Experimental analysis of dynamic algorithms for the single source shortest paths problem
Journal of Experimental Algorithmics (JEA)
Deriving traffic demands for operational IP networks: methodology and experience
IEEE/ACM Transactions on Networking (TON)
OSPF Network Design Solutions
OSPF: Anatomy of an Internet Routing Protocol
OSPF: Anatomy of an Internet Routing Protocol
IEEE Transactions on Network and Service Management
Optimizing OSPF routing using accelerated iterative heuristic
AIKED'09 Proceedings of the 8th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Parallel tabu search for optimizing the OSPF weight setting problem
WSEAS TRANSACTIONS on COMMUNICATIONS
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Setting weights for Open Shortest Path First (OSPF) routing protocol is an NP-hard problem. Optimizing these weights leads to less congestion in the network while utilizing link capacities efficiently. In this paper, Simulated Evolution (SimE), a non-deterministic iterative heuristic, is engineered to solve this problem. A cost function that depends on the utilization and the extra load caused by congested links in the network is used. A goodness measure which is a prerequisite of SimE is designed to solve this problem. The proposed SimE algorithm is compared with Simulated Annealing. Results show that SimE explores search space intelligently due to its goodness function feature and reaches near optimal solutions very quickly.