In a distance vector algorithm (like bellman ford) each machine directly exchanges information (vectors) with every other machine? true or false
The correct answer and explanation is:
Correct Answer: False
In a distance vector algorithm such as the Bellman-Ford algorithm, each machine or node does not directly exchange information with every other machine in the network. Instead, each node only communicates with its immediate neighbors, meaning those nodes that are directly connected to it by a network link.
The distance vector algorithm works by having each node maintain a routing table (or distance vector) that contains the best-known distances to all other nodes in the network. Initially, each node only knows the distance to its directly connected neighbors. Over time, it learns about the rest of the network through periodic exchanges of distance vectors with its neighbors.
Each node shares its distance vector with its immediate neighbors. When a node receives a distance vector from a neighbor, it uses the Bellman-Ford equation to update its own routing table. The update is based on the principle that the best path to a destination may be through one of the neighbors. By continuously sharing and updating this information, the network gradually converges to the correct shortest paths between all pairs of nodes.
This localized information exchange makes distance vector algorithms relatively simple and efficient for smaller or less dynamic networks. However, it also means they can suffer from problems such as slow convergence and routing loops, especially in large or frequently changing networks.
In contrast, link-state algorithms (like OSPF) require each node to have knowledge of the entire network topology and involve broadcasting information to all nodes. That is not the case with distance vector algorithms, which rely on neighbor-to-neighbor communication only.
So, in summary, in a distance vector routing protocol, each node does not directly exchange routing information with all other nodes, only with its neighboring nodes.