Internet DRAFT - draft-karagiannis-supa-problem-statement
draft-karagiannis-supa-problem-statement
Network Working Group G. Karagiannis
Internet Draft J. Strassner
Intended status: Informational Huawei Technologies
Expires: December 5, 2015 Q. Sun
China Telecom
Luis M. Contreras
Telefonica
P. Yegani
Juniper Networks
J.Bi
Tsinghua University
June 5, 2015
Problem Statement for Simplified Use of Policy Abstractions (SUPA)
draft-karagiannis-supa-problem-statement-07
Abstract
The increase in complexity of modern networks makes it challenging to
deploy new services and to keep networks up to date whilst
maintaining stability and availability for critical business
services. This is a major challenge that network operators (service
providers, SME, etc) face today. The operators aim of streamlining
both operations and the deployment of new services, is being met by
increasingly relying on (1) software abstractions to simplify the
design and configuration of monitoring and control operations and (2)
the use of programmatic control over the configuration and operation
of such networks.
In this context, providing network operators with a generic policy-
based management model that can be used to express policies on top
of arbitrary configuration data models is essential.
In particular, SUPA addresses the needs of operators and application
developers to use a generic policy-based management model for
defining and representing multiple types of policy rules.
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . .2
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . .3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Use Case: Distributed Data Centers (DDCs) . . . . . . . . . 5
4. Requirements . . . . . . . . . . . . . . . . . . . . . . . . . 6
5. Security Considerations . . . . . . . . . . . . . . . . . . . 6
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 6
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 6
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 7
8.1 Normative References . . . . . . . . . . . . . . . . . . 7
8.2 Informative References . . . . . . . . . . . . . . . . . 7
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 7
1. Introduction
Network operators are faced with networks of increasing size and
complexity while trying to improve their quality and availability, as
more and more business services depend on them. Software abstractions
to simplify the design and configuration of monitoring and control
operations and the use of programmatic control, often called
software-defined, are considered by many network operators as an
essential tool toward the management of that complexity.
Providing means to network operators to (1) express policies on top
of arbitrary configuration data models and (2) represent multiple
types of policy rules, enable significant improvements in
configuration agility, error detection and uptime for operators.
This document describes the problems that need to be addressed in
order to equip service providers with the means, such as a generic
policy-based management model used to represent multiple types of
policy rules to quickly and dynamically manage their offering of
network services.
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1.1 Motivation
The rapid growth in the variety and importance of traffic flowing
over increasingly complex enterprise and service provider network
makes the task of network operations and management applications and
of deploying new services much more difficult.
This is a significant challenge that network operators (service
providers, SME, etc) face today.
Several mechanisms can be used to deal with this challenge. The main
ones are: (1) the use of software abstractions to simplify the design
and configuration of monitoring and control operations and (2) the
use of programmatic control over the configuration and operation of
such networks. By combining these mechanisms can (1) provide
additional and significant benefits in design and deployment agility
and (2) be used to define a generic policy-based management model.
In particular, the power of policy management is its applicability to
many different types of systems. Many different types of actors can
be identified that can use a policy management system, including
applications, end-users, developers, network administrators and
operators. Each of these actors, typically, has different skills and
uses different concepts and terminologies. For example, an operator
may want to express that only Platinum and Gold users can use
streaming and interactive multimedia applications. As a second
example, an operator may want to define a more concrete policy rule
that looks at the number of dropped packets. If, for example, this
number exceeds a certain threshold value, then the applied queuing,
dropping and scheduling algorithms could be changed in order to
reduce the number of dropped packets.
Both examples can be referred to as "policy rules", but they take
very different forms, since they are at very different levels of
abstraction and likely authored by different actors. The first
example described a very abstract policy rule, and did not contain
any technology-specific terms, while the second example included a
more concrete policy rule and likely used technical terms of a
general (e.g., IP address range, port numbers) as well as vendor-
specific nature (e.g., specific algorithms implemented in a
particular device). Furthermore, these two policy rules could affect
each other. For example, Gold and Platinum users might need different
device configurations to give the proper QoS markings to their
streaming multimedia traffic. This is very difficult to do if a
common policy framework does not exist.
It needs to be mentioned that there are ongoing policy modeling
efforts in IETF. However, all these policy modeling models can be
characterized as being technology specific. This means that the IETF
needs to reinvent the wheel in different colors (i.e., policy models
that apply for a specific technology) several times.
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SUPA will address these challenges by:
(1) developing an information model fragment for defining
standardized policy rules at different levels of abstraction,
(2) specifying how to map this information fragment into
corresponding YANG [RFC6020] and [RFC6991], data models to
define interoperable implementations that can exchange and
modify generic policies using protocols such as NETCONF/RESTCONF
on the interface north of the controller (or other similar
management entity) and south of the service manager.
Specifically, three information model fragments are envisioned:
(a) a generic policy information model (GPIM) that defines concepts
needed by policy management independent of the form and content of
the policy
(b) a more specific information model that refines the generic
information model to specify how to build policy rules of the
event-condition-action (ECA) paradigm
(c) a more specific information model that refines the generic
information model to specify how to build policy rules that
declaratively specify what goals to achieve (but not how to
achieve those goals); this is often called "intent-based" policy
2. Terminology
Some of definitions are based on [RaBe11] and/or [Stras02].
Network Service: the composition of network functions as defined
by its functional and behavioral specification. A network service
is characterized by performance, dependability, and security
specifications. Furthermore, a network service is delivered by
network service endpoints, which may be aggregations of multiple
lower-layer technology specific endpoints.
Network Element: a physical or virtual entity that implements one or
more network function(s). NEs can interact with local or remote
network controllers in order to exchange information, such as
configuration information and status.
Service specific abstraction: an abstract view of the service
topology, associated with a specific network service type, e.g.,
inter-datacenter communication services
Policy: a definite goal, course, or method of action to guide and
determine present and future decisions. Policies are implemented or
executed within a particular context.
SUPA policy: a means to monitor and control the changing and/or
maintaining of the state of one or more managed entities.
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Policy-based management: the usage of policy rules to manage one or
more entities.
Information Model: a representation of managed objects and their
relationships that is independent of data repository, language, and
protocol.
Data Model: a representation of managed objects and their
relationships that is dependent on data repository, language, and/or
protocol (typically all three).
Policy Rule: A container that uses metadata to define how the content
is interpreted, and hence, how the behavior that it governs is
defined separates the content of the policy from its representation
provides a convenient control point for OAMP operations.
Policy condition: a representation of the necessary state and/or
prerequisites that define whether a policy rule's actions should be
performed.
Policy action: defines what is to be done to enforce a policy rule
when its conditions are met.
Event Condition Action policy: reactive behavior of a system that
correlates a set of events, a set of conditions, and a set of
actions. Conditions are evaluated on the occurrence of an event and
which determine whether the policy is applicable or not for that
particular situation. Furthermore, the actions are only executed only
if the conditions are met.
Goal (Intent) policy rule (also called a declarative policy rule, or
an intent-based policy rule): a declarative statement that
defines what the policy should do, but not how to implement the
policy.
Model Mapping: a translation from one type of model to another type
of model. Model mapping changes the representation and/or level of
abstraction used to another representation and/or level of
abstraction. The most common form of model mapping is from an
information model to a data model; another important form is from a
vendor-neutral data model to a vendor-specific data model.
3. Use Case: Distributed Data Centers (DDCs)
Large scale Distributed Data Centers (DDCs) can provide various
services and usually consist of many internal and external links
where various VPNs are built upon. The Service provisioning and
network connectivity configurations could be complex and dynamic, for
which manual configuration is not onerous and error-prone.
The SUPA generic policy management models can be used to support the
dynamic and automated resource usage and simplify and automate the
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service/network deployment/configuration of various VPN scenarios in
the DDC environment. A more detailed description of this use case is
provided in [ID.draft-cheng-supa-ddc-use-cases].
4. Requirements
In order to satisfy the challenges mentioned in Section 1.1 and the
goal of the DDC use case briefly described in section 3, the
following requirements need to be addressed:
o) Specify a generic and non-technology specific policy information
model.
o) Specify a more specific information model that defines how to
build policy rules of the event-condition-action (ECA) paradigm.
o) Specify a more specific information model that defines how to
build policy rules that declaratively specify what goals (what
intents) to achieve using the Goal (Intent) policy paradigm.
o) Specify how to map the above mentioned information models into
corresponding YANG standardized data models to
define interoperable implementations that can exchange and modify
generic policies using protocols such as NETCONF/RESTCONF on the
interface north of the controller (or other similar management
entity) and south of the service manager.
5. Security Considerations
Security is a key aspect of any protocol that allows state
installation and extracting detailed configuration states of network
elements. This places additional security requirements on SUPA (e.g.,
authorization, and authentication of network services) that needs
further investigation. Moreover, policy interpretation can lead to
corner cases and side effects that should be carefully examined,
e.g., in case policy rules are conflicting with each other.
6. IANA Considerations
This document has no actions for IANA.
7. Acknowledgements
The authors of this draft would like to thank the following
persons for the provided valuable feedback and contributions:
Diego Lopez, Spencer Dawkins, Jun Bi, Xing Li, Chongfeng Xie, Benoit
Claise, Ian Farrer, Marc Blancet, Zhen Cao, Hosnieh Rafiee, Mehmet
Ersue, Simon Perreault, Fernando Gont, Jose Saldana, Tom Taylor,
Kostas Pentikousis, Juergen Schoenwaelder, John Strassner, Eric Voit,
Scott O. Bradner, Marco Liebsch, Scott Cadzow, Marie-Jose Montpetit.
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Tina Tsou, Will Liu and Jean-Francois Tremblay contributed to an
early version of this draft.
8. References
8.1. Normative References
8.2. Informative References
[ID.draft-cheng-supa-ddc-use-cases] Y. Cheng, JF. Tremblay, J. Bi,
L. M. Contreras, "Use Case for Distributed Data Center in SUPA", IETF
Internet draft (Work in progress), draft-cheng-supa-ddc-use-cases-07,
May 8, 2015
[RFC6020] M. Bjorklund, "YANG - A Data Modeling Language for the
Network Configuration Protocol (NETCONF)", RFC 6020,
October 2010.
[RFC6991] J. Schoenwaelder, "Common YANG Data Types", RFC 6991,
July 2013.
[RaBe11] Raphael Romeikat, Bernhard Bauer, "Formal Specification of
DomainSpecific ECA Policy Models", in Proc. 2011 Fifth IEEE
International Conference on Theoretical Aspects of Software
Engineering, 2011
[Stras02] John Strassner, "DEN-ng: Achieving Business-Driven Network
Management" in Proc. IEEE Network Operations and Management Symposium
(NOMS), 2002.
Authors' Addresses
Georgios Karagiannis
Huawei Technologies
Hansaallee 205,
40549 Dusseldorf,
Germany
Email: Georgios.Karagiannis@huawei.com
Qiong Sun
China Telecom
No.118 Xizhimennei street, Xicheng District
Beijing 100035
P.R. China
Email: sunqiong@ctbri.com.cn
Luis M. Contreras
Telefonica I+D
Ronda de la Comunicacion, Sur-3 building, 3rd floor
Madrid 28050
Spain
Email: luismiguel.contrerasmurillo@telefonica.com
URI: http://people.tid.es/LuisM.Contreras/
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Parviz Yegani
JUNIPER NETWORKS
1133 Innovation Way
Sunnyvale, CA 94089
Email: pyegani@juniper.net
John Strassner
Huawei Technologies
2330 Central Expressway
Santa Clara, CA 95138 USA
Email: john.sc.strassner@huawei.com
Jun Bi
Tsinghua University
Network Research Center, Tsinghua University
Beijing 100084
China
EMail: junbi@tsinghua.edu.cn
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