Example of Distance Vector Routing 1 - Georgia Tech - Network Implementation

Summary

The script explains the concept of distance vector routing in a three-node network, illustrating how each node initially has a single distance vector for the shortest path to each other node. It demonstrates the process of nodes sharing their distance vectors and updating their routing tables using the Bellman-Ford equation, leading to a complete routing table for the network. The script also touches on the issue of slow convergence when network failures occur, highlighting the challenge of 'bad news' traveling slowly.

Takeaways

• 📐 The script describes a three-node network with edge costs and initial distance vectors representing the shortest path between nodes.
• 🔄 Each node starts with a single distance vector and updates it based on the Bellman-Ford equation when receiving vectors from adjacent nodes.
• 🔄 The Bellman-Ford equation is used to compute the shortest path cost by summing the distances through intermediate nodes.
• 👀 Node x initially doesn't know about the shorter path between x and z via y, which is a key point in understanding the network's initial state.
• 🔄 When node x learns y's distance vector, it updates its shortest path to z from five to three, demonstrating the routing update process.
• 🔄 Node x also receives a distance vector from z, which it uses to further refine its routing table.
• 🔄 The process of updating routing tables is iterative and involves all nodes in the network until each has a complete routing table.
• 📉 The network converges quickly when costs decrease, indicating efficient routing updates in response to cost changes.
• 🚨 The script highlights a problem with distance vector routing: bad news (failures) can travel slowly, affecting network reliability.
• 🔄 Distance vector routing relies on the exchange of distance vectors between adjacent nodes to update routing information.
• 🔄 The script emphasizes the dynamic nature of routing in a network, where nodes continuously update their routing tables based on new information.
• 🔄 The example provided illustrates the importance of accurate and timely information exchange in maintaining an efficient and reliable network.

Q & A

What is the initial shortest path cost between node x and node y?

The initial shortest path cost between node x and node y is one, which is the direct path between them.

What is the initial shortest path cost from node x to node z according to node x?

The initial shortest path cost from node x to node z is five, as x only knows about the direct path.

Why does node x not know about the shorter path between x and z via y?

Node x does not know about the shorter path between x and z via y because it has not yet received the updated distance vector from node y.

How does distance vector routing work in updating routing tables?

In distance vector routing, each node sends its distance vectors to every adjacent node, and then updates its routing table according to the Bellman-Ford equation by calculating the minimum sum of distances through any intermediate node.

What happens when node x learns of node y's distance vectors?

When node x learns of node y's distance vectors, it updates its shortest path cost to node z from five to three, by adding the cost between x and y (one) to the distance between y and z (two).

How does the Bellman-Ford equation help in updating the shortest path costs?

The Bellman-Ford equation is used to update the shortest path costs by comparing the current known cost to a node with the cost calculated by adding the current node's cost to the next node's cost to the destination.

What is the updated shortest path cost from node x to node z after receiving node y's distance vectors?

After receiving node y's distance vectors, the updated shortest path cost from node x to node z is three, computed as the sum of the cost between x and y (one) and the distance between y and z (two).

How does the network react when the costs decrease?

When costs decrease, the network converges quickly as nodes update their routing tables with the new, lower cost paths as they receive updated distance vectors from adjacent nodes.

What is the issue mentioned when failures occur in the network?

When failures occur, bad news can travel slowly because it takes time for the updated distance vectors reflecting the failure to propagate through the network, leading to potential routing inefficiencies or loops.

How does the network eventually achieve a complete routing table?

The network achieves a complete routing table as each node iteratively receives and processes distance vectors from other nodes, updating their routing tables until all nodes have the shortest path costs to all other nodes.

What is the significance of the Bellman-Ford equation in distance vector routing?

The Bellman-Ford equation is significant in distance vector routing as it allows nodes to dynamically update their routing tables with the shortest path costs, even in the presence of changing network conditions or failures.

Outlines

00:00

🔄 Introduction to Distance Vector Routing

This paragraph introduces the concept of distance vector routing in a three-node network. It explains the initial state of the network with predefined edge costs and the nodes' understanding of the shortest path costs to each other. The paragraph also describes how each node starts with a single distance vector and how they are unaware of potentially shorter paths that exist but are not yet known. The process of nodes sharing their distance vectors with adjacent nodes and updating their routing tables using the Bellman-Ford equation is outlined, highlighting the dynamic nature of route calculation and the eventual convergence to a complete routing table as nodes learn about each other's distance vectors.

Keywords

💡Three node network

A 'three node network' refers to a simple network topology consisting of three interconnected nodes. In the context of the video, it is used to demonstrate the principles of distance vector routing. The script describes a scenario where each node has an initial understanding of the shortest path costs to other nodes, which is essential for understanding how routing updates and distance vector algorithms work.

💡Distance vector

A 'distance vector' is a routing mechanism where each node in a network shares the shortest path cost to each of its neighboring nodes. It is central to the video's theme as it illustrates how nodes communicate and update their routing tables based on the shortest known paths. The script uses the concept to explain how nodes x, y, and z initially perceive their connections and later update these perceptions as they learn about more optimal paths.

💡Shortest path cost

The 'shortest path cost' is the minimum cost or distance required to reach a destination node from a source node. It is a fundamental concept in the video, as the entire routing process revolves around finding and updating these costs. The script provides examples of how nodes x, y, and z initially have different perceptions of the shortest path costs to each other.

💡Bellman-Ford equation

The 'Bellman-Ford equation' is an algorithm used to compute the shortest paths from a single source node to all other nodes in a network. It is integral to the video's explanation of how nodes update their routing tables. The script describes how each node uses this equation to calculate the minimum cost to reach other nodes through intermediate nodes.

💡Routing table

A 'routing table' is a data file used by routers to determine the next hop for packets in a network. In the video, the concept is used to explain how nodes maintain and update their knowledge of the network's topology and the best paths to other nodes. The script illustrates the process of nodes updating their routing tables as they receive new distance vector information.

💡Convergence

In the context of networks, 'convergence' refers to the process by which all nodes in a network agree on the same information, such as routing paths and costs. The video discusses how the network converges quickly when costs decrease, highlighting the efficiency of the distance vector routing process when conditions are favorable.

💡Failures

In the script, 'failures' refer to disruptions or issues within the network that can affect routing. The video points out that when failures occur, the dissemination of updated routing information can be slow, which is a potential drawback of the distance vector routing method.

💡Bad news travels slowly

The phrase 'bad news travels slowly' is used metaphorically in the video to describe a situation where negative changes in the network, such as increased costs or failures, are not quickly propagated to all nodes. It emphasizes the potential delay in routing updates that can occur in distance vector routing when the network experiences issues.

💡Direct path

A 'direct path' is a route between two nodes with no intermediate nodes. The video uses this term to describe the initial known routes between nodes x, y, and z, which are later improved upon as nodes learn about more efficient paths through other nodes.

💡Intermediate node

An 'intermediate node' is any node that lies between the source and destination nodes in a network path. The video explains how nodes update their routing decisions by considering the costs through all possible intermediate nodes, as illustrated by node x updating its path to z via node y.

💡Costs decrease

The term 'costs decrease' in the video refers to a scenario where the path costs between nodes become lower. It is used to highlight how the network's routing can quickly adapt and converge to these new, more optimal conditions, demonstrating the responsiveness of the distance vector routing process.

Highlights

Introduction of a three-node network model with edge costs.

Initial single distance vector representation for shortest path costs.

Zero cost for the direct path between a node and itself.

Direct path cost from x to y is one.

Initial unknown shorter path from x to z via y.

Explanation of distance vector routing and its mechanism.

Node x updating its routing table using Bellman-Ford equation.

Node x learning of node y's distance vector and updating its path to z.

Calculation of the new shortest path cost from x to z as three.

Reception of distance vector from z by node x.

Update of the distance between z and x to three using Bellman-Ford.

Propagation of updated routing information across the network.

Achievement of complete routing tables for all nodes.

Network's quick convergence when costs decrease.

The issue of slow propagation of bad news during failures.

The importance of understanding routing updates in network failures.

The theoretical contribution of Bellman-Ford in routing algorithms.

Practical applications of distance vector routing in network topologies.

Transcripts

Let's suppose that we have a three node network with the costs on the edges as

shown. Initially, each node has a single distance

vector representing the shortest path cost to each other

incident node in the graph. For example, the

distance between x and x is obviously zero.

And the shortest known distance between x and

y, from x's perspective is one, the direct path.

Similarly, the shortest known distance between x and z

to x at the outset is five because all

it knows is the direct path. Note that a

shorter path between x and z exists via y,

but x simply doesn't know about it yet. Now

in distance vector routing, every node send its vectors

to every other adjacent node. And each node then

updates its routing table according to the Bellman-Ford equation.

Let's look at what happens when node x learns of y's distance vectors. Well in

this case, the distance from x to z will be computed as the minimum of the

sums of all distances to z through any

intermediate node. So the cost between x and

y is one, and the distance between y and z as discovered by y's distance vector

is two. Therefore, x can update its shortest

cost distance to z as three. Similarly, x

will receive a distance vector from z, five

two zero, but of course, when it uses

the Bellman-Ford equation to update its distances, again

the distance between z and x will be

updated from five to three. We can repeat

this exercise at other nodes, as they receive distance

vectors from other nodes in the topology. And quickly, every

node in the network has a complete routing table. Now

when costs decrease, the network converges quickly but one problem

is that when failures occurs, bad news can actually travel slowly.