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Network Working Group G. Karagiannis
Internet-Draft Huawei Technologies
Intended status: Informational Q. Sun
Expires: September 9, 2015 China Telecom
Luis M. Contreras
Telefonica
P. Yegani
Juniper Networks
JF Tremblay
Viagenie
J.Bi
Tsinghua University
March 9, 2015
Problem Statement for Simplified Use of Policy Abstractions (SUPA)
draft-karagiannis-supa-problem-statement-06
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 programmatic control of network elements and
by the use of various virtualization technologies. In this context,
providing network operators with a set of standard generic YANG-based
service and policy models that enable management and automation
of services on their network is essential.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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material or to cite them other than as "work in progress."
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Copyright Notice
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . .2
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . .3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.1 Inter Data Centers (IDC) . . . . . . . . . . . . . . . . . . 4
3.2 DTS (DC Traffic Schedule) . . . . . . . . . . . . . . . . . 4
3.3 Flexible VPN Set-Up in Campus Environments . . . . . . . . . 5
3.4 VPNs connecting VPCs (Virtual Private Clouds) and
data centers . . . . . . . . . . . . . . . . . . . . . . . . 5
3.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . 5
4. Requirements/Challenges . . . . . . . . . . . . . . . . . . . . 6
5. Security Considerations . . . . . . . . . . . . . . . . . . . 7
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 7
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 7
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. Programmatic ways to
configure networks, often called software-defined, are considered by
many network operators an essential tool toward the management of
that complexity.
Providing means of exposing a view of the network to applications
provides significant improvements in configuration agility, error
detection and uptime for operators.
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This document describes the problems that need to be addressed in
order to equip service providers with the means, such as generic
network service models and generic policy rule models, to quickly and
dynamically manage their offering of network services.
1.1 Motivation
The rapid increase in the complexity of managing virtual paths makes
it significantly more challenging to operate and improve networks. In
particular, the expansion and management of virtual connections,
and the virtualization of networks and services using
data centers are creating much more complex and dynamic networks.
This is a significant challenge that network operators (service
providers, SME, etc) face today.
Three main mechanisms can be used to deal with this
growing complexity:
o) the use of software abstractions. This mechanism enables the
construction of the simplified views of networks, which hides
complexity from applications while allowing them to configure
common functions within a domain.
o) the increase in programmatic control over the configuration and
operation of networks. This mechanism uses the software
abstractions and control points to more quickly define and
manage network services.
o) apply generic policy models that enable network operators to
craft their own policy rules.
Combining these mechanisms provides additional and significant
benefits in design and deployment agility.
These main challenges can be addressed by developing a policy driven
service management methodology that incorporates generic models, by
which network services can be managed using standardized and generic
policy rule models.
2. Terminology
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.
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Service specific abstraction: an abstract view of the service
topology, associated with a specific network service type, e.g.,
inter-datacenter communication services
3. Use Cases
This section briefly describes the use cases that are associated with
different types of network services. A more detailed description of
these use cases is provided in [ID.draft-cheng-supa-ddc-use-cases].
3.1 Inter Data Centers (IDC)
A large-scale IDC (Inter Data Center) operator provides server
hosting, bandwidth, and value-added services to enterprises and ISPs,
and has more than 10 data centers and more than 1Tbs bandwidth in a
capital city. In current IDC networks, traffic is routed by
applying routing policies and adjusting route prioritization to
prefer specific links. Link bandwidth in the data centers are often
overprovisioned and therefore not efficiently utilized. Services
usually have variable bandwidth requirements depending of the time of
day, e.g. video ISP usually require more bandwidth at non-working
hours but require less bandwidth at working hours. Some customers
have high QoS requirement for their services, e.g. IM (Instant
Messaging). Such scenarios are worth modeling because static
bandwidth allocations and manual QoS provisioning for all services is
not a cost-effective solution on the long term.
Network operators will benefit from using the policy driven service
management methodology that can be applied to design flexible
adjustment policies for bandwidth allocations and dynamic QoS
provisioning.
3.2 DTS (Datacenter Traffic Schedule)
China Telecom is part of a group of operators testing and
implementing a new management schema called Datacenter Traffic
Schedule (DTS). Due to the rapid development of Internet services,
each single datacenter location cannot meet all the requirements of
a given service. A general model has been developed to host service
instances in multiple collaborating datacenters. More specifically,
client systems can request resources from a single virtual
datacenter, making the service more flexible and scalable. This also
provides for more reliability and security of services. As a result,
inter datacenter traffic has increased dramatically during the last
years. Service instances located in different datacenters will
exchange large volume of data for backup and storage, which may
occur at a fixed or variant times each day. In such an environment, a
management system is able to monitor traffic volume on the links
between datacenters and react accordingly to prevent synchronization
and resource exhaustion. When the volume exceeds the threshold set
by the system, it requests traffic schedules may be adjusted within
bounds in a dynamic policy driven framework in order traffic to move
overflowing traffic on other links. Such scenarios are well worth
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modeling as operators need to design flexible adjustment of
scheduling policies for optimizing the throughput of datacenter edge
routers.
3.3 Flexible VPN Set-Up in Campus Environments
There are requirements from campus network operators to flexibly
manage traffic for multiple functions in a building, such as traffic
for network operation, traffic for building monitoring network,
traffic for professor working on test-bed/data for different research
projects. Traditionally, the operation staffs manually set up VLANs
for different users. However, the increasing number of projects/users
makes it very hard to manually set up those different
network/test-beds in the shared building LAN, because sometimes one
office can have multiple access rights to access different
networks/projects.
Therefore, SUPA could potentially support the flexible VPN set up on
the shared infrastructure (based on IP/MAC address, VLAN ID, etc.).
In this case, a controller and standardized northbound APIs could
serve for an operator's application to flexibly set up the access to
different resources. In general, by providing a policy
driven service management methodology, network operators
will be able to define the network services for the different
academic and administrative functions along with policy rules that
govern the service instantiation, e.g., the dynamic creation and
maintenance of VPNs.
3.4 VPNs connecting VPCs (Virtual Private Clouds) and data
centers
Currently, Virtual Private Clouds (VPCs) are used to provide capacity
for various internal applications. The VPCs need to securely exchange
data with the local data center, which is not exposed to the general
Internet. Inter-site IPsec VPNs have been the mechanism of choice to
secure these connections in the past. However the complexity of
managing the VPNs increases exponentially as the number of VPCs and
the data centers becomes larger. By providing a policy
driven service management methodology enables network operators
to model, monitor and manage such VPNs.
3.5 Conclusion
SUPA aims at addressing the requirements imposed by these use
cases. SUPA provides a policy driven service management methodology,
by which network services can be managed using standardized and
generic policy rule models.
In particular, SUPA enables policies controlling network services,
that can dynamically request the optimization of the traffic paths
dynamically and have the ability to request load balancing between
data centers and links, and direct customer traffic via standard,
generic network management policies. Path optimization can be
accomplished using data models or software programs routines to
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differentiate customer based on their service class and/or QoS
requirements. Moreover, when VPN tunnels are interconnecting
datacenters, the policy driven service management methodology can be
used to dynamically reconfigure these VPNs in order to avoid possible
congested communication paths and improve end to end latency.
4. Requirements and Challenges
In order to satisfy the requirements imposed by the use cases
described in Section 3, a policy driven service management
methodology needs to be developed to address the following main
challenges:
1) in order to correctly execute, deploy and perform the network
service in the physical and/or virtual topology, generic network
service models that define the resources needed by the network
service for correct operation are required.
2) the management of a network service and the dynamical mapping of
the network service to the network topology and network resources
requires the specification and implementation of generic policy
rule models.
Several working groups in IETF such as I2RS, BESS, TEAS, PCE focus on
data models that describe the network element centric view.
Furthermore, some published Individual Internet drafts associated
with some of these IETF WGs focus on data models of physical and
virtual network topology. However, none of these IETF WGs focus on a
policy driven service management methodology that is able to provide:
o) generic network service YANG based data models, [RFC6020],
[RFC6991], that define the resources needed by the network
service for correct operation,
o) generic policy rule models that define how to manage the network
service and its required resources and that dynamically map
services to the network topology and resources.
SUPA can address the above listed requirements/challenges by
developing a policy driven service management, by which network
services can be managed using standardized and generic policy rule
models.
In particular, a network service is defined by a network service
topology. The network service topology data model can be seen as an
extension of a generic YANG topology model supporting multiple
topology layers and endpoint mapping functionality. The network
service topology is then mapped to the underlying network topology.
Using the policy driven service management methodology, a set of
generic policy rule models is defined to manage the network service.
In this approach, service specific policy models will be derived from
a generic policy model, ensuring that policies have a common
structure and can be easily interpreted and reused as managed
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objects.
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.
Tina Tsou and Will Liu 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,
"Use Cases for Distributed Data Center Applications in SUPA", IETF
Internet draft (Work in progress), draft-cheng-supa-ddc-use-cases-05,
February 6, 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.
Authors' Addresses
Georgios Karagiannis
Huawei Technologies
Hansaallee 205,
40549 Dusseldorf,
Germany
Email: Georgios.Karagiannis@huawei.com
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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/
Parviz Yegani
JUNIPER NETWORKS
1133 Innovation Way
Sunnyvale, CA 94089
Email: pyegani@juniper.net
Jean-Francois Tremblay
Viagenie inc.
Email: jean-francois.tremblay@viagenie.ca
Jun Bi
Tsinghua University
Network Research Center, Tsinghua University
Beijing 100084
China
EMail: junbi@tsinghua.edu.cn
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