A reduced search space routing algorithm for large-scale cognitive radio wireless

The problem of finding the shortest route between a source and a destination in a large-scale network is investigated. A simple and efficient technique to reduce the network search space size based on nodes position information is developed. Following the proposed technique, it is shown that the route found within the reduced search space has the same number of hops as that obtained when solving the problem considering the large-scale network as the number of nodes increases. Furthermore, the proposed technique provides a significant complexity reduction. The proposed algorithm is also applied to cognitive radio networks to analyze route throughput. Compared to the average link throughput obtained via solving the large-scale network, a negligible throughput degradation is noticed and a remarkable complexity reduction is obtained.

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