Distance Vector Routing Workbench

Step through neighbor advertisements, Bellman-Ford updates, convergence rounds, route choices, and distance-vector limitations

Interactive distance-vector routing animation for learning distributed Bellman-Ford convergence, neighbor advertisements, routing tables, next-hop selection, equal-cost paths, and RIP-style limitations.

Animation Distance Vector Bellman-Ford Convergence

Distance Vector Routing Workbench

Watch routers learn shortest paths by exchanging distance vectors with neighbors. Each step shows one neighbor advertisement, the Bellman-Ford test a receiver applies, and the route table changes that move the network toward convergence.

Round 0Advertisement pass

ReadyCurrent exchange

0 updatesRoute improvements

A to E: directSelected route

Scenarios

Controls

Focus router A

Destination E

What To Watch

Distance-vector routing is local: a router trusts neighbor advertisements, adds the link cost to that neighbor, and installs the lower total.

AdvertisementThe orange line is the neighbor vector currently being received.

Update ruleReceiver tests cost(receiver, neighbor) + neighbor distance.

ConvergenceStable means a full pass completed with no table changes.

LimitationFailure recovery is harder; see count-to-infinity for bad-news behavior.

Distributed Bellman-Ford Scene

Waiting for first advertisement

D(A,E) = direct 8Current Bellman-Ford test

No advertisement yetReceiver decision

Not convergedNetwork stability

Routing Table View

Learning Diagnosis

Route pendingStep through advertisements to see how the selected path is learned.

Protocol behaviorOnly neighbor vectors and local link costs are used; no router sees the full topology.

Failure cautionNormal convergence is shown here. Cost increases and failures require safeguards such as triggered updates, split horizon, poison reverse, or hold-down behavior.

Step Trace

Quick Reference

Distance Vector

• Each router stores destination, metric, and next hop.
• Routers advertise their current vector to direct neighbors.
• The algorithm converges by repeated local improvements.

Bellman-Ford Test

• Candidate = link cost to neighbor + neighbor's advertised cost.
• Install the candidate when it is lower than the current cost.
• Equal candidates are ties; protocols may install one or support ECMP.

RIP Context

• RIP uses hop count, with 16 meaning infinity.
• This workbench uses additive teaching costs to show the general rule.
• Real protocols add timers, invalidation, and loop-reduction rules.

How To Read The Animation

Orange ExchangeThe sender advertises its current table. The receiver does not learn anything from non-neighbor routers directly.

Green PathThe selected router's current next-hop chain toward the selected destination. It can change as lower metrics are discovered.

Changed RowsOrange table rows are the entries improved by the latest advertisement. A stable round with no changes means convergence for this model.

Technical Accuracy Notes

What Is ModeledThe page models distributed Bellman-Ford with positive additive metrics and asynchronous neighbor advertisements. It is suitable for explaining RIP-style distance-vector convergence.

What Is SimplifiedPacket format, update timers, invalid timers, hold-down timers, route tags, authentication, and policy controls are intentionally omitted to keep the convergence mechanism visible.

Failure ScopeFailure recovery is mentioned but not simulated in detail here because bad-news behavior and count-to-infinity are covered in the dedicated count-to-infinity workbench.

Source Links

RFC 1058 - Routing Information ProtocolClassic RIP description, including distance-vector operation and infinity behavior.

RFC 2453 - RIP Version 2RIPv2 routing table, metric, and update behavior for a widely taught distance-vector protocol.

RFC 8966 - Babel Routing ProtocolModern distance-vector protocol context showing that real implementations add loop-avoidance and feasibility logic.