IS-IS Optimal Distributed Flooding for Dense Topologies

The goal of this draft is to solve one specific set of problems involved in operating a link state protocol in a densely meshed topology. The problem with such topologies is the connectivity density, which causes too many copies of identical information to be flooded. Analysis and experiment show, for instance, that in a butterfly fabric of around 2500 intermediate systems, each intermediate system will receive more than 40 copies of any changed LSP fragment. This not only wastes bandwidth and processor time, this dramatically slows convergence speed. This document describes a set of modifications to existing IS-IS flooding mechanisms which minimize the number of LSP fragments received by individual intermediate systems, in its extreme version to one copy per intermediate system. The mechanisms described in this document are similar to those implemented in OSPF to support mobile ad-hoc networks, as described in , , and . These mechanisms have been widely implemented and deployed.

The following people have contributed to this draft: Abhishek Kumar, Nikos Triantafillis, Ivan Pepelnjak, Christian Franke, Hannes Gredler, Les Ginsberg, Naiming Shen, Uma Chunduri, Nick Russo, Shawn Zandi, and Rodny Molina.

Laboratory tests show modifications similar to these reduce flooding in a large scale emulated butterfly network topology; without these modifications, intermediate systems receive, on average, 40 copies of any changed LSP fragment. With the modifications described in this document intermediate systems recieve, on average, two copies of any changed LSP fragment. In many cases, each intermediate system receives only a single copy of each changed LSP. In terms of performance, the modifications described here cut convergence times in half. Processor load times were not checked, as this was an emulated environment. A mechanism similar to the one described in this document has been implemented in the FR Routing open source routing stack as part of fabricd.

The following spine and leaf fabric will be used to describe these modifications.

To reduce confusion (spine and leaf fabrics are difficult to draw in plain text art), this diagram does not contain the connections between devices. The reader should assume that each device in a given layer is connected to every device in the layer above it. For instance: 5A is connected to 4A, 4B, 4C, 4D, 4E, and 4F 5B is connected to 4A, 4B, 4C, 4D, 4E, and 4F 4A is connected to 3A, 3B, 3C, 3D, 3E, 3F, 5A, 5B, 5C, 5D, 5E, and 5F 4B is connected to 3A, 3B, 3C, 3D, 3E, 3F, 5A, 5B, 5C, 5D, 5E, and 5F etc. The tiers or stages of the fabric are also marked for easier reference. T0 is assumed to be connected to application servers, or rather they are Top of Rack (ToR) intermediate systems. The remaining tiers, T1 and T2, are connected only to other devices in the fabric itself. A common alternate representation of this topology is drawn "folded" with T2, the "top of fabric," shown on top, while T1 is shown below, and T0 below T1.

Flooding is perhaps the most challenging scaling issue for a link state protocol running on a dense, large scale topology. This section describes detailed modifications to the IS-IS flooding process to reduce flooding load in a densely meshed topology.

The simplest way to conceive of the solution presented here is in two stages: Stage 1: Forward Optimization Find the group of intermediate systems that will all flood to the same set of neighbors as the local IS Decide (deterministically) which subset of the intermediate systems within this group should re-flood any received LSPs Stage 2: Reverse Optimization Find neighbors on the shortest path towards the origin of the change Do not flood towards these neighbors The first stage is best explained through an illustration. In the network above, if 5A transmits a modified Link State Protocol Data Unit (LSP) to 4A-4F, each of 4A-4F will, in turn, flood this modified LSP to 3A (for instance). 3A will receive 6 copies of the modified LSP, while only one copy is necessary for the intermediate systems shown to converge on a single view of the topology. If 4A-4F could determine they will all flood identical copies of the modified LSP to 3A, it is possible for all of them except one to decide not to flood the changed LSP to 3A. The technique used in this draft to determine the flooding group is for each intermediate system to calculate a special Shortest-path Spanning Tree (SPT) from the point of view of the transmitting neighbor. By setting the metric of all links to 1 and truncating the SPT to two hops, the local IS can find the group of neighbors it will flood any changed LSP towards and the set of intermediate systems (not necessarily neighbors) which will also flood to this same set of neighbors. If every intermediate system in the flooding set performs this same calculation, they will all obtain the same flooding group. Once this flooding group is determined, the members of the flooding group will each (independently) choose which of the members should re-flood the received information. Each member of the flooding group calculates this independently of all the other members, but a common hash MUST be used across a set of shared variables so each member of the group comes to the same conclusion. The group member which is selected to flood the changed LSP does so normally; the remaining group members do not flood the LSP. Note there is no signaling between the intermediate systems running this flooding reduction mechanism. Each IS calculates the special, truncated SPT separately, and determines which IS should flood any changed LSPs independently based on a common hash function. Because these calculations are performed using a shared view of the network, however (based on the common link state database) and a shared hash function, each member of the flooding group will make the same decision. The second stage is simpler, consisting of a single rule: do not flood modified LSPs along the shortest path towards the origin of the modified LSP. This rule relies on the observation that any IS between the origin of the modified LSP and the local IS should receive the modified LSP from some other IS closer to the source of the modified LSP.

Each intermediate system will determine whether it should re-flood LSPs as described below. When a modified LSP arrives from a Transmitting Neighbor (TN), the result of the following algorithm obtains the necessary decision: Step 1: Build the Two-Hop List (THL) and Remote Neighbor's List (RNL) by: Set all link metrics to 1 Calculate an SPT truncated to 2 hops from the perspective of TN For each IS that is two hops (has a metric of two in the truncated SPT) from TN: If the IS is on the shortest path towards the originator of the modified LSP, skip If the IS is not on the shortest path towards the originator of the modified LSP, add it to THL Add each IS that is one hop away from TN to the RNL Step 2: Sort RNL by system IDs, from the least to the greatest. Step 3: Calculate a number, N, by adding each byte in LSP-ID (without the fragment ID) and fragment ID MOD 2 (allowing for some balancing of LSPs coming from same system ID without introducing excessive amount of state in an implementation) and then taking MOD on the number of neighbors. N MUST be less than the number of members of RNL. Step 4: Starting with the Nth member of RNL: If THL is empty, exit If this member of RNL is the local calculating IS, this IS MUST reflood the modified LSP; exit Remove all members of THL connected to (adjacent to) this member of RNL Move to the next member of RNL, wrapping to the beginning of RNL if necessary Note: This description is geared to clarity rather than optimal performance.

It is possible in some failure modes for flooding to be incomplete because of the flooding optimizations outlined. Specifically, if a reflooder fails, or is somehow disconnected from all the links across which it should be reflooding, it is possible an LSP is only partially flooded through the fabric. To prevent such partition failures, an intermediate system which does not reflood an LSP (or fragment) should: Set a short timer; the default should be one second When the timer expires, send Partial Sequence Number Packet (PSNP) of all LSPs that have not been reflooded during the timer runtime to all neighbors unless an up-to-date PSNP or CSNP has been already received from the neighbor Process any Partial Sequence Number Packets (PSNPs) received that indicate that neighbors still have older versions of the LSP per normal protocol procedures to resynchronize If resynchronization above a configurable threshold is required, an implementation SHOULD notify the network operator

Assume, in the network above, 5A floods some modified LSP towards 4A-4F. To determine whether 4A should flood this LSP to 3A-3F: 5A is TN; 4A calculates a truncated SPT from 5A's perspective with all link metrics set to 1 4A builds THL, which contains 3A, 3B, 3C, 3D, 3E, 3F, 5B, 5C, 5D, 5E and 5F 4A builds RNL, which contains 4A,4B,4C,4D,4E and 4F, sorting it by the system ID 4A computes hash on the received LSP-ID to get N; assume N is 1 in this case Since 4A is the Nth member of R-NL and there are members in N-NL, 4A must reflood; the loop exits

The calculations described here are complex, which might lead the reader to conclude that the cost of calculation is so much higher than the cost of flooding that this optimization is counter-productive. The description provided here is designed for clarity rather than optimal calculation, however. Many of the calculations can be performed in advance and stored, rather than being performed for each LSP and each neighbor. Optimized versions of the process described here have been implemented, and do result in strong convergence speed gains.