A Routing Algorithm with Candidate Shortest Path

An improved algorithm based on the next node routing principle is proposed in this paper.In this algorithm there is a column added to the classical routing table, in which the candidateshortest distance to the destination node is the entry. When a link fails, the new shortest path inthe nodes connected directly with the failure link can be found immediately (it is just thecandidate shortest path before failure). For all other nodes in which routing tables should bechanged, the required number of control messages and time for convergence are also less thanTajibnapis' algorithm and Predecessor algorithm. The message looping problem does not existin duplex loop networks and is radically improved in mesh networks. These statements areproved by the analysis and simulation in this paper. From the simulation results of a 30-nodemesh network, when one link goes down, the total number of control messages generatedduring convergence with this algorithm on the average is about 30% of Tajibnapis' algorithm.The iterations required is 50% of Tajibnapis' algorithm. The memory space required andcomputation complexity in nodes are almost the same as the two algorithms mentioned aboveand the algorithm implementation is as easy as well.

A routing algorithm with candidate shortest path

An improved algorithm based on the next node routing principle is proposed in this paper. In this algorithm there is a column added to the classical routing table, in which the candidate shortest distance to the destination node is the entry. When a link fails, the new shortest path in the nodes connected directly with the failure link can be found immediately (it is just the candidate shortest path before failure). For all other nodes in which routing tables should be changed, the required number of control messages and time for convergence are also less than Tajibnapis‖ algorithm and Predecessor algorithm. The message looping problem does not exist in duplex loop networks and is radically improved in mesh networks. These statements are proved by the analysis and simulation in this paper. From the simulation results of a 30-node mesh network, when one link goes down, the total number of control messages generated during convergence with this algorithm on the average is about 30% of Tajibnapis‖ algorithm. The iterations required is 50% of Tajibnapis‖ algorithm. The memory space required and computation complexity in nodes are almost the same as the two algorithms mentioned above and the algorithm implementation is as easy as well.