Problem Statement for Simplified Use of Policy Abstractions (SUPA)
draft-karagiannis-supa-problem-statement-06

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

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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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