draft-ietf-opsawg-large-flow-load-balancing-02.txt   draft-ietf-opsawg-large-flow-load-balancing-03.txt 
OPSAWG R. Krishnan OPSAWG R. Krishnan
Internet Draft S. Khanna Internet Draft S. Khanna
Intended status: Informational Brocade Communications Intended status: Informational Brocade Communications
Expires: December 25, 2013 L. Yong Expires: January 25, 2014 L. Yong
June 25, 2013 Huawei USA July 9, 2013 Huawei USA
A. Ghanwani A. Ghanwani
Dell Dell
Ning So Ning So
Tata Communications Tata Communications
B. Khasnabish B. Khasnabish
ZTE Corporation ZTE Corporation
Mechanisms for Optimal LAG/ECMP Component Link Utilization in Mechanisms for Optimal LAG/ECMP Component Link Utilization in
Networks Networks
draft-ietf-opsawg-large-flow-load-balancing-02.txt draft-ietf-opsawg-large-flow-load-balancing-03.txt
Status of this Memo Status of this Memo
This Internet-Draft is submitted in full conformance with the This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79. This document may not be modified, provisions of BCP 78 and BCP 79. This document may not be modified,
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as an RFC and to translate it into languages other than English. as an RFC and to translate it into languages other than English.
Internet-Drafts are working documents of the Internet Engineering Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF), its areas, and its working groups. Note that Task Force (IETF), its areas, and its working groups. Note that
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and may be updated, replaced, or obsoleted by other documents at any and may be updated, replaced, or obsoleted by other documents at any
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This Internet-Draft will expire on December 25, 2013. This Internet-Draft will expire on January 9, 2009.
Copyright Notice Copyright Notice
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document authors. All rights reserved. document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal This document is subject to BCP 78 and the IETF Trust's Legal
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publication of this document. Please review these documents publication of this document. Please review these documents
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4.3.2. Criteria for Identifying a Large Flow...............10 4.3.2. Criteria for Identifying a Large Flow...............10
4.3.3. Sampling Techniques.................................11 4.3.3. Sampling Techniques.................................11
4.3.4. Automatic Hardware Recognition......................12 4.3.4. Automatic Hardware Recognition......................12
4.4. Load Re-balancing Options................................13 4.4. Load Re-balancing Options................................13
4.4.1. Alternative Placement of Large Flows................13 4.4.1. Alternative Placement of Large Flows................13
4.4.2. Redistributing Small Flows..........................13 4.4.2. Redistributing Small Flows..........................13
4.4.3. Component Link Protection Considerations............14 4.4.3. Component Link Protection Considerations............14
4.4.4. Load Re-balancing Algorithms........................14 4.4.4. Load Re-balancing Algorithms........................14
4.4.5. Load Re-Balancing Example...........................14 4.4.5. Load Re-Balancing Example...........................14
5. Information Model for Flow Re-balancing.......................15 5. Information Model for Flow Re-balancing.......................15
5.1. Configuration Parameters for Flow Re-balancing...........15 5.1. Configuration Parameters for Flow Re-balancing...........16
5.2. System Configuration and Identification Parameters.......16 5.2. System Configuration and Identification Parameters.......16
5.3. Information for Alternative Placement of Large Flows.....17 5.3. Information for Alternative Placement of Large Flows.....17
5.4. Information for Redistribution of Small Flows............17 5.4. Information for Redistribution of Small Flows............17
5.5. Export of Flow Information...............................17 5.5. Export of Flow Information...............................17
5.6. Monitoring information...................................18 5.6. Monitoring information...................................18
5.6.1. Interface (link) utilization........................18 5.6.1. Interface (link) utilization........................18
5.6.2. Other monitoring information........................18 5.6.2. Other monitoring information........................18
6. Operational Considerations....................................18 6. Operational Considerations....................................18
7. IANA Considerations...........................................19 7. IANA Considerations...........................................19
8. Security Considerations.......................................19 8. Security Considerations.......................................19
9. Acknowledgements..............................................19 9. Acknowledgements..............................................20
10. References...................................................20 10. References...................................................20
10.1. Normative References....................................20 10.1. Normative References....................................20
10.2. Informative References..................................20 10.2. Informative References..................................20
1. Introduction 1. Introduction
Networks extensively use LAG/ECMP techniques for capacity scaling. Networks extensively use LAG/ECMP techniques for capacity scaling.
Network traffic can be predominantly categorized into two traffic Network traffic can be predominantly categorized into two traffic
types: long-lived large flows and other flows (which include long- types: long-lived large flows and other flows (which include long-
lived small flows, short-lived small/large flows). Stateless hash- lived small flows, short-lived small/large flows). Stateless hash-
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Figure 3: Evenly utilized Composite Links Figure 3: Evenly utilized Composite Links
Basically, the use of the mechanisms described in Section 4.4.1 Basically, the use of the mechanisms described in Section 4.4.1
resulted in a rebalancing of flows where one of the large flows on resulted in a rebalancing of flows where one of the large flows on
component link (3) which was previously congested was moved to component link (3) which was previously congested was moved to
component link (2) which was previously under-utilized. component link (2) which was previously under-utilized.
5. Information Model for Flow Re-balancing 5. Information Model for Flow Re-balancing
In order to support flow rebalancing in a router from an external
system, the exchange of some information is necessary between the
router and the external system. This section provides an exemplary
information model covering the various components needed for the
purpose. The model is intended to be informational and may be used
as input for development of a data model.
5.1. Configuration Parameters for Flow Re-balancing 5.1. Configuration Parameters for Flow Re-balancing
The following parameters are required the configuration of this The following parameters are required the configuration of this
feature: feature:
. Large flow recognition parameters: . Large flow recognition parameters:
o Observation interval: The observation interval is the time o Observation interval: The observation interval is the time
period in seconds over which the packet arrivals are period in seconds over which the packet arrivals are
observed for the purpose of large flow recognition. observed for the purpose of large flow recognition.
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the ACM SIGCOMM, August 2011. the ACM SIGCOMM, August 2011.
[NDTM] Estan, C. and G. Varghese, "New directions in traffic [NDTM] Estan, C. and G. Varghese, "New directions in traffic
measurement and accounting," Proceedings of ACM SIGCOMM, August 2002. measurement and accounting," Proceedings of ACM SIGCOMM, August 2002.
[bin-pack] Coffman, Jr., E., M. Garey, and D. Johnson. Approximation [bin-pack] Coffman, Jr., E., M. Garey, and D. Johnson. Approximation
Algorithms for Bin-Packing -- An Updated Survey. In Algorithm Design Algorithms for Bin-Packing -- An Updated Survey. In Algorithm Design
for Computer System Design, ed. by Ausiello, Lucertini, and Serafini. for Computer System Design, ed. by Ausiello, Lucertini, and Serafini.
Springer-Verlag, 1984. Springer-Verlag, 1984.
Appendix A. Internet Traffic Analysis and Load Balancing Simulation Appendix A. Internet Traffic Analysis and Load Balancing Simulation
Internet traffic [CAIDA] has been analyzed to obtain flow statistics Internet traffic [CAIDA] has been analyzed to obtain flow statistics
such as the number of packets in a flow and the flow duration. The such as the number of packets in a flow and the flow duration. The
five tuples in the packet header (IP addresses, TCP/UDP Ports, and IP five tuples in the packet header (IP addresses, TCP/UDP Ports, and IP
protocol) are used for flow identification. The analysis indicates protocol) are used for flow identification. The analysis indicates
that < ~2% of the flows take ~30% of total traffic volume while the that < ~2% of the flows take ~30% of total traffic volume while the
rest of the flows (> ~98%) contributes ~70% [YONG]. rest of the flows (> ~98%) contributes ~70% [YONG].
The simulation has shown that given Internet traffic pattern, the The simulation has shown that given Internet traffic pattern, the
hash-based technique does not evenly distribute the flows over ECMP hash-based technique does not evenly distribute the flows over ECMP
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