . . . 3
3. Overview of Time-Variant Networks . . . . . . . . . . . . . . 5
3.1. Resource Scheduling . . . . . . . . . . . . . . . . . . . 5
3.1.1. Schedule Visibility . . . . . . . . . . . . . . . . . 6
3.1.2. Generation Locality . . . . . . . . . . . . . . . . . 6
3.1.3. Execution Locality . . . . . . . . . . . . . . . . . 7
3.2. General Temporality . . . . . . . . . . . . . . . . . . . 8
3.2.1. Scope of Time-Variability . . . . . . . . . . . . . . 8
3.2.2. Time Horizon . . . . . . . . . . . . . . . . . . . . 9
3.2.3. Time Precision . . . . . . . . . . . . . . . . . . . 9
3.2.4. Validity in a Schedule . . . . . . . . . . . . . . . 10
3.2.5. Periodicity in a Schedule . . . . . . . . . . . . . . 10
3.2.6. Continuity in a Schedule . . . . . . . . . . . . . . 10
3.2.7. Time-Overlap and Priority . . . . . . . . . . . . . . 11
3.2.8. Property Value Interpolation . . . . . . . . . . . . 11
3.2.9. Changes to Model State . . . . . . . . . . . . . . . 12
3.3. Topologies . . . . . . . . . . . . . . . . . . . . . . . 12
3.3.1. Nodes . . . . . . . . . . . . . . . . . . . . . . . . 12
3.3.2. Termination Points . . . . . . . . . . . . . . . . . 13
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3.3.3. Links . . . . . . . . . . . . . . . . . . . . . . . . 13
3.3.4. Network Layering . . . . . . . . . . . . . . . . . . 13
3.4. Routing . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.4.1. Centralized . . . . . . . . . . . . . . . . . . . . . 14
3.4.2. Distributed . . . . . . . . . . . . . . . . . . . . . 14
3.4.3. Hybrid . . . . . . . . . . . . . . . . . . . . . . . 15
3.4.4. Constraints . . . . . . . . . . . . . . . . . . . . . 15
4. Time-Variant Use Case Requirements . . . . . . . . . . . . . 15
4.1. Operating Efficiency Use Case . . . . . . . . . . . . . . 15
5. Requirements Summary . . . . . . . . . . . . . . . . . . . . 16
5.1. Support the Identification and Advertisement of Entity
Property Changes . . . . . . . . . . . . . . . . . . . . 16
5.2. Support Proxy Advertisement . . . . . . . . . . . . . . . 16
5.3. Support Identification and Classification of Node
Properties . . . . . . . . . . . . . . . . . . . . . . . 16
5.4. Support System Schedule and Time Interval Changes . . . . 17
5.5. Support Appropriate Time Accuracy . . . . . . . . . . . . 17
6. Security Considerations . . . . . . . . . . . . . . . . . . . 17
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 18
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . 18
References . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Normative References . . . . . . . . . . . . . . . . . . . . . 18
Informative References . . . . . . . . . . . . . . . . . . . . 18
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 19
1. Introduction
2. Conventions and Definitions
Specific terms used within this document are as follows:
Model: The universe being modeled, which defines a parameter space.
Entity: A single separable item within the model. Each entity has a
stable identity which is time-invariant.
Property: A single attribute of an entity which is used to
parameterize that entity. The notion of a property is not time-
variant, the property always exists within an entity but its value
may be time-variant.
Property Value: The specific value of a property, both as a planned
state within the schedule timeline and as a realized state in
wall-clock time.
Schedule: The method of parameterizing time-variance intrinsic to a
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time-variant model. The parameters of a schedule are within the
state space of the model.
Schedule Time: An idealized timeline within a time-variant model
over which entities and property values may change without a
difference of state in the model itself. The notion of schedule
time is intrinsic to the model.
Wall-Clock Time: The true timeline, measured in some time scale by
some local ticker. The notion of wall-clock time is extrinsic to
the model; even non-time-variant models allow for changes over
wall-clock time, just as different model states rather than a
change _within_ the model itself.
Time Instant: A single instant of time, consistent with the concepts
of date-time in [RFC3339].
Timeline: A possibly bounded interval of time, consistent with the
concept of a period in [RFC3339].
Subsequent: A time instant which is later in a timeline than some
reference time instant.
Orchestrator: The subsystem of a managing device which centralizes
control of a network and applies policy to manage a network. A
Path Computation Element (PCE) is an example of an Orchestrator.
Manager: The subsystem in a managing device which operates a
management protocol to control an Agent.
Agent: The subsystem in a managed device which operates a management
protocol to be controlled by a Manager.
(Routing) Application: The subsystem of a managed device which
performs the functions of a routing protocol and/or algorithm.
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+--------------------+ +-------------------+
| Managing Device | | Managed Device |
| | | |
| +--------------+ | | +-------------+ |
| | Orchestrator | | | | Application | |
| +--------------+ | | +-------------+ |
| | | | | |
| +--------------+ | | +-------------+ |
| | Manager | |---+---| | Agent | |
| +--------------+ | : | +-------------+ |
+--------------------+ : +-------------------+
:
+-------------+
| Data Model |
+-------------+
Figure 1: Management Entities
3. Overview of Time-Variant Networks
Existing Internet routing techniques maintain end-to-end connected
paths across a network. Routing mechanisms exist to recover
connectivity and resume normal traffic forwarding as the topology
changes. Occasionally, optimization of routes may also be requested,
especially post-topology changes due to disruptive events. However,
there are a growing number of use cases where changes to the routing
topology are an expected part of network operations. In these
scenarios, the pre-planned loss and restoration of an adjacency, or
formation of an alternate adjacency, should be seen as a non-
disruptive event.
Time-Variant Routing (TVR) refers to calculating a path or subpath
through a network where the time of message transmission (or receipt)
is part of the overall route computation. Therefore, a TVR
computation might produce different results depending on the time
that the calculation is performed without other detectable changes to
the network topology or other cost functions associated with the
route.
3.1. Resource Scheduling
Planned resource scheduling will be required for various scenarios;
these include networks with mobile entities, such as crewless aerial
vehicles and orbiting satellite constellations
[I-D.ietf-tvr-use-cases]. In these scenarios, links are lost and re-
established as a function of the mobility of the platforms.
Furthermore, link activity might be restricted to certain times of
the day in networks without reliable access to power, such as
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networks harvesting energy from tidal, wind, and solar resources.
Similarly, network traffic might be planned around energy costs or
expected user data volumes in networks prioritising green computing
and energy efficiency over data rate.
3.1.1. Schedule Visibility
Because scheduled time-variance is not a part of exsting routing
algorithms and managed data models, not all routing applications will
be made to handle schedules as part of the routing parameters
intrinsically.
Two extremes of schedules being associated to routing data are:
Intrinsic Schedule: In this situation, the schedule is an intrinsic
part of the managed data model which is visible to the routing
application and used as part of the routing algorithms. When the
schedule is intrinsic, there is not necessarily the notion of a
schedule being "executed" in wall-clock time because the time-
varying parameters are ingested as part of the routing algorithms
natural functioning.
Extrinsic Schedule: In this situation, the schedule is not part of
the managed data proper but maintained within the Orchestrator;
the routing application only sees the effects of changes in
routing parameters as the schedule is executed (in wall-clock
time) by the Agent.
There is also the possibility of an intermediate situation where the
schedule is still part of the managed data model but is visible only
to, and executed in wall-clock time by, the management Agent. This
allows a more distributed use of scheduled data than centralizing its
processing in an Orchestrator.
3.1.2. Generation Locality
The generation of a scheduled data model depends on collecting source
data (which likely has some temporal information in it to begin
with), choosing a time horizon to schedule within, and then
processing the source data into an overall schedule.
Two extremes for locality of schedule generation are:
Centralized Generation: In this situation, all schedule generation
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is centralized within a network Orchestrator and changes are sent
to routing applications in wall-clock time via a management
interface. Even though the generation of the schedule is
centralized, both the schedule visibility (within the data model)
and the locality of how the schedule is executed are
unconstrained.
For example, a schedule could be generated in a central
orchestrator synchronized to all managed devices which then
execute the schedule in a distributed manner.
Distributed Generation: This situation corresponds with the
Intrinsic or intermediate schedule visibility, where a schedule
(with a potentially limited time horizon from what is known at the
orchestrator) is part of the managed data which is distributed to
managed devices to be handled either by the Agent or by the
routing Application itself.
3.1.3. Execution Locality
Depending on the visibility of schedules within a data model (see
Section 3.1.1) there are different options for where the schedule may
be executed to ultimately affect a time-varying configuration on a
managed device.
Two extremes for locality of schedule execution are:
Centralized Execution: In this situation, all schedule execution is
centralized within a network Orchestrator and changes are sent to
routing applications in wall-clock time via a management
interface. This situation can apply to any type of schedule
visibility, but only to centralized generation because the full
scheduled data model needs to be available to the entity
performing the execution.
Distributed Execution: In this situation, schedules are executed on
each managed device independently but based on synchronized
clocks. This situation corresponds with the Intrinsic or
intermediate schedule visibility, where a schedule (with a
potentially limited time horizon from what is known at the
Orchestrator) is part of the managed data which is distributed to
managed devices to be handled either by the Agent or by the
routing Application itself.
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When schedules are distributed to the managed devices, it
necessarily increases the amount of data that the managing device
needs to synchronize across the network. The ratio of increased
size can be mitigated by only distributing a limited time horizon
to each device within a sliding window that moves forward in non-
real-time.
When schedules are both generated and executed centrally, there is a
consistency risk between different managed devices because if one
device fails to be reconfigured in wall-clock time its configuration
will no longer align with the other devices which are supposed to all
operate on the same schedule. To recover from this kind of
situation, either reattempts to configure the misaligned device can
be made to bring it back into alignment with the other devices or the
other devices' configurations must be rolled-back into consistency
which will then cause all the devices to be off-schedule.
When schedules are executed on each device, there is a risk that
clocks on different devices become desynchronized beyond the time
precision required of the schedule. Because real-time clocks are
necessary for more than just schedule execution, and because accurate
and precise time sources exist outside of network time (_e.g._, GPS
time) this risk can be made to have a low probability.
With distributed execution there is also a risk that a manager loses
connectivity with the managed device and the device eventually runs
out of time horizon in the schedule which is known to it. This risk
can be mitigated by trading between the size and the horizon end-time
of schedules distributed to managed devices. This trade can be
different for different devices, where some well-connected devices
operate closer to just-in-time with short horizons while other
devices can be given a longer horizon to allow it to execute in the
absense of near-continuous manager connectivity.
3.2. General Temporality
This section covers different aspects of how temporality applies to
any potential TVR information model. Each aspect is roughly
independent and informs how a model can choose to include temporality
in its parameter space.
3.2.1. Scope of Time-Variability
One aspect of any time-varying model is the scope of what may be
time-variable. Two extremes of this aspect are:
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* A model which is completely time-invariant, which while there is
still a notion of time it has no affect on any of the model
entities.
* A model in which every entity has some kind of schedule applied.
It is expected that an application of time-variability to real world
data models will keep some entities within the model time-invariant
and allow scheduling of other, specific entities.
Another aspect of any time-varying model is the granularity of state
to which a schedule can be applied. Two extremes of this aspect are:
* A model where one single schedule applies to the entire universe
(_i.e._ indicating when the time-variant entities are valid or
invalid).
* A model where every property of every entity can be scheduled
independently. This is the temporality model of [AIXM].
It is expected that an application of time-variability to data models
will fit within these extremes, possibly applying a schedule to each
entity indicating when that entity is valid or invalid, or applying a
schedule to groups of properties within the entity (while leaving
other properties time-invariant).
3.2.2. Time Horizon
In an idealized model the schedules will apply indefinitely far in
the past and the future, but in a realizable model with both
processing and storage limitations there will need to be a time
horizon within which the model applies and outside of which the model
has no meaning. In some cases this horizon will be intrinsic to the
model itself, with an explicit model parameter indicating the
horizon. In other cases the model may allow indefinitely-large
schedules but the processing of the planning timeline is bounded to
limit resource needs.
3.2.3. Time Precision
Different time-variant models will require different granularities of
planning time, either because of limitations or assumptions about
wall-clock time or because of requirements within the modeled domain.
It is up to specific models to define the precision of time values
and the required accuracy and precison of wall-clocks which execute
the schedules.
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3.2.4. Validity in a Schedule
Within a single schedule over the planning timeline there will likely
be a need to have multiple discrete intervals of validity over
absolute schedule time. The time instants at which a schedule is
invalid indicate an undefined property value, so it is important for
a model to be able to accomodate multiple schedules as necessary to
ensure that some properties can have values at all times.
A model which restricts itself to a single interval of validity could
run into difficulties over a long enough time horizon and would need
to resort to having multiple model entities represent the same
modeled "thing" which can lead to confusion and inefficiency.
3.2.5. Periodicity in a Schedule
Separate from the concept of intervals of validity in absolute
schedule time, there can be a need to model repetitive states in a
concise way. One way to model a periodic change of state is to
combine a set of absolute time intervals with a periodic
parameterization (duration valid and duration invalid); this is the
mdoel of [AIXM].
A model which does not include the notion of periodicy within a
schedule could be used in situations where discrete intervals of
validity are needed to handle periodic state changes which is neither
storage nor processing efficient.
3.2.6. Continuity in a Schedule
A schedule which includes a sequence of time intervals needs to
ensure that the interpretation of those intervals in the schedule
timeline does not leave any "gaps" at the interval boundaries. For
that reason, it is important that the model uses half-open intervals
of time so that time-adjacent intervals leave no gap. In keeping
with the terminology of [RFC3339], intervals are bounded by their
"start" and "end" instants. It is suggested that any time-varying
model use schedules with intervals closed on their start time and
open on their end time. This behavior lends to the interpretation,
in the schedule timeline, that the scheduled state takes effect at an
interval's start and continues until the subsequent state.
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3.2.7. Time-Overlap and Priority
In an ideal situation a model would be guaranteed by design to
contain only contiguous and non-overlapping schedules for each time-
variant scope. In a realized model this kind of invaraint might not
be enforcable or might lead to overly complex schedule structures.
One way a model can handle this is to establish a concept of schedule
priority, where some intervals of the schedule timeline contain
overlapping schedules for the same properties and only the highest-
priority schedule applies. When priorities are allowed by a model,
it enables the concept of an "overlay" where a long-duration state
can be temporarilly (in schedule time) superseded by a short-duration
state.
3.2.8. Property Value Interpolation
When a schedule is applied to an entity in a way which is more
granular (Section 3.2.1) than just indicating when that whole entity
is valid or invalid, the model needs to consider how individual
properties are to be treated between scheduled instants. Some of the
possibile behaviors are:
Zero-order hold: From the instant a scheduled value applies to a
property until the subsequent-in-schedule-time value supersedes
it. This is simple from a logical standpoint, but discontinuties
in the value over schedule time could cause issues with the model
itself. For some models, though, the constant values between
change instants are actually beneficial by allowing the entire
timeline to be compressed into a sequence of discrete state-change
instants. This is the behavior implied in models such as [AIXM].
Linear interpolation: At the instants of time defined in the
schedule the property takes the exact values, but between those
instants the property is interpolated linearly over time. This
results in a state that is continuous over time, which is
beneficial for some kinds of model but also means that there is no
simple discrete sequence of states.
Higher-order or spline interpolation: Higher order interpolations
can result in properties that vary over schedule time in ways that
are more or less beneficial to different types of models.
Regardless of the types of interpolation used, a model can choose to
apply interpolation globally or per-property. Since different
properties represent different physical or logical metrics of a
network it is expected that different types of interpolation will be
needed for different represented quantities.
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3.2.9. Changes to Model State
Separate from how a time-variant model can contain a schedule
timeline within the model state, a model design will need to consider
how changes to the model state itself (over wall-clock time) are
handled. This aspect is actually not specific to a time-variant
model but is important to consider in this context.
Two extremes of this aspect are:
* A model which can only be changed wholesale, superseded by an
entire new model state. This is easy to keep consistent but has
inefficiences of storage and transport if the model state is to be
shared or exchanged between real entities.
* A model which has an intrinsic notion of fine-grained superseding
changes, possibly scoped to individual entities, individual
schedules, or more complex groupings.
3.3. Topologies
The primary entities of a topological network model, as realized in
[RFC8345] and similar predecessors, are nodes and unidirectional
links, with a secondary entity representing the "termination point"
for each side of a link at a node. Following the concepts described
in Section 3.1 these are the entities to which an intrinsic schedule
can be applied.
3.3.1. Nodes
When a schedule is applied to a node the granularity could at least
be at the individual node. In cases where the properties of a node
have time-variable values the model may define an interpolation
method, either globally or per-property.
A node is just a named entity in Layer 3 [RFC8346] and Layer 2
[RFC8944] topologies. Schedules on a node could be used to indicate
the validity of the entire node or changing properties of that
entity. When a schedule indicates that a node is not valid for a
schedule time instant, that validity could apply to all of its
termination points and links as well. This logic allows a schedule
to represent, for example, the expected power-on state of a node at a
specific layer.
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3.3.2. Termination Points
When a schedule is applied to a termination point the granularity
should at least be at the individual entity. In cases where the
properties of a termination point have time-variable values the model
may define an interpolation method, either globally or per-property.
A termination point is associated with an IP address in Layer 3
[RFC8346] and a MAC address in Layer 2 [RFC8944] topologies.
Schedules on a termination point could be used to indicate the
validity of the layer-2/3 interface represented by the entity or
changing properties of that entity. When a schedule indicates that a
termination point is not valid for a schedule time instant, that
validity may apply to all of its links as well. This logic allows a
schedule to represent, for example, the expected power-on or
administrative-enabled state of an attached network interface card
(NIC) or virtual private network (VPN) endpoint.
3.3.3. Links
When a schedule is applied to a link the granularity should at least
be at the individual link. In cases where the properties of a link
have time-variable values the model should define an interpolation
method, either globally or per-property.
A link is associated with link metric properties in Layer 3 [RFC8346]
and Layer 2 [RFC8944] topologies. Schedules on a link should be used
to indicate the validity of the entire link or changing properties of
that entity. When a schedule indicates that a link is not valid for
a schedule time instant, that validity should not apply to its
termination points and nodes. This logic allows a schedule to
represent, for example, the expected connectivity state, data
throughput/rate, and latency/delay of a link.
3.3.4. Network Layering
When a schedule indicates that an entity is not valid for a schedule
time instant, that validity should not apply to any of its associated
overlay or underlay network entities. The effects of scheduled
administrative disabling or enabling of an entity at one layer do not
imply a change in administrative enabled state at any other layer.
Likewise, the assigning of an address property at one layer does not
imply the presence or absence of an address assignment at that same
time instant for any other layer.
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3.4. Routing
Traditional network routing techniques typically use link bandwidth
and delay for path calculation, and do not consider time-based
factors. TVR should be capable of improving network performance and
reliability in environments where entities liveness and link
availability is a time-based consideration, with various factors,
including power availability, interface line of sight or expected
demand.
However, even if some adjacency failures are predictable, others are
not, including link failures and entity outages. Therefore, any new
technique or routing protocol extension for TVR enviroments must be
capable of handling planned and unexpected resource losses.
Time-Variant Routing (TVR) introduces a scenario of calculating a
path, or sub-path within a network, taking into account the timing of
message transmission or receipt as an integral part of the overall
route computation.
Furthermore, Synchronization of network time across TVR-capable
entities is critical in TVR networks.
Three scenarios are currently considered when computing TVR-enabled
paths.
3.4.1. Centralized
The network entities will receive the time variable information and
traffic forwarding rules directly from a logically centralized
source, an Orchestrator. The time variable data may then be
processed locally by the entity entered into the scheduled routing
table and specific forwarding rules applied.
3.4.2. Distributed
Network entities may participate in a routing scheme where time
variable information is propagated through the network via capability
and variability advertisements. This could be achieved using
extensions to existing routing schemes and techniques so that link,
adjacency, cost, and schedule may be considered when making
forwarding decisions for per-hop packets or calculating traffic
engineered end-to-end paths. It should be noted that schedule
distribution and entity computation latency may exist in some network
environments.
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In some enviroments scheduling information may distributed through a
management plane mechanism, such as NETCONF or gnmi, instead of the
routing scheme.
3.4.3. Hybrid
In this scenario, mixed-entity TVR capability exists. Some entities
will require a schedule provided by a centralized source, and others
will be capable of advertising and learning scheduled information via
a distributed mechanism.
This scenario presents time and schedule synchronization and source
verification challenges and will require further study.
3.4.4. Constraints
// TBD
4. Time-Variant Use Case Requirements
Several TVR use cases have been identifed and discussed in
[I-D.ietf-tvr-use-cases]. This section provides further detail on
specific requirements to meet use case needs.
4.1. Operating Efficiency Use Case
Several operational efficiency requirements exist; these include:
1. Distribution of Predicted Topology-change. The predicted
topology-change information may include the valid time, invalid
time, link costs at different times, and change periods.
2. Topology Changes. The predicted topology-change information may
change due to forecasted or unforecasted changes. The managing
entity should be capable of providing a partial or full topology
update as often as needed.
3. The Minimum Route Recalculation Interval and Threshold. Although
some cases may assume that the cost persists for a sufficient
amount of time, considering that each route contains multiple
links, the change frequency of the path may be much higher than
the cost. In this case, the minimum recalculation interval or
cost change threshold is needed to determine when a route
recalculation is required. Of course, scheduled topology
connection changes must be considered when path calculation is
required.
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5. Requirements Summary
5.1. Support the Identification and Advertisement of Entity Property
Changes
In Time-Variant Routing, scheduling of availible entity resources is
expected is expected. In practical situations, however, the
properties of entities can be converted back and forth between Time-
Variant and Non-Time-Variant nodes.
An entity must support the identification and advertisement of non-
scheduled property changes.
Besides, if there are abnormal changes in the system, it is necessary
to advertise them through the existing routing protocols in time to
achieve the stability of Time-Variant Routing and avoid redundant
advertisements. For example, an entity in the system is suddenly
damaged due to external factors. Changes in entity state outside of
a schedule are communicated to other entities in a network through
existing routing protocol mechanims, where they exist.
A manager should provide an advertisement methodology for responding
to abnormal changes in the system.
5.2. Support Proxy Advertisement
Proxies can help to improve the efficiency of the network. There are
some entities in the network that do not have routing functions.
When their properties change, they are unable to notify other
entities in the network. Proxy nodes can help nodes without routing
functions to advertise information, thus improving the efficiency of
the network. Therefore,
o Must support proxy entities to help non-routing nodes implement
information advertisement.
5.3. Support Identification and Classification of Node Properties
The entity properties of the network may change as described in 3.1.
If the system cannot timely identify and classify in a processing
manner after the entity properties change, it will lead to suboptimal
routing decisions. Therefore,
o Must provide a discovery and resolving methodology for the
identification and classification of entity schedule changes.
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5.4. Support System Schedule and Time Interval Changes
The system's schedule may change, requiring entity configuration
updates instead it being set once and not being able to be modified.
Additionally, time-variant intervals in the system may also vary.
Therefore,
o Must support system schedule changes.
o Must support time interval changes.
5.5. Support Appropriate Time Accuracy
The accuracy of the time cannot be too large or too small; otherwise,
convergence may not be possible. Therefore,
o Must support appropriate time tolerance.
6. Security Considerations
The security implications for networks using time-variant routing
mechanisms must also be considered. Several potential security
implications will need careful investigation, these include:
* Denial-of-Service (DoS) attacks: Malicious actors could manipulate
or disrupt the time information shared within the network, leading
to issues with routing protocols and potentially causing DoS
attacks. This could impact the network's ability to function
properly and deliver services to entities.
* Traffic analysis and route prediction: Predicting network
activity: By analyzing the shared time information, attackers
could potentially predict network activity patterns and routing
decisions. This information could be used to launch targeted
attacks or plan disruptions.
* Identifying user activity: In some scenarios, precise time
information might be linked to specific user or device activity or
network usage patterns. This could raise privacy concerns if not
properly anonymized or protected.
* Spoofing and manipulation: Fake or manipulated time information
could be injected into the network, leading to incorrect routing
decisions and disruptions. This could be used to redirect
traffic, launch man-in-the-middle attacks, or gain unauthorized
access to resources.
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7. IANA Considerations
This document has no IANA actions.
Contributors
The following authors contributed significantly to this document:
Jing Wang
China Mobile
China
Email: wangjingjc@chinamobile.com
Peng Liu
China Mobile
China
Email: liupengyjy@chinamobile.com
Li Zhang
Huawei
China
Email: zhangli344@huawei.com
Zheng (Sandy) Zhang
ZTE Corporation
China
Email: zhang.zheng@zte.com.cn
Yuehua Wei
ZTE Corporation
China
Email: wei.yuehua@zte.com.cn
References
Normative References
[I-D.ietf-tvr-use-cases]
Birrane, E. J., Kuhn, N., Qu, Y., Taylor, R., and L.
Zhang, "TVR (Time-Variant Routing) Use Cases", Work in
Progress, Internet-Draft, draft-ietf-tvr-use-cases-09, 29
February 2024, <https://datatracker.ietf.org/doc/html/
draft-ietf-tvr-use-cases-09>.
Informative References
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[AIXM] EUROCONTROL and Federal Aviation Administration, "AIXM 5
Temporality Model", 15 September 2010,
<https://aixm.aero/sites/aixm.aero/files/imce/AIXM51/
aixm_temporality_1.0.pdf>.
[I-D.contreras-tvr-alto-exposure]
Contreras, L. M., "Using ALTO for exposing Time-Variant
Routing information", Work in Progress, Internet-Draft,
draft-contreras-tvr-alto-exposure-03, 27 February 2024,
<https://datatracker.ietf.org/doc/html/draft-contreras-
tvr-alto-exposure-03>.
[I-D.hou-tvr-satellite-network-usecases]
Dongxu, H., Min, X., Zhou, F., and D. Yuan, "Satellite
Network Routing Use Cases", Work in Progress, Internet-
Draft, draft-hou-tvr-satellite-network-usecases-02, 14
September 2023, <https://datatracker.ietf.org/doc/html/
draft-hou-tvr-satellite-network-usecases-02>.
[I-D.king-tvr-ntn-challanges]
King, D. and K. Shortt, "Time Variant Challenges for Non-
Terrestrial Networks", Work in Progress, Internet-Draft,
draft-king-tvr-ntn-challanges-00, 17 January 2023,
<https://datatracker.ietf.org/doc/html/draft-king-tvr-ntn-
challanges-00>.
[RFC3339] Klyne, G. and C. Newman, "Date and Time on the Internet:
Timestamps", RFC 3339, DOI 10.17487/RFC3339, July 2002,
<https://www.rfc-editor.org/info/rfc3339>.
[RFC8345] Clemm, A., Medved, J., Varga, R., Bahadur, N.,
Ananthakrishnan, H., and X. Liu, "A YANG Data Model for
Network Topologies", RFC 8345, DOI 10.17487/RFC8345, March
2018, <https://www.rfc-editor.org/info/rfc8345>.
[RFC8346] Clemm, A., Medved, J., Varga, R., Liu, X.,
Ananthakrishnan, H., and N. Bahadur, "A YANG Data Model
for Layer 3 Topologies", RFC 8346, DOI 10.17487/RFC8346,
March 2018, <https://www.rfc-editor.org/info/rfc8346>.
[RFC8944] Dong, J., Wei, X., Wu, Q., Boucadair, M., and A. Liu, "A
YANG Data Model for Layer 2 Network Topologies", RFC 8944,
DOI 10.17487/RFC8944, November 2020,
<https://www.rfc-editor.org/info/rfc8944>.
Authors' Addresses
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D. King
Lancaster University
Email: d.king@lancaster.ac.uk
L. M. Contreras
Telefonica
Email: luismiguel.contrerasmurillo@telefonica.com
B. Sipos
JHU/APL
Email: brian.sipos+ietf@gmail.com
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