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Versions: (draft-li-dynamic-flooding-isis) 00 01 02 03 04

Internet Engineering Task Force                                    T. Li
Internet-Draft                                           Arista Networks
Intended status: Informational                            March 18, 2018
Expires: September 19, 2018


          An Architecture for Dynamic Flooding on Dense Graphs
                      draft-li-dynamic-flooding-03

Abstract

   Routing with link state protocols in dense network topologies can
   result in sub-optimal convergence times due to the overhead
   associated with flooding.  This can be addressed by decreasing the
   flooding topology so that it is less dense.

   This document discusses the problem in some depth and an
   architectural solution.  Specific protocol changes are not described
   in this document.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

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   This Internet-Draft will expire on September 19, 2018.

Copyright Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   to this document.  Code Components extracted from this document must



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   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   3
   2.  Problem Statement . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Requirements  . . . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Dynamic Flooding  . . . . . . . . . . . . . . . . . . . . . .   4
     4.1.  Leader election . . . . . . . . . . . . . . . . . . . . .   5
     4.2.  Computing the Flooding Topology . . . . . . . . . . . . .   6
     4.3.  Topologies on Complete Bipartite Graphs . . . . . . . . .   7
       4.3.1.  A Minimal Flooding Topology . . . . . . . . . . . . .   7
       4.3.2.  Xia Topologies  . . . . . . . . . . . . . . . . . . .   7
       4.3.3.  Optimization  . . . . . . . . . . . . . . . . . . . .   8
     4.4.  Encoding the Flooding Topology  . . . . . . . . . . . . .   8
   5.  Applicability . . . . . . . . . . . . . . . . . . . . . . . .   8
   6.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .   9
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   9
   8.  Security Considerations . . . . . . . . . . . . . . . . . . .   9
   9.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   9
     9.1.  Normative References  . . . . . . . . . . . . . . . . . .   9
     9.2.  Informative References  . . . . . . . . . . . . . . . . .   9
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  10

1.  Introduction

   In recent years, there has been increased focused on how to address
   the dynamic routing of networks that have a bipartite (a.k.a. spine-
   leaf or leaf-spine), Clos [Clos], or Fat Tree [Leiserson] topology.
   Conventional Interior Gateway Protocols (IGPs, i.e. IS-IS [ISO10589],
   OSPF [RFC5340]) under-perform, redundantly flooding information
   throughout the dense topology, leading to overloaded control plane
   inputs and thereby creating operational issues.  For practical
   considerations, network architects have resorted to applying
   unconventional techniques to address the problem, applying BGP in the
   data center [RFC7938], however it is very clear that using an
   Exterior Gateway Protocol as an IGP is sub-optimal, if only due to
   the configuration overhead.

   The primary issue that is demonstrated when conventional mechanisms
   are applied is the poor reaction of the network to topology changes.
   Normal link state routing protocols rely on a flooding algorithm for
   state distribution.  In a dense topology, this flooding algorithm is
   highly redundant, resulting in unnecessary overhead.  Each node in
   the topology receives each link state update multiple times.



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   Ultimately, all of the redundant copies will be discarded, but only
   after they have reached the control plane and been processed.  This
   creates issues because significant link state database updates can
   become queued behind many redundant copies of another update.  This
   delays convergence as the link state database does not stabilize
   promptly.

   In a real world implementation, the packet queues leading to the
   control plane are necessarily of finite size, so if the flooding rate
   exceeds the update processing rate for long enough, the control plane
   will be obligated to drop incoming updates.  If these lost updates
   are of significance, this will further delay stabilization of the
   link state database and the convergence of the network.

   This is not a new problem.  Historically, when routing protocols have
   been deployed in networks where the underlying topology is a complete
   graph, there have been similar issues.  This was more common when the
   underlying link layer fabric presented the network layer with a full
   mesh of virtual connections.  This was addressed by reducing the
   flooding topology through IS-IS Mesh Groups [RFC2973], but this
   approach requires careful configuration of the flooding topology.

   Thus, the root problem is not limited to massively scalable data
   centers.  It exists with any dense topology at scale.

   This problem is not entirely surprising.  Link state routing
   protocols were conceived when links were very expensive and
   topologies were sparse.  The fact that those same designs are sub-
   optimal in a dense topology should not come as a huge surprise.  The
   fundamental premise that was addressed by the original designs was an
   environment of extreme cost and scarcity.  Technology has progressed
   to the point where links are cheap and common.  This represents a
   complete reversal in the economic fundamentals of network
   engineering.  The original designs are to be commended for continuing
   to provide correct operation to this point, and optimizations for
   operation in today's environment are to be expected.

1.1.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

2.  Problem Statement

   In a dense topology, the flooding algorithm that is the heart of
   conventional link state routing protocols causes a great deal of
   redundant messaging.  This is exacerbated by scale.  While the



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   protocol can survive this combination, the redundant messaging is
   unnecessary overhead and delays convergence.  Thus, the problem is to
   provide routing in dense, scalable topologies with rapid convergence.

3.  Requirements

   A solution to this problem must then meet the following requirements:

   Requirement 1    Provide a dynamic routing solution.  Reachability
       must be restored after any topology change.

   Requirement 2    Provide a significant improvement in convergence.

   Requirement 3    The solution should address a variety of dense
       topologies.  Just addressing a complete bipartite topology such
       as K5,8 is insufficient.  Multi-stage Clos topologies must also
       be addressed, as well as topologies that are slight variants.
       Addressing complete graphs is a good demonstration of generality.

   Requirement 4    There must be no single point of failure.  The loss
       of any link or node should not unduly hinder convergence.

   Requirement 5    Dense topologies are subgraphs of much larger
       topologies.  Operational efficiency requires that the dense
       subgraph not operate in a radically different manner than the
       remainder of the topology.  While some operational differences
       are permissible, they should be minimized.  Changes to nodes
       outside of the dense subgraph are not acceptable.  These
       situations occur when massively scaled data centers are part of
       an overall larger wide-area network.  Having a second protocol
       operating just on this subgraph would add much more complexity at
       the edge of the subgraph where the two protocols would have to
       inter-operate.

4.  Dynamic Flooding

   We have observed that the combination of the dense topology and
   flooding on the physical topology in a scalable network is sub-
   optimal.  However, if we decouple the flooding topology from the
   physical topology and only flood on a greatly reduced portion of that
   topology, we can have efficient flooding and retain all of the
   resilience of existing protocols.

   In this idea, one node is elected to compute the flooding topology
   for the dense subgraph.  This flooding topology is encoded into and
   distributed as part of the normal link state database.  Nodes within
   the dense topology would only flood on the flooding topology.  On
   links outside of the normal flooding topology, normal database



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   synchronization mechanisms (i.e., OSPF database exchange, IS-IS
   CSNPs) would apply, but flooding would not.  New link state
   information that arrives from outside of the flooding topology
   suggests that the sender has a different or no flooding topology
   information and that the link state update should be flooded on the
   flooding topology as well.

   Since the flooding topology is computed prior to topology changes, it
   does not factor into the convergence time and can be done when the
   topology is stable.  The speed of the computation and its
   distribution is not a significant issue.

   If a node has not received any flooding topology information when it
   receives new link state information, it should flood according to
   legacy flooding rules.  This situation will occur when the dense
   topology is first established, but is unlikely to recur.

   If, during a transient, there are multiple flooding topologies being
   advertised, then nodes should flood link state updates on all of the
   flooding topologies.  Each node should locally evaluate the election
   of the lead node for the dense subgraph and first flood on the
   topology of the lead node.  The rationale behind this is
   straightforward: if there is a transient and there has been a recent
   change in the elected node, then propagating topology information
   promptly along the most likely flooding topology should be the
   priority.

   During transients, it is possible that loops will form in the
   flooding topology.  This is not problematic, as the legacy flooding
   rules would cause duplicate updates to be ignored.  Similarly, during
   transients, it is possible that the forwarding topology may become
   disconnected.  To address this, nodes can perform a database
   synchronization check anytime a link is added to or removed from the
   flooding topology.

4.1.  Leader election

   The election of the node within the dense topology that computes the
   flooding topology is straightforward.  A generalization of the
   mechanisms used in existing Designated Router (OSPF) or Designated
   Intermediate-System (IS-IS) elections would suffice.  When a new node
   is elected and has distributed new flooding topology information,
   then the old node should withdraw its flooding topology information
   from the link state database.







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4.2.  Computing the Flooding Topology

   There is a great deal of flexibility in how the flooding topology is
   computed.  For resilience, it needs to at least contain a cycle of
   all nodes in the dense subgraph.  However, additional links could be
   added to decrease the convergence time.  The trade-off between the
   density of the flooding topology and the convergence time is a matter
   for further study.  The exact algorithm for computing the flooding
   topology need not be standardized, as it is not an interoperability
   issue.  Only the encoding of the result needs to be documented.

   While the flooding topology should be a covering cycle, it need not
   be a Hamiltonian cycle where each node appears only once.  In fact,
   in many relevant topologies this will not be possible.  Consider
   K5,8.  This is fortunate, as computing a Hamiltonian cycle is known
   to be NP-complete.

   A simple algorithm to compute the topology for a complete bipartite
   graph is to simply select unvisited nodes on each side of the graph
   until both sides are completely visited.  If the number of nodes on
   each side of the graph are unequal, then revisiting nodes on the less
   populated side of the graph will be inevitable.  This algorithm can
   run in O(N) time, so is quite efficient.

   While a simple cycle is adequate for correctness and resiliency, it
   may not be optimal for convergence.  At scale, a cycle may have a
   diameter that is half the number of nodes in the graph.  This could
   cause an undue delay in link state update propagation.  Therefore it
   may be useful to have a bound on the diameter of the flooding
   topology.  Introducing more links into the flooding topology would
   reduce the diameter, but at the trade-off of possibly adding
   redundant messaging.  The optimal trade-off between convergence time
   and graph diameter is for further study.

   Similarly, if additional redundancy is added to the flooding
   topology, specific nodes in that topology may end up with a very high
   degree.  This could result in overloading the control plane of those
   nodes, resulting in poor convergence.  Thus, it may be optimal to
   have an upper bound on the degree of nodes in the flooding topology.
   Again, the optimal trade-off between graph diameter, node degree, and
   convergence time, and topology computation time is for further study.

   If the leader chooses to include a multi-node broadcast LAN segment
   as part of the flooding topology, all of the connectivity to that LAN
   segment should be included as well.  Once updates are flooded onto
   the LAN, they will be received by every attached node.





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4.3.  Topologies on Complete Bipartite Graphs

   Complete bipartite graph topologies have become popular for data
   center applications and are commonly called leaf-spine or spine-leaf
   topologies.  In this section, we discuss some flooding topologies
   that are of particular interest in these networks.

4.3.1.  A Minimal Flooding Topology

   We define a Minimal Flooding Topology on a complete bipartite graph
   as one in which the topology is connected and each node has at least
   degree two.  This is of interest because it guarantees that the
   flooding topology has no single points of failure.

   In practice, this implies that every leaf node in the flooding
   topology will have a degree of two.  As there are usually more leaves
   than spines, the degree of the spines will be higher, but the load on
   the individual spines can be evenly distributed.

   This type of flooding topology is also of interest because it scales
   well.  As the number of leaves increases, we can construct flooding
   topologies that perform well.  Specifically, for n spines and m
   leaves, if m >= n(n/2-1), then there is a flooding topology that has
   a diameter of four.

4.3.2.  Xia Topologies

   We define a Xia Topology on a complete bipartite graph as one in
   which all spine nodes are bi-connected through leaves with degree
   two, but the remaining leaves all have degreee one and are evenly
   distributed across the spines.

   Constructively, we can create a Xia topology by iterating through the
   spines.  Each spine can be connected to the next spine by selecting
   any unused leaf.  Since leaves are connected to all spines, all
   leaves will have a connection to both the first and second spine and
   we can therefore choose any leaf without loss of generality.
   Continuing this iteration across all of the spines, selecting a new
   leaf at each iteration, will result in a path that connects all
   spines.  Adding one more leaf between the last and first spine will
   produce a cycle of n spines and n leaves.

   At this point, m-n leaves remain unconnected.  These can be
   distributed evenly across the remaining spines, connected by a single
   link.

   Xia topologies represent a compromise that trades off increased risk
   and decreased performance for lower flooding amplification.  Xia



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   topologies will have a larger diameter.  For m spines, the diameter
   will be m + 2.

   In a Xia topology, some leaves are singly connected.  This represents
   a risk in that in some failures, convergence may be delayed.
   However, there may be some alternate behaviors that can be employed
   to mitigate these risks.  If a leaf node sees that its single link on
   the flooding topology has failed, it can compensate by performing a
   database sychronization check with a different spine.  Similarly, if
   a leaf determines that its connected spine on the flooding topology
   has failed, it can compensate by performing a database
   synchronization check with a different spine.  In both of these
   cases, the synchronization check is intended to ameliorate any delays
   in link state propagation due to the fragmentation of the flooding
   topology.

   The benefit of this topology is that flooding load is easily
   understood.  Each node in the spine cycle will never receive an
   update more than twice.  For n leaves and m spines, a spine never
   transmits more than m/n updates.

4.3.3.  Optimization

   If two systems have multiple links between them, only one of the
   links should be part of the flooding topology.  Moreover, symmetric
   selection of the link to use for flooding is not required.

4.4.  Encoding the Flooding Topology

   There are a variety of ways that the flooding topology could be
   encoded efficiently.  If the topology was only a cycle, a simple list
   of the nodes in the topology would suffice.  However, this is
   insufficiently flexible as it would require a different encoding
   scheme as soon as a single additional link is added.  In anticipation
   of richer flooding topologies, we recommend the advertisement of the
   full adjacency matrix of the flooding topology.

   We can assume that all links are bidirectional, so we can represent
   each link with a single bit.  The matrix can then be represented as
   the list of nodes, plus one bit per possible link.  This results in N
   * (N -1)/2 possible bits for links.  This can be further reduced by
   sparse matrix techniques.

5.  Applicability

   In a complete graph, this approach is appealing because it
   drastically decreases the flooding topology without the manual
   configuration of mesh groups.  By controlling the diameter of the



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   flooding topology, as well as the maximum degree node in the flooding
   topology, convergence time goals can be met and the stability of the
   control plan can be assured.

   Similarly, in a massively scaled data center, where there are many
   opportunities for redundant flooding, this mechanism ensures that
   flooding is redundant, with each leaf and spine well connected, while
   ensuring that no update need make too many hops and that no node
   shares an undue portion of the flooding effort.

6.  Acknowledgements

   The author would like to thank Zeqing (Fred) Xia, Naiming Shen, Adam
   Sweeney, and Olufemi Komolafe for their helpful comments.

7.  IANA Considerations

   This memo includes no request to IANA.

8.  Security Considerations

   This document introduces no new security issues.  Security of routing
   within a domain is already addressed as part of the routing protocols
   themselves.  This document proposes no changes to those security
   architectures.

9.  References

9.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/info/rfc2119>.

9.2.  Informative References

   [Clos]     Clos, C., "A Study of Non-Blocking Switching Networks",
              The Bell System Technical Journal Vol. 32(2), DOI
              10.1002/j.1538-7305.1953.tb01433.x, March 1953,
              <http://dx.doi.org/10.1002/j.1538-7305.1953.tb01433.x>.

   [ISO10589]
              International Organization for Standardization,
              "Intermediate System to Intermediate System Intra-Domain
              Routing Exchange Protocol for use in Conjunction with the
              Protocol for Providing the Connectionless-mode Network
              Service (ISO 8473)", ISO/IEC 10589:2002, Nov. 2002.



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   [Leiserson]
              Leiserson, C., "Fat-Trees: Universal Networks for
              Hardware-Efficient Supercomputing", IEEE Transactions on
              Computers 34(10):892-901, 1985.

   [RFC2973]  Balay, R., Katz, D., and J. Parker, "IS-IS Mesh Groups",
              RFC 2973, DOI 10.17487/RFC2973, October 2000,
              <https://www.rfc-editor.org/info/rfc2973>.

   [RFC5340]  Coltun, R., Ferguson, D., Moy, J., and A. Lindem, "OSPF
              for IPv6", RFC 5340, DOI 10.17487/RFC5340, July 2008,
              <https://www.rfc-editor.org/info/rfc5340>.

   [RFC7938]  Lapukhov, P., Premji, A., and J. Mitchell, Ed., "Use of
              BGP for Routing in Large-Scale Data Centers", RFC 7938,
              DOI 10.17487/RFC7938, August 2016,
              <https://www.rfc-editor.org/info/rfc7938>.

Author's Address

   Tony Li
   Arista Networks
   5453 Great America Parkway
   Santa Clara, California  95054
   USA

   Email: tony.li@tony.li
























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