Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks Page: 5
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nodes in the network. After receiving the update information from a neigh-
boring node, a node ni updates its own routing table in the following manner
(Hedrick 1988; Malkin and Streenstrup 1995):
D(i,j) = Vi (1)
min[d(i, k) + D(k, j)] V nk adjacent to n2
where D(i, j) represents the metric of the best route from node ni to node nj
currently known to ni. d(i, k) represents the cost of traversing the link from
node ni to node nk. Any node ni that receives D(k,j) from a neighbor nk,
computes D(i, j) based on equation(1) and integrates this value in its routing
table. When the routing table of ni is updated, the changes are propagated
to all neighbors, which in turn perform the same algorithm. Therefore, an
update in one routing table can cause a sequence of update messages in nodes
throughout the entire network.
In ADVR, the exchange of the metrics and the process of route discovery
moves from the nodes to the agents. Hence in this approach, route discovery
and updates are manifested in the movement of agents carrying routing infor-
mation from one node to another rather than the propagation of individual up-
date messages. Agents in ADVR can be formally described as: A(i, x, y, Rx, 'y),
where A is an Agent with ID i migrating from node n to node ny, carrying the
routing table R, and using the migration strategy 7 to move among adjacent
nodes. R, is a subset of r,, the routing table of n, (See Figure 1).
In ADVR, agents start at arbitrary nodes and migrate to adjacent nodes using
y. Upon arriving at a node ny, an agent A(i, x, y, Rx, y) updates the routing
table R, based on the following equation:
D(y, j) = min(D(y, j), [d(y, x) + D(x, j)]) V nj in Rx (2)
where D(x, j) is an entry in Rx. After performing the update, the agent selects
R, and migrates to an adjacent node using migration strategy y.
At every node the agent has to make a decision regarding the routing data
it would carry to the next node. This decision plays an important role in
providing a resource efficient solution with ADVR. If the agent carries the en-
tire routing table available at each node, it would incur excessive overhead in
transferring redundant data. On the other hand, if the agent selected a subset
of total routing data available at the node, it would unnecessarily delay the
propagation of important routing information. The flexibility adopted by the
agents in selecting the routing data reflects the inherent degree of intelligence
acquired by it. It is important for the agents to execute certain book keep-
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Amin, Kaizar A. & Mikler, Armin R. Agent-based Distance Vector Routing: A Resource Efficient and Scalable approach to Routing in Large Communication Networks, article, March 25, 2002; [New York, New York]. (digital.library.unt.edu/ark:/67531/metadc111275/m1/5/: accessed November 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.