Internet DRAFT - draft-liu-dyncast-reqs
draft-liu-dyncast-reqs
rtgwg P. Liu
Internet-Draft T. Jiang
Intended status: Informational China Mobile
Expires: 8 September 2022 P. Eardley
British Telecom
D. Trossen
C. Li
Huawei Technologies
7 March 2022
Dynamic-Anycast (Dyncast) Requirements
draft-liu-dyncast-reqs-02
Abstract
This draft provides requirements for an architecture addressing the
problems outlined in the use case and problem statement draft for
Dyncast[I-D.liu-dyncast-ps-usecases] .
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Copyright (c) 2022 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Definition of Terms . . . . . . . . . . . . . . . . . . . . . 3
3. Desirable System Characteristics and Requirements . . . . . . 3
3.1. Anycast-based Service Addressing Methodology . . . . . . 3
3.2. Instance Affinity . . . . . . . . . . . . . . . . . . . . 4
3.3. Proper Runtime-state Granularity and Keeping . . . . . . 5
3.4. Encoding Metrics . . . . . . . . . . . . . . . . . . . . 5
3.5. Signaling Metrics . . . . . . . . . . . . . . . . . . . . 6
3.6. Using Metrics in Routing Decisions . . . . . . . . . . . 6
3.7. Supporting Service Dynamism . . . . . . . . . . . . . . . 7
4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 8
5. Security Considerations . . . . . . . . . . . . . . . . . . . 8
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
7. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 8
8. Informative References . . . . . . . . . . . . . . . . . . . 8
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 9
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
Computing service instances instantiated at multiple geographical
edge sites are used to better realize an edge computing service in
edge computing use cases, as shown in[I-D.liu-dyncast-ps-usecases].
To optimally deliver the service request to the most appropriate
service instance is the fundamental requirement in such deployments.
As shown in [I-D.liu-dyncast-ps-usecases], choosing the most
appropriate service instance should take both, the computing
resources available and the network path quality, into consideration.
"Optimal" here additionally means the architecture and overall
mechanism should be efficient, support high dynamism, while
maintaining instance affinity, as shown in
[I-D.liu-dyncast-ps-usecases].
This draft provides the requirements to realize the potential dynamic
anycast architecture by alleviating the problems of existing
solutions outlined in [I-D.liu-dyncast-ps-usecases]
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2. Definition of Terms
Service: A monolithic functionality that is provided by an endpoint
according to the specification for said service. A composite
service can be built by orchestrating monolithic services.
Service instance: Running environment (e.g., a node) that makes the
functionality of a service available. One service can have several
instances running at different network locations.
Service identifier: Used to uniquely identify a service, at the same
time identifying the whole set of service instances that each
represent the same service behaviour, no matter where those service
instances are running.
Anycast: An addressing and packet sending methodology that assign an
"anycast" identifier for one or more service instances to which
requests to an "anycast" identifier could be routed, following the
definition in [RFC4786] as anycast being "the practice of making a
particular Service Address available in multiple, discrete,
autonomous locations, such that datagrams sent are routed to one of
several available locations".
Dyncast: Dynamic Anycast, taking the dynamic nature of computing
resource metrics into account to steer an anycast-like decision in
sending an incoming service request.
3. Desirable System Characteristics and Requirements
In the following, we outline the desirable characteristics of a
system to overcome the observed problems in
[I-D.liu-dyncast-ps-usecases] for the realization of the use cases
described in that document.
3.1. Anycast-based Service Addressing Methodology
A unique service identifier is used by all the service instances for
a specific service no matter which edge it attaches to. An anycast
like addressing and routing methodology among multiple edges makes
sure the data packet can potentially reach any of the edges with the
service instance attached. At the same time, each service instance
has its own unicast address to be used by the attaching edge to
access the service.Since a client will use the service identifier as
the destination addressing, mapping of the service identifier to the
unicast address will need to happen in-band, considering the metrics
for selection to make this selection service-specific. From an
addressing perspective, a desirable system for the realization of the
use cases described in that document.
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o MUST provide a discovery and mapping methodology for the in-band
mapping of the service identifier (an anycast address) to a specific
unicast address.
3.2. Instance Affinity
A routing relation between a client and a service exists not at the
packet but at the service request level in the sense that one or more
service requests, possibly consisting of one or many more routing-
level packets, must be ensured to be sent to said service.Each
service may be provided by one or more service instances, each
providing equivalent service functionality to their respective
clients, while those service instances may be deployed at different
locations in the network. With that, the routing problem becomes one
between the client and a selected service instance for at least the
duration of the service-level request, but possibly more than just
one request.
This relationship between the client and the chosen service instance
is described as "instance affinity" in the following, where the
"affinity" spans across the aforementioned one or more service
requests. This impacts the routing decision to be taken in that the
normal packet level communication, i.e., each packet is forwarded
individually based on the forwarding table at the time, will need
extending with the notion of instance affinity since otherwise
individual packets may be sent to different places when the network
status changes, possibly segmenting individual requests and breaking
service-level semantics.
The nature of this affinity is highly dependent on the nature of the
specific service. The minimal affinity of a single request
represents a stateless service, where each service request may be
responded to without any state being held at the service instance for
fulfilling the request. Providing any necessary information/state
in-band as part of the service request, e.g., in the form of a multi-
form body in an HTTP request or through the URL provided as part of
the request, is one way to achieve such stateless nature.
Alternatively, the affinity to a particular service instance may span
more than one request, as in our VR example in
[I-D.liu-dyncast-ps-usecases], where previous client input is needed
to render subsequent frames. Therefore, a desirable system
o MUST maintain "instance affinity" which MAY span one or more
service requests, i.e., all the packets from the same flow MUST go to
the same service instance.
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3.3. Proper Runtime-state Granularity and Keeping
The instance affinity, as outlined in Section 3.2, requires a client
and the chosen service instance to keep persistent relationship
across one or more service requests. For a multi-request session,
this determines that the mapping logic has to consistently pick up
the same service instance. This type of affinity can be normally
achieved by deploying a mapping device to keep in-place all the
necessary states. However, a client, e.g., a mobile UE, has
generally many applications running. If all, or majority, of the
applications request the dyncast-like services, then the runtime
states that need to be created and accordingly maintained would
require high granularity. In the extreme scenario, this granular
requirement could reach the level of per-UE per-APP per-(sub)flow
with regard to a service instance.
Evidently, these fine-granular runtime states can potentially become
heavy burden for network devices if they have to dynamically create
and maintain them. On the other hand, it is not appropriate either
to place the state-keeping task on clients themselves. Therefore, a
desirable system
o MUST avoid keeping fine runtime-state granularity in network nodes
in order to achieve instance affinity.
o MUST provide mechanism to free clients from maintaining granular
runtime-states in order to achieve instance affinity.
3.4. Encoding Metrics
As outlined in the scenarios in [I-D.liu-dyncast-ps-usecases],
metrics can have many different semantics, particularly if considered
to be service- specific. Even the notion of a "computing load"
metric may be computed in many different ways. What is crucial,
however, is the representation and encoding of that metric when being
conveyed to the routing fabric in order for the routing elements to
act upon those metrics. Such representation may entail information
on the semantics of the metric or it may be purely one or more
semantic-free numerals. Agreement of the chosen representation among
all service and network elements participating in the service-
specific routing decision is important. Specifically, a desirable
system
o MUST agree on the service-specific metrics and their representation
between service elements in the participating edges in the network
and network elements acting upon them.
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o MAY obfuscate the specific semantic of the metric to preserve
privacy of the service provider information towards the network
provider.
o MAY include routing protocol metrics
3.5. Signaling Metrics
The aforementioned representation of metrics needs conveyance to the
network elements that will need to act upon them. Depending on the
service-specific decision logic, one or more metrics will need to be
conveyed. Problems to be addressed here may be that of loop
avoidance of any advertisement of metrics as well as the frequency of
such conveyance and therefore the overall load that the signaling may
add to the overall network traffic. While existing routing protocols
may serve as a baseline for signaling metrics, other means to convey
the metrics can equally be realized. Specifically, a desirable
system
o MUST provide mechanisms to signal the metrics for using in routing
decisions
o MUST realize means for rate control for signaling of metrics
o MUST implement mechanisms for loop avoidance in signaling metrics,
when necessary
3.6. Using Metrics in Routing Decisions
Metrics being conveyed, as outlined in Section 3.4, in the agreed
manner, as outlined in Section 3.3, will ultimately need suitable
action in the routers of the network. Routing decisions can be
manifold, possibly including (i) min or max over all metrics, (ii)
extending previous action with a random or first choice when more
than one min/max entry found, (iii) weighted round robin of all
entries, among others. It is important for the proper work of the
service-specific routing decision, that it is understood to both
network and service provider, which action (out of a possible set of
supported actions) is to be used for a particular set of metrics.
Specifically, a desirable system
Further, different network nodes, e.g., routers, switches, etc., bear
diversified capabilities even in the same routing domain, let alone
in different administrative domains. So, the service-specific
metrics that have been adopted by some nodes might not be supported
by others, either due to technical reasons, administrative reasons,
or something else. There could be some scenario that a node
supporting service-specific metrics might prefer some type of metrics
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to others [3GPP-TR22.847], or, in another scenario, even not utilize
any at all. Therefore, there must exist flexibility in term of
metrics handling and routing decisions in a network.
o MUST specify a default action to be taken, if more than one action
possible
o MUST allow a network node not supporting service-specific metrics
to interoperate with the supporting ones, i.e., providing backward
compatibility.
o SHOULD allow the prioritization of using the service-specific
metrics when compared to the currently widely-used networking
metrics, like bandwidth, delay, loss, etc.
o SHOULD enable other alternative actions to be taken. (1)Any
solution MUST provide appropriate signaling of the desired action to
the router. For this, the action MAY be signaled in combination with
signaling the metric (see Section 3.4). (2)Any solution SHOULD allow
associating the desired action to a specific service identifier.
3.7. Supporting Service Dynamism
Network cost in the current routing system usually does not change
very frequently. However, computing load and service-specific
metrics in general can be highly dynamic, e.g., changing rapidly with
the number of sessions, CPU/GPU utilization and memory space. It has
to be determined at what interval or events such information needs to
be distributed among edges. More frequent distribution of more
accurate synchronization may result in more overhead in terms of
signaling.
Choosing the least path cost is the most common rule in routing.
However, the logic does not work well when routing should be aware of
service-specific metrics. Choosing the least computing load may
result in oscillation. The least loaded edge can quickly be flooded
by the huge number of new computing demands and soon become
overloaded with tidal effects possibly following.
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Generally, a single instance may have very dynamic resource
availability over time in order to serve service requests. This
availability may be affected by computing resource capability and
load, network path quality, and others. The balancing mechanisms
should adapt to the service dynamism quickly and seamlessly. With
this, the relationship between a single client and the set of
possible service instances may possibly be very dynamic in that one
request that is being dispatched to instance A may be followed by a
request that is being dispatched to instance B and so on, generally
within the notion of the service-specific service affinity discussed
before in Section 3.2. With this in mind, a desirable system
o MUST support the dynamics of metrics changing on, e.g., a per flow
basis, without violating the metrics defined in the selection of the
specific service instance, while taking into account the requirements
for the signaling of metrics and routing decision (see Section 3.4
and 3.5).
4. Conclusion
This document presents high-level requirements for solutions to
Dyncast, where the architecture should address how to distribute the
resource information and how to assure instance affinity in an
anycast based service addressing environment, while realizing
appropriate routing actions to satisfy the metrics provided.
5. Security Considerations
TBD
6. IANA Considerations
No IANA action is required so far.
7. Contributors
The following people have substantially contributed to this document:
Peter Willis
BT
8. Informative References
[RFC4786] Abley, J. and K. Lindqvist, "Operation of Anycast
Services", BCP 126, RFC 4786, DOI 10.17487/RFC4786,
December 2006, <https://www.rfc-editor.org/info/rfc4786>.
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[I-D.liu-dyncast-ps-usecases]
Liu, P., Willis, P., Trossen, D., and C. Li, "Dynamic-
Anycast (Dyncast) Use Cases & Problem Statement", Work in
Progress, Internet-Draft, draft-liu-dyncast-ps-usecases-
02, 17 January 2022, <https://www.ietf.org/archive/id/
draft-liu-dyncast-ps-usecases-02.txt>.
[TR22.874] 3GPP, "Study on traffic characteristics and performance
requirements for AI/ML model transfer in 5GS (Release
18)", 2020.
Acknowledgements
The author would like to thank Yizhou Li, Luigi IANNONE and Geng
Liang for their valuable suggestions to this document.
Authors' Addresses
Peng Liu
China Mobile
Email: liupengyjy@chinamobile.com
Tianji Jiang
China Mobile
Email: jiangtianji@chinamobile.com
Philip Eardley
British Telecom
Email: philip.eardley@bt.com
Dirk Trossen
Huawei Technologies
Email: dirk.trossen@huawei.com
Cheng Li
Huawei Technologies
Email: c.l@huawei.com
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